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<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1.0, maximum-scale=2.0"> <meta http-equiv="content-type" content="text/html; charset=utf-8"/> <meta name="apple-mobile-web-app-capable" content="yes"> <meta name="apple-itunes-app" content="app-id=1654786709"> <meta name="description" content="How do you connect the needs of researchers to the capabilities of technology? What are the main stages of research and the challenges faced at each stage? And will AI and machine learning speed up research and get solutions to market faster? We will learn those answers and more in this episode with Dr. Mark Hoffman, the Chief Research Information officer for Children’s Mercy and the Children’s Mercy Research Institute, a position he has held since 2016. Dr. Hoffman earned his doctorate in Bacteriology from the University of Wisconsin-Madison. He later joined Cerner as a software engineer where he advanced to the role of Vice President for Genomics and Research. Dr. Hoffman was also part of the faculty at the University of Missouri Kansas City (UMKC) in the Departments of Biomedical and Health Informatics and Pediatrics. His formal training in research and experience in software development has prepared him to connect the needs of researchers to the capabilities of technology. His work is focused on identifying the best capabilities possible to meet rapidly changing requirements in genomics, public health, and big data. Dr. Hoffman is an inventor of 22 issued patents, a member of the American Academy of Inventors, a TED talk alumnus, and an award-winning healthcare product developer. You can learn more about Dr. Hoffman and Children’s Mercy here: Learn more about Oracle for Researcher here: ---------------------------------------------------------- Episode Transcript 00;00;00;00 - 00;00;26;02 What are the three main stages of research and the challenges each are facing? How are researchers handling the new federal policies around data sharing? And will AI and machine learning speed research and get solutions to market faster? We'll get those answers and more on this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research. &nbsp; 00;00;26;02 - 00;00;49;21 I'm Mike Stiles. And today our guest is Dr. Mark Hoffman, who is the Chief Research Information Officer for Children's Mercy and the Children's Mercy Research Institute. That's a position he's held since 2016. Dr. Hoffman earned his doctorate in bacteriology from the University of Wisconsin-Madison and later joined Cerner as a software engineer, where he went on to be Vice President for genomics and research. &nbsp; 00;00;49;24 - 00;01;17;11 Dr. Hoffman was also part of the faculty at the University of Missouri, Kansas City, and the Departments of Biomedical and Health Informatics and Pediatrics. Now, because he's had formal training and research and real-world experience in software development, he's kind of uniquely qualified to talk about what researchers need when it comes to technology. His work focuses on identifying the best capabilities to meet requirements in genomics, public health and big data that are always changing. &nbsp; 00;01;17;14 - 00;01;38;22 He's an inventor of 95 issued patents, a member of the American Academy of Inventors, a TED Talk alumnus, and an award-winning health care product developer. And honest to gosh, that's about the shortest intro I could come up with for someone who is so accomplished. So, we're glad you are with us today, Dr. Hoffman. Well, thanks, Mike. I look forward to talking with you. &nbsp; 00;01;38;24 - 00;02;05;06 Our audience is going to be particularly lucky that they decided to stream this episode because there's a lot to cover. But first of all, what got you into research to begin with? Kind of what led you to each step along the way to where you are now at Children's Mercy? Well, it's a long story, but, you know, I think as a kid, I was always curious and I enjoyed Legos and, you know, taking things apart. &nbsp; 00;02;05;06 - 00;02;36;00 And so, in hindsight, I see all the foundations. And that took me a while to realize that my interests are really split between doing science and building technologies. And so, I see myself as very fortunate to have a role that lets me keep one foot in each of those areas of interest. So, you went when you made the decision to go to Cerner and go into that software development world. &nbsp; 00;02;36;02 - 00;03;05;24 What inspired you to do that? It's interesting. When I was in graduate school studying bacteriology, I was funded by an NIH program that if you're in the life sciences, you were required to take coursework outside the life sciences. I chose to do that in computer science. And then the other requirement was you were required to do an industry internship one summer. &nbsp; 00;03;05;26 - 00;03;31;27 Most of my peers chose to do that in pharma. I chose instead to do my internship at a software development company that does bioinformatics software development. Realized how much I liked that type of work and building things that get used in the real world. It's funny, but to this day, some of the features that I developed are still part of their application suite. &nbsp; 00;03;31;27 - 00;04;04;27 So, I learned from that that I enjoy the software and technology and development process. When there was the opportunity to join Cerner as a software engineer. I jumped at it and happened to be in their microbiology product line, so I was able to talk with the clients about what they were struggling with in the lab, understand that, and then translate that into whatever changes were needed in the software. &nbsp; 00;04;05;00 - 00;04;26;28 Did you expect that to be the case that you would be able to keep a foot in both sides on both the technology and the research side? Or was that something like you never thought that could happen? I didn't plan it this way, but I feel very fortunate that I'm able to exercise so many of my different interests. &nbsp; 00;04;27;00 - 00;05;12;19 So obviously children's mercy benefits from your professional expertise, but behind that you've got a real personal commitment and passion for the work that you're doing that kind of increases your value even more. If you're willing, tell us about that personal connection. And just in general, both Cerner and Children's Mercy are based in Kansas City. And as a parent, while I was working at Cerner, over time, both of our children have needed inpatient care at Children's Mercy Hospital and just the compassion and caring and quality of care and the creativity that we often saw with some of our children's physicians. &nbsp; 00;05;12;22 - 00;05;55;21 The willingness to keep trying things until they could help our kids work through their different health concerns has made a huge impression on me. Now, when I walk through the hospital and see parents with their kids who are going through really some of the most difficult situations you can imagine, I try to take a moment and share a smile or, you know, hold the elevator for a parent. I'm just trying to even though I'm not involved in patient care, I just really am empathetic to those families and see that as really kind of my connection to purpose. &nbsp; 00;05;55;24 - 00;06;35;13 What are the unique differences between a children's centered health care provider like that and, say, a regular adult hospital? What are the biggest differences that the staff has to operate with? I think probably the key difference is with adult medicine, you're really working primarily with the patient and they're making their own decisions. In pediatrics, you're working with children and they're their care providers so that there's more voices involved, you know, with younger children. &nbsp; 00;06;35;14 - 00;07;08;04 It's really is the care providers who are making those decisions with teenagers and adolescents, they certainly will have their own voice into the decision making. So that's really a key difference in pediatrics. I think pediatric medicine is interesting because it's both very cautious but also very willing to innovate. And I find that often to be a really interesting dynamic. &nbsp; 00;07;08;06 - 00;07;33;07 So you were a fan, as it were, of Children's Mercy before you started working there? Absolutely. That was a big part of my decision-making process to come here. So how did that come about that you started working for Children's Mercy? And what exactly do you do there? So, I made the difficult decision to move forward in my career in 2013. &nbsp; 00;07;33;09 - 00;07;58;04 The step that I took was to join the University of Missouri, Kansas City School of Medicine, join the faculty there and form what we called the Center of Health Insights. Through those negotiations, Children's Mercy funded 25% of my role at the university. And so, I already had not quite one foot, but at least a few toes in the door. &nbsp; 00;07;58;06 - 00;08;26;19 And I spent a lot of time building relationships with Children's Mercy. About three years into that, there was some hiring of senior leadership for the Research Institute, and I was involved in that and made the case that I'm seeing other organizations create the Chief Research Information Officer role. That idea stuck and I was hired as our first chief Research Information Officer. &nbsp; 00;08;26;21 - 00;08;50;09 So it sounds like what you want, what you're kind of your North star is to make sure researchers at Children's Mercy can tap into the best technical resources and experts out there, because especially medical researchers, everyone expects them to find answers quickly. You know, there are waiting to be helped. So. What's a typical day like for a chief research information officer? &nbsp; 00;08;50;12 - 00;09;27;09 I tell everybody there really is no typical day. Sometimes I'm down in the weeds talking through technical issues and then in the next meeting can be talking with organizational ownership about high level strategy. Part of what I enjoy is the variety in my role. I don't support any single clinical area of research. So, one meeting just yesterday was with our neurology department, where we're doing research into telemedicine and that can support rural communities where children have epilepsy. &nbsp; 00;09;27;11 - 00;09;55;25 And so there was that meeting and then there was another meeting within the same 24 hours about long read genomic sequencing with our genome center. So just context shifting and you know, always with the theme though, of trying to find ways for technology to be an enabler. All too often my peers in research feel that technology sometimes creates a barrier. &nbsp; 00;09;55;25 - 00;10;25;08 And so, one of my goals is just to try to reduce the barriers and increase the opportunities. And for you, it seems like, you know, you actually see the faces of the people that this research is trying to help. Does that add yet another motivational personal element behind kind of your mission there? Absolutely. I think through the pandemic, the entire work model for people in technology in particular has changed. &nbsp; 00;10;25;10 - 00;10;55;26 I know many of us spent a long time working from home and when I was able to start coming back on site, I just find it very motivating to go to the hospital cafeteria or, you know, get out of my research and technology bubble and be among the patients and families. Well, you've met researchers of every kind all over the world, people just like those who listen to this podcast and you know how they define success and also know what challenges they face. &nbsp; 00;10;55;28 - 00;11;25;06 I'll get to what those are in a second, but let's kind of define research. The stages are basic, translational and clinical. What exactly are those stages and how do you maneuver through those to get to actual innovation? I look at those where I see basic research as working with either molecules, cells or even animal models to understand the biological process. &nbsp; 00;11;25;09 - 00;11;57;14 And then the first level of translational research is taking a subset of those basic findings and exploring whether they may have a role to play in clinical practice. So sometimes that can also be where things start to be defined in an animal model. And then you start when something looks promising, you start working through early-stage clinical trials for safety, and then you start working with patient populations. &nbsp; 00;11;57;17 - 00;12;32;08 And then ultimately, if something's successful and does seem to benefit patients, then it gets rolled into practice and then there's an additional layer that we call outcomes research, where periodically it's important to review whether, you know, those new interventions or new tests really are making a positive difference in patient outcomes. That's kind of how I like to conceptualize the different phases of both basic and translational research. &nbsp; 00;12;32;10 - 00;13;06;17 Well, I'm assuming the challenges and opportunities are different depending on what kind of research we're talking about. So, let's start with your world of clinical research. What makes life unnecessarily harder for clinical researchers and does technology offer any help? I think no matter who I spoke with, recruitment into clinical trials is a continuing challenge. And I do think that data and technology have a helpful role to play in that. &nbsp; 00;13;06;20 - 00;13;37;07 Some of our work, as well as some work within Oracle or Oracle Health, is focused on using large de-identified data sets to evaluate the feasibility of doing research at a particular setting. Do they have enough patients who might meet the inclusion criteria? And so, I do think that data and technology have a role to play in the recruitment challenge. &nbsp; 00;13;37;10 - 00;14;05;23 That's kind of interesting that that recruiting for some of these trials is so difficult. What's the reluctance? You know, people have these conditions, it seems like they would be more than willing to try, you know, something? Why the reluctance? I think there's a number of factors. One is sometimes the designers of a study are maybe overly optimistic about the population. &nbsp; 00;14;05;26 - 00;14;36;01 Sometimes they underestimate the concerns that patients and their families may have. So that's one factor. I think as a scientific community, we need to continue working on how we communicate with the public, especially now, you know, with what I think of as the epidemic of mis- and dis-information. Those may not be preventing people from joining studies, but certainly they impact the willingness to utilize the benefits of research. &nbsp; 00;14;36;04 - 00;15;19;10 Yeah. Do you worry about the level of trust declining in health care researchers? I mean, the pandemic probably we took a hit with that. It's you know, that's a really interesting topic because on the one hand, I often reflect on the pandemic and if it had been ten years ago how different and much worse it would have been, because it really would have been unheard of to have in lab diagnostic tests within weeks, at home, testing within months, and a functional and safe vaccine within a year. &nbsp; 00;15;19;12 - 00;16;16;09 Ten years ago, that would not have been possible. And that's exclusively because of our capacity and in doing clinical research. I think, though, there's a lot of challenging dynamics in play that as a scientific community, we just need to keep getting out into the public, explaining in accessible terms what research is about and why it matters. One thing that we're very intentional about here at Children's Mercy is we have both parent and youth advisory boards, and so we work with them closely as we develop new research initiatives so that they're at the table and they're also out in the community, in the community, sharing the work that's happening here, because that's in so many ways &nbsp; 00;16;16;09 - 00;16;44;18 far more effective to hear from your neighbors, your friends at work than it is to hear from, you know, those of us who are doing the technical work. Well, kind of same question for those at the basic or fundamental research level, what are their biggest headaches? And, you know, is technology being applied to those headaches? Yeah, I think I wouldn't necessarily call them so much headaches. &nbsp; 00;16;44;18 - 00;17;21;07 But, you know, all categories of research, of course, feel that funding is always a challenge. I think for basic research, the volume of data that many techniques, not all, but many generate, creates an exciting opportunity for people who work in data science. For example, genomic sequencing, you know, is highly automated now, but the volume of data that any one genomic evaluation can generate is massive as well as, you know, very complex. &nbsp; 00;17;21;07 - 00;17;48;14 And so, the informatics and data science opportunities to analyze these growing volume of data is really exciting. Yeah, it feels like even though there are different research stages, there's obviously overlap when it comes to some of the roadblocks and opportunities to knock those roadblocks down. I mean, what do you see as kind of the shared pain points? You mentioned funding, I guess that goes across all stages. &nbsp; 00;17;48;17 - 00;18;27;09 Yeah, I think especially in a clinical setting there, there's a very high focus on cybersecurity. So, the research community is not always as involved in that as they probably needed to be. So, you know, we even have a lot of considerations that we incorporate into making sure that our systems, our data are secure to the highest standards. So that also my team tries to insulate the researchers from that type of work because we want them to be focused on doing science. &nbsp; 00;18;27;09 - 00;18;53;28 And in many organizations, we see researchers who have to get their hands in some of these other processes and technology issues. So a key part of what I see as my role and my team's role is insulating the researchers from those types of concerns. Yeah, which I'm sure they greatly appreciate. Obviously, there is a lot of compute resources that are required. &nbsp; 00;18;54;00 - 00;19;28;24 So, I imagine one of your challenges is to make sure these folks have the kind of compute resources they need. Yeah, and that's really an exciting area. We have recently completed the migration for our Genome Center of their bioinformatics pipeline from an on-premise data center to a completely cloud-based system. And we're excited that we're starting to see that gain of efficiencies from that, you know, moving that to a complete cloud model. &nbsp; 00;19;28;24 - 00;20;01;12 We have other projects that are more of a hybrid model. We do have a data center and our new research institute building. So, I'm excited about the new world where we can really offer computational and storage resources at a totally different scale than was needed ten years ago or even five years ago. Well, I know you're part of the Oracle Research Industry Strategy Council, a group that talked about a lot of the same stuff, pretty recently. &nbsp; 00;20;01;12 - 00;20;24;14 Just this May actually. So, one of the topics of discussion was how some researchers who are federally funded are kind of I don't know if struggling is the right word, but dealing with new policies around data storage and data sharing. The NIH has gotten real serious about those policies earlier this year. Why are these policies like FAIR principles coming down now? &nbsp; 00;20;24;17 - 00;20;56;13 And how ready are researchers to cope with those new protocols? Plus, whatever else may pop up in terms of regulation? Yeah, I think the change in policy reflects a realization on the funders that, you know, despite the expectation that researchers would share all of most of their data that was generated with those taxpayer funds, that that wasn't happening at the consistency level that they expected. &nbsp; 00;20;56;14 - 00;21;33;02 So, the major change this year is that that expectation is articulated much more forcefully. And so now anybody doing federally funded research is expected to make any data that does not include protected health information available to the community. I think some researchers are already doing that. So again, in the genomics world, that's already a fairly common practice. But in other areas it will require some change and different ways of thinking. &nbsp; 00;21;33;04 - 00;22;06;12 I'm not seeing a high level of anxiety or concern about it. I think it's something that we can work through. It's a matter of right sizing the solution. So, we don't want to oversize how we accommodate the new regulations, but we want to make sure that all of our researchers are equipped to be compliant. The reluctance that there is to data sharing is that just concerns about proprietary stuff or researchers are thinking about going to market with this. &nbsp; 00;22;06;12 - 00;22;31;02 And, you know, they want to keep it close to the vest. Sometimes that's the case. I think sometimes it's also academic competitive concerns. So, if you're competing for grant funding with the same people who could download your data, are you giving you know, there's concern that you're giving them, if not a head start, at least the capacity to catch up faster than they otherwise would have. &nbsp; 00;22;31;04 - 00;23;05;04 Does technology help in any way to adhere to these new policies and facilitate that kind of data sharing? I definitely believe it can. There's a variety of portals that can enable researchers to share their data. I think many of these have features that researchers like so that you can track how often your data assets are downloaded. In some cases, you can get a sense for, you know, where are the downloads originating. &nbsp; 00;23;05;07 - 00;23;39;10 What I think will be interesting over the next few years. Right now, in academia, tenure decisions are made based on publications and how often your papers are cited and so forth. I think if we can see a movement towards rewarding, how often is your data downloaded and accessed and utilized and rewarding, you know, academics that do that. I think that will be a real important factor in changing the culture around that. &nbsp; 00;23;39;12 - 00;24;04;28 So, in a couple of past episodes, I actually did ask our guests about this concept of open science that's grounded in FAIR principles. From what I've learned, open science doesn't mean, you know, anything goes, everybody dive in. It's all chaos. There is still scientific rigor. What does open science mean to you? What's open about it and what's still closed about it? &nbsp; 00;24;05;00 - 00;24;48;24 I think data sharing is a key part of open science, you know, and this is where having one foot in technology and one foot in science is helpful because if you look at the open-source software movement, there was very similar cultural resistance to that. But then as people realized that if you put your software code out for the public and they find and fix bugs in that code, that similar process can start to occur with scientific data where maybe there is an inconsistency or maybe there's a pattern in the data that you didn't recognize as, but somebody else does. &nbsp; 00;24;48;27 - 00;25;16;08 So, I think there's a lot to be learned from the process that the open-source software world witnessed and experienced. I think certainly in both cases, putting your either your code or your data out there as a vulnerable feeling for a lot of people. So, helping create a comfort level to get past that vulnerability is really important for the success of both. &nbsp; 00;25;16;08 - 00;25;44;21 But I think when you look at the long-term benefits of open science, I personally believe that the quality of work will go up. And when you pull it back to pediatrics, I think some of the very interesting work in pediatrics revolves around rare disease. And so no single organization is likely to have the numbers of patients with these rare diseases that they can independently gain the insights they need to. &nbsp; 00;25;44;21 - 00;26;13;12 So, collaborating and sharing data is essential for so many areas of pediatric research in particular. Well, for all the acronym fans out there, we talk about FAIR principles. That stands for findability, accessibility, interoperability and reusability. So yeah, I guess on a scale of 1 to 10, how close do you think we are to being FAIR? It'll vary from place to place, but I would just pull a number out of the air. &nbsp; 00;26;13;12 - 00;26;36;29 On average, I would give us a six or seven. Okay, already. Good. But probably going to get better is how I kind of interpret that answer. Yeah. So, one of the guests I pestered with the open science questions was Amy Dockser Marcus of the Wall Street Journal. She wrote a book called, “We The Scientists: How a Daring Team of Parents and Doctors Forged a New Path for Medicine.” &nbsp; 00;26;37;01 - 00;27;10;13 And basically, it's about patient-scientist-doctor collaborations and how that approach could get us to solutions faster. Do you see these collaborations happening? Are doctors and scientists more open to listening to and including patients and their caregivers? Yeah, I'm really seeing, you know, exciting changes in that. I mentioned earlier that we have patient and parent community advisory groups that are increasingly engaged and active in our research strategy. &nbsp; 00;27;10;16 - 00;27;44;14 And it's really shifting from just sometimes those initiatives start with us just telling those groups about what we're doing. But now it's really shifting to how can we do it better and how can we work through these barriers to recruitment, How can we make sure that we're reaching underserved populations? So, I find this whole engagement model to be a really exciting development, and it's really gaining much needed momentum. &nbsp; 00;27;44;16 - 00;28;12;13 And I find it inspiring and motivating to hear, you know, parents of children who have gone through a very difficult health conditions share their stories because that motivates me as well and motivates my colleagues. So, it really is an exciting development that's really picked up momentum. Well, thinking about the technology part, researchers kind of have to figure out what the appropriate tools are and deal with. &nbsp; 00;28;12;14 - 00;28;30;28 Okay, is this data I need and legacy on premises systems or can I get to it in the cloud? And you touched on this a little bit earlier about how you have a cloud solution, but you still also have some hybrid situations. Are you a hybrid guy or do you think all things in the cloud is the way to go? &nbsp; 00;28;30;28 - 00;29;02;13 Which way do you lean? My approach to everything is what are your requirements? And then I will help you fulfill your requirements. And so increasingly we can fulfill many of those requirements with an exclusively cloud-based model. Where it's interesting is that not only are there functional requirements, but there's cost requirements. And so, the hybrid model can often still be delivered with lower cost than a cloud exclusive model. &nbsp; 00;29;02;15 - 00;29;34;06 So, we're trying to be sensitive to the budgetary constraints of especially some of our early career investigators and offer a hybrid model to them as a way to get started without incurring the sometimes high costs of working in any of the major cloud providers. So, everybody in nearly every field that there is thinking about and talking about AI now and how it could change things dramatically. &nbsp; 00;29;34;08 - 00;29;59;06 What are you thinking about AI and machine learning when it comes to scientific research? Is it all positive and will it speed discovery and solutions getting to market? Or are you also waving the caution flag and trying to manage expectations? Because I think about how the combination of open science and it could get really interesting. &nbsp; 00;29;59;09 - 00;30;33;14 Yeah, I currently take a nuanced and cautious stance on AI and machine learning. If you're using those resources for data analysis, I see a lot of value to them. There's so many as we deal with these rapidly growing large datasets, the capacity of our minds to do the pattern recognition is limited. And so, AI and ML are great at pattern recognition in data. &nbsp; 00;30;33;14 - 00;31;24;04 And so, I think as a tool to support data analysis, I'm very positive. I worry more about the application and clinical practice of AI. I mean, being a member of the Ethical AI Initiative of the Center for Practical Bioethics in Kansas City, and I'm very impressed with the approach that they take and they deliver a workshop that is focused on if you're either buying a system that reports to be AI enabled or building something, what are the variety of ethical considerations that you should be considering? &nbsp; 00;31;24;06 - 00;31;55;11 And a particular area of concern is around health equity. And because we know that so many of these systems are trained on data sets that are skewed towards non-diverse populations. So, if that's what you're training these models with, and they will reinforce the inequities in health care. So, I think for some of those larger scale applications, we need to have a deliberate, careful and intentional approach. &nbsp; 00;31;55;13 - 00;32;22;24 It's not to say that there won't be positive uses of AI and ML, but I do think as we get closer to patient facing application, we need to be more intentional and more deliberate. Well, I want to be in a really good mood for the rest of the day, so could you tell us about research that's going on right now at Children's Mercy and some things that you're particularly excited about? &nbsp; 00;32;22;27 - 00;32;59;02 Yeah, and again, as I mentioned earlier, I really enjoy and thrive on the variety of work here. So I'm fortunate to collaborate, for example, with Dr. Bridgette Jones, who does research on health disparity and asthma. I'm fortunate to work with our Genome Center for Genomic Medicine, where they have a very large community facing project called Genomic Answers for Kids and focused on identifying the genetic basis for rare diseases. &nbsp; 00;32;59;05 - 00;33;28;23 I'm fortunate to collaborate with a wide group of experts on some of my own research where we use large de-identified clinical data from Oracle Health. So, two recent things we evaluated were how often and this is at a national level, are youth and young adults who present in the emergency room with a migraine, how often are they treated with an opioid? &nbsp; 00;33;28;25 - 00;33;59;29 The ideal would be 0 to 2%. We noticed that more than 20% of those youth and young adults nationally are treated with an opioid. So that type of research can then lend to process changes that challenge providers to reflect on their ordering patterns. So, the variety of really exciting research that we do at Children's Mercy is just something that excites me a lot. &nbsp; 00;34;00;03 - 00;34;32;15 Yeah, and on the genomics side, how close are we to, you know, all the exciting articles we read about the entire genome being mapped to the extent that we can go on and find the marker that is causing this rare disease and switch it off. Well, the very last part is where things get hard. But we've made huge strides in the recognition of the genetic basis for different rare health conditions. &nbsp; 00;34;32;18 - 00;35;09;01 Sometimes just finding that can lead to the realization that it's similar to a condition that presents differently but has a treatment available. And then you can try that medication on the patient with that genetic variant. And so those are the initial successes. I think the gene therapy type interventions that you might be alluding to, they're starting to regain some momentum, but that's going to be a long process. &nbsp; 00;35;09;04 - 00;35;42;17 So do you think people like me who just ask the question that I asked have over or heightened expectations? It's like, what is that balance between where the public thinks we should be and where actual research really is? Yeah, I think and that gets back to the even some of the societal topics that we were touching on earlier, where on the one hand there's elements of society that want research to move faster and to do more. &nbsp; 00;35;42;19 - 00;36;19;15 And then there's other elements that are much more of the go slow. And so, again, as a scientific community, finding that right balance and how we communicate about our work is really critical. And it's something that we really need to put an increased focus on to, you know, on the one hand, make sure that the advances that are complete and ready are utilized, which, you know, we all want that and that the emerging advances that people are participating in studies that they know that it is safe to participate in studies. &nbsp; 00;36;19;17 - 00;36;46;16 And then when the results of those studies are completed, that they're comfortable utilizing the output of that research. Well, for the last question, we'll stick with that societal aspect. You are an Oracle Council member, so you already know this, but Oracle believes that for the good of global health and humanity, we must understand and serve the needs of research and researchers at every level. &nbsp; 00;36;46;18 - 00;37;13;10 And it feels like we're facing bigger things like food security, disease prevention. Nobody needs another pandemic. What's your view on how research is only going to get more vital? And the pressure on research is only going to go up for kind of holding the earth and the species together? Yeah, that's a great question. And I am an optimist about research. &nbsp; 00;37;13;10 - 00;37;47;13 I believe that the work we do in research matters to the public and to the world. The examples you gave of food security, climate change, pandemics are all the, you know, major emerging concerns that all types of research are going to play a role in the solutions to those problems. And then I would pull us back to the question of how different would things have been if the pandemic had been ten years ago. &nbsp; 00;37;47;13 - 00;38;23;03 And to me, the research into many vaccines and rapid molecular diagnostics, those are all things that made the response to the pandemic. What it was, again, far from perfect, but much more effective than it would have been ten years ago were it not for all of the research that supported those developments. And I think that same mindset would apply to the other large scale problems and challenges that you mentioned. &nbsp; 00;38;23;05 - 00;38;44;00 Dr. Hoffman, thank you again for joining us today. You know, a lot of times our listeners will want to learn more about what you talked about or even get in touch with you. Is there any way they can do that? Sure. I'm on Twitter at Mark Hoffman K.C. I'm also on LinkedIn and my bio is available on the Children's Mercy website. &nbsp; 00;38;44;03 - 00;40;56;11 Great. We appreciate that. If you are interested in how Oracle can simplify and accelerate your research, you can check out Oracle dot com slash research. And join us next time on Research in Action. &nbsp; &nbsp; "> <meta itemprop="name" content="Research in Action: Transforming healthcare research with technology's latest capabilities"> <meta itemprop="description" content="How do you connect the needs of researchers to the capabilities of technology? What are the main stages of research and the challenges faced at each stage? And will AI and machine learning speed up research and get solutions to market faster? We will learn those answers and more in this episode with Dr. Mark Hoffman, the Chief Research Information officer for Children’s Mercy and the Children’s Mercy Research Institute, a position he has held since 2016. Dr. Hoffman earned his doctorate in Bacteriology from the University of Wisconsin-Madison. He later joined Cerner as a software engineer where he advanced to the role of Vice President for Genomics and Research. Dr. Hoffman was also part of the faculty at the University of Missouri Kansas City (UMKC) in the Departments of Biomedical and Health Informatics and Pediatrics. His formal training in research and experience in software development has prepared him to connect the needs of researchers to the capabilities of technology. His work is focused on identifying the best capabilities possible to meet rapidly changing requirements in genomics, public health, and big data. Dr. Hoffman is an inventor of 22 issued patents, a member of the American Academy of Inventors, a TED talk alumnus, and an award-winning healthcare product developer. You can learn more about Dr. Hoffman and Children’s Mercy here: Learn more about Oracle for Researcher here: ---------------------------------------------------------- Episode Transcript 00;00;00;00 - 00;00;26;02 What are the three main stages of research and the challenges each are facing? How are researchers handling the new federal policies around data sharing? And will AI and machine learning speed research and get solutions to market faster? We'll get those answers and more on this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research. &nbsp; 00;00;26;02 - 00;00;49;21 I'm Mike Stiles. And today our guest is Dr. Mark Hoffman, who is the Chief Research Information Officer for Children's Mercy and the Children's Mercy Research Institute. That's a position he's held since 2016. Dr. Hoffman earned his doctorate in bacteriology from the University of Wisconsin-Madison and later joined Cerner as a software engineer, where he went on to be Vice President for genomics and research. &nbsp; 00;00;49;24 - 00;01;17;11 Dr. Hoffman was also part of the faculty at the University of Missouri, Kansas City, and the Departments of Biomedical and Health Informatics and Pediatrics. Now, because he's had formal training and research and real-world experience in software development, he's kind of uniquely qualified to talk about what researchers need when it comes to technology. His work focuses on identifying the best capabilities to meet requirements in genomics, public health and big data that are always changing. &nbsp; 00;01;17;14 - 00;01;38;22 He's an inventor of 95 issued patents, a member of the American Academy of Inventors, a TED Talk alumnus, and an award-winning health care product developer. And honest to gosh, that's about the shortest intro I could come up with for someone who is so accomplished. So, we're glad you are with us today, Dr. Hoffman. Well, thanks, Mike. I look forward to talking with you. &nbsp; 00;01;38;24 - 00;02;05;06 Our audience is going to be particularly lucky that they decided to stream this episode because there's a lot to cover. But first of all, what got you into research to begin with? Kind of what led you to each step along the way to where you are now at Children's Mercy? Well, it's a long story, but, you know, I think as a kid, I was always curious and I enjoyed Legos and, you know, taking things apart. &nbsp; 00;02;05;06 - 00;02;36;00 And so, in hindsight, I see all the foundations. And that took me a while to realize that my interests are really split between doing science and building technologies. And so, I see myself as very fortunate to have a role that lets me keep one foot in each of those areas of interest. So, you went when you made the decision to go to Cerner and go into that software development world. &nbsp; 00;02;36;02 - 00;03;05;24 What inspired you to do that? It's interesting. When I was in graduate school studying bacteriology, I was funded by an NIH program that if you're in the life sciences, you were required to take coursework outside the life sciences. I chose to do that in computer science. And then the other requirement was you were required to do an industry internship one summer. &nbsp; 00;03;05;26 - 00;03;31;27 Most of my peers chose to do that in pharma. I chose instead to do my internship at a software development company that does bioinformatics software development. Realized how much I liked that type of work and building things that get used in the real world. It's funny, but to this day, some of the features that I developed are still part of their application suite. &nbsp; 00;03;31;27 - 00;04;04;27 So, I learned from that that I enjoy the software and technology and development process. When there was the opportunity to join Cerner as a software engineer. I jumped at it and happened to be in their microbiology product line, so I was able to talk with the clients about what they were struggling with in the lab, understand that, and then translate that into whatever changes were needed in the software. &nbsp; 00;04;05;00 - 00;04;26;28 Did you expect that to be the case that you would be able to keep a foot in both sides on both the technology and the research side? Or was that something like you never thought that could happen? I didn't plan it this way, but I feel very fortunate that I'm able to exercise so many of my different interests. &nbsp; 00;04;27;00 - 00;05;12;19 So obviously children's mercy benefits from your professional expertise, but behind that you've got a real personal commitment and passion for the work that you're doing that kind of increases your value even more. If you're willing, tell us about that personal connection. And just in general, both Cerner and Children's Mercy are based in Kansas City. And as a parent, while I was working at Cerner, over time, both of our children have needed inpatient care at Children's Mercy Hospital and just the compassion and caring and quality of care and the creativity that we often saw with some of our children's physicians. &nbsp; 00;05;12;22 - 00;05;55;21 The willingness to keep trying things until they could help our kids work through their different health concerns has made a huge impression on me. Now, when I walk through the hospital and see parents with their kids who are going through really some of the most difficult situations you can imagine, I try to take a moment and share a smile or, you know, hold the elevator for a parent. I'm just trying to even though I'm not involved in patient care, I just really am empathetic to those families and see that as really kind of my connection to purpose. &nbsp; 00;05;55;24 - 00;06;35;13 What are the unique differences between a children's centered health care provider like that and, say, a regular adult hospital? What are the biggest differences that the staff has to operate with? I think probably the key difference is with adult medicine, you're really working primarily with the patient and they're making their own decisions. In pediatrics, you're working with children and they're their care providers so that there's more voices involved, you know, with younger children. &nbsp; 00;06;35;14 - 00;07;08;04 It's really is the care providers who are making those decisions with teenagers and adolescents, they certainly will have their own voice into the decision making. So that's really a key difference in pediatrics. I think pediatric medicine is interesting because it's both very cautious but also very willing to innovate. And I find that often to be a really interesting dynamic. &nbsp; 00;07;08;06 - 00;07;33;07 So you were a fan, as it were, of Children's Mercy before you started working there? Absolutely. That was a big part of my decision-making process to come here. So how did that come about that you started working for Children's Mercy? And what exactly do you do there? So, I made the difficult decision to move forward in my career in 2013. &nbsp; 00;07;33;09 - 00;07;58;04 The step that I took was to join the University of Missouri, Kansas City School of Medicine, join the faculty there and form what we called the Center of Health Insights. Through those negotiations, Children's Mercy funded 25% of my role at the university. And so, I already had not quite one foot, but at least a few toes in the door. &nbsp; 00;07;58;06 - 00;08;26;19 And I spent a lot of time building relationships with Children's Mercy. About three years into that, there was some hiring of senior leadership for the Research Institute, and I was involved in that and made the case that I'm seeing other organizations create the Chief Research Information Officer role. That idea stuck and I was hired as our first chief Research Information Officer. &nbsp; 00;08;26;21 - 00;08;50;09 So it sounds like what you want, what you're kind of your North star is to make sure researchers at Children's Mercy can tap into the best technical resources and experts out there, because especially medical researchers, everyone expects them to find answers quickly. You know, there are waiting to be helped. So. What's a typical day like for a chief research information officer? &nbsp; 00;08;50;12 - 00;09;27;09 I tell everybody there really is no typical day. Sometimes I'm down in the weeds talking through technical issues and then in the next meeting can be talking with organizational ownership about high level strategy. Part of what I enjoy is the variety in my role. I don't support any single clinical area of research. So, one meeting just yesterday was with our neurology department, where we're doing research into telemedicine and that can support rural communities where children have epilepsy. &nbsp; 00;09;27;11 - 00;09;55;25 And so there was that meeting and then there was another meeting within the same 24 hours about long read genomic sequencing with our genome center. So just context shifting and you know, always with the theme though, of trying to find ways for technology to be an enabler. All too often my peers in research feel that technology sometimes creates a barrier. &nbsp; 00;09;55;25 - 00;10;25;08 And so, one of my goals is just to try to reduce the barriers and increase the opportunities. And for you, it seems like, you know, you actually see the faces of the people that this research is trying to help. Does that add yet another motivational personal element behind kind of your mission there? Absolutely. I think through the pandemic, the entire work model for people in technology in particular has changed. &nbsp; 00;10;25;10 - 00;10;55;26 I know many of us spent a long time working from home and when I was able to start coming back on site, I just find it very motivating to go to the hospital cafeteria or, you know, get out of my research and technology bubble and be among the patients and families. Well, you've met researchers of every kind all over the world, people just like those who listen to this podcast and you know how they define success and also know what challenges they face. &nbsp; 00;10;55;28 - 00;11;25;06 I'll get to what those are in a second, but let's kind of define research. The stages are basic, translational and clinical. What exactly are those stages and how do you maneuver through those to get to actual innovation? I look at those where I see basic research as working with either molecules, cells or even animal models to understand the biological process. &nbsp; 00;11;25;09 - 00;11;57;14 And then the first level of translational research is taking a subset of those basic findings and exploring whether they may have a role to play in clinical practice. So sometimes that can also be where things start to be defined in an animal model. And then you start when something looks promising, you start working through early-stage clinical trials for safety, and then you start working with patient populations. &nbsp; 00;11;57;17 - 00;12;32;08 And then ultimately, if something's successful and does seem to benefit patients, then it gets rolled into practice and then there's an additional layer that we call outcomes research, where periodically it's important to review whether, you know, those new interventions or new tests really are making a positive difference in patient outcomes. That's kind of how I like to conceptualize the different phases of both basic and translational research. &nbsp; 00;12;32;10 - 00;13;06;17 Well, I'm assuming the challenges and opportunities are different depending on what kind of research we're talking about. So, let's start with your world of clinical research. What makes life unnecessarily harder for clinical researchers and does technology offer any help? I think no matter who I spoke with, recruitment into clinical trials is a continuing challenge. And I do think that data and technology have a helpful role to play in that. &nbsp; 00;13;06;20 - 00;13;37;07 Some of our work, as well as some work within Oracle or Oracle Health, is focused on using large de-identified data sets to evaluate the feasibility of doing research at a particular setting. Do they have enough patients who might meet the inclusion criteria? And so, I do think that data and technology have a role to play in the recruitment challenge. &nbsp; 00;13;37;10 - 00;14;05;23 That's kind of interesting that that recruiting for some of these trials is so difficult. What's the reluctance? You know, people have these conditions, it seems like they would be more than willing to try, you know, something? Why the reluctance? I think there's a number of factors. One is sometimes the designers of a study are maybe overly optimistic about the population. &nbsp; 00;14;05;26 - 00;14;36;01 Sometimes they underestimate the concerns that patients and their families may have. So that's one factor. I think as a scientific community, we need to continue working on how we communicate with the public, especially now, you know, with what I think of as the epidemic of mis- and dis-information. Those may not be preventing people from joining studies, but certainly they impact the willingness to utilize the benefits of research. &nbsp; 00;14;36;04 - 00;15;19;10 Yeah. Do you worry about the level of trust declining in health care researchers? I mean, the pandemic probably we took a hit with that. It's you know, that's a really interesting topic because on the one hand, I often reflect on the pandemic and if it had been ten years ago how different and much worse it would have been, because it really would have been unheard of to have in lab diagnostic tests within weeks, at home, testing within months, and a functional and safe vaccine within a year. &nbsp; 00;15;19;12 - 00;16;16;09 Ten years ago, that would not have been possible. And that's exclusively because of our capacity and in doing clinical research. I think, though, there's a lot of challenging dynamics in play that as a scientific community, we just need to keep getting out into the public, explaining in accessible terms what research is about and why it matters. One thing that we're very intentional about here at Children's Mercy is we have both parent and youth advisory boards, and so we work with them closely as we develop new research initiatives so that they're at the table and they're also out in the community, in the community, sharing the work that's happening here, because that's in so many ways &nbsp; 00;16;16;09 - 00;16;44;18 far more effective to hear from your neighbors, your friends at work than it is to hear from, you know, those of us who are doing the technical work. Well, kind of same question for those at the basic or fundamental research level, what are their biggest headaches? And, you know, is technology being applied to those headaches? Yeah, I think I wouldn't necessarily call them so much headaches. &nbsp; 00;16;44;18 - 00;17;21;07 But, you know, all categories of research, of course, feel that funding is always a challenge. I think for basic research, the volume of data that many techniques, not all, but many generate, creates an exciting opportunity for people who work in data science. For example, genomic sequencing, you know, is highly automated now, but the volume of data that any one genomic evaluation can generate is massive as well as, you know, very complex. &nbsp; 00;17;21;07 - 00;17;48;14 And so, the informatics and data science opportunities to analyze these growing volume of data is really exciting. Yeah, it feels like even though there are different research stages, there's obviously overlap when it comes to some of the roadblocks and opportunities to knock those roadblocks down. I mean, what do you see as kind of the shared pain points? You mentioned funding, I guess that goes across all stages. &nbsp; 00;17;48;17 - 00;18;27;09 Yeah, I think especially in a clinical setting there, there's a very high focus on cybersecurity. So, the research community is not always as involved in that as they probably needed to be. So, you know, we even have a lot of considerations that we incorporate into making sure that our systems, our data are secure to the highest standards. So that also my team tries to insulate the researchers from that type of work because we want them to be focused on doing science. &nbsp; 00;18;27;09 - 00;18;53;28 And in many organizations, we see researchers who have to get their hands in some of these other processes and technology issues. So a key part of what I see as my role and my team's role is insulating the researchers from those types of concerns. Yeah, which I'm sure they greatly appreciate. Obviously, there is a lot of compute resources that are required. &nbsp; 00;18;54;00 - 00;19;28;24 So, I imagine one of your challenges is to make sure these folks have the kind of compute resources they need. Yeah, and that's really an exciting area. We have recently completed the migration for our Genome Center of their bioinformatics pipeline from an on-premise data center to a completely cloud-based system. And we're excited that we're starting to see that gain of efficiencies from that, you know, moving that to a complete cloud model. &nbsp; 00;19;28;24 - 00;20;01;12 We have other projects that are more of a hybrid model. We do have a data center and our new research institute building. So, I'm excited about the new world where we can really offer computational and storage resources at a totally different scale than was needed ten years ago or even five years ago. Well, I know you're part of the Oracle Research Industry Strategy Council, a group that talked about a lot of the same stuff, pretty recently. &nbsp; 00;20;01;12 - 00;20;24;14 Just this May actually. So, one of the topics of discussion was how some researchers who are federally funded are kind of I don't know if struggling is the right word, but dealing with new policies around data storage and data sharing. The NIH has gotten real serious about those policies earlier this year. Why are these policies like FAIR principles coming down now? &nbsp; 00;20;24;17 - 00;20;56;13 And how ready are researchers to cope with those new protocols? Plus, whatever else may pop up in terms of regulation? Yeah, I think the change in policy reflects a realization on the funders that, you know, despite the expectation that researchers would share all of most of their data that was generated with those taxpayer funds, that that wasn't happening at the consistency level that they expected. &nbsp; 00;20;56;14 - 00;21;33;02 So, the major change this year is that that expectation is articulated much more forcefully. And so now anybody doing federally funded research is expected to make any data that does not include protected health information available to the community. I think some researchers are already doing that. So again, in the genomics world, that's already a fairly common practice. But in other areas it will require some change and different ways of thinking. &nbsp; 00;21;33;04 - 00;22;06;12 I'm not seeing a high level of anxiety or concern about it. I think it's something that we can work through. It's a matter of right sizing the solution. So, we don't want to oversize how we accommodate the new regulations, but we want to make sure that all of our researchers are equipped to be compliant. The reluctance that there is to data sharing is that just concerns about proprietary stuff or researchers are thinking about going to market with this. &nbsp; 00;22;06;12 - 00;22;31;02 And, you know, they want to keep it close to the vest. Sometimes that's the case. I think sometimes it's also academic competitive concerns. So, if you're competing for grant funding with the same people who could download your data, are you giving you know, there's concern that you're giving them, if not a head start, at least the capacity to catch up faster than they otherwise would have. &nbsp; 00;22;31;04 - 00;23;05;04 Does technology help in any way to adhere to these new policies and facilitate that kind of data sharing? I definitely believe it can. There's a variety of portals that can enable researchers to share their data. I think many of these have features that researchers like so that you can track how often your data assets are downloaded. In some cases, you can get a sense for, you know, where are the downloads originating. &nbsp; 00;23;05;07 - 00;23;39;10 What I think will be interesting over the next few years. Right now, in academia, tenure decisions are made based on publications and how often your papers are cited and so forth. I think if we can see a movement towards rewarding, how often is your data downloaded and accessed and utilized and rewarding, you know, academics that do that. I think that will be a real important factor in changing the culture around that. &nbsp; 00;23;39;12 - 00;24;04;28 So, in a couple of past episodes, I actually did ask our guests about this concept of open science that's grounded in FAIR principles. From what I've learned, open science doesn't mean, you know, anything goes, everybody dive in. It's all chaos. There is still scientific rigor. What does open science mean to you? What's open about it and what's still closed about it? &nbsp; 00;24;05;00 - 00;24;48;24 I think data sharing is a key part of open science, you know, and this is where having one foot in technology and one foot in science is helpful because if you look at the open-source software movement, there was very similar cultural resistance to that. But then as people realized that if you put your software code out for the public and they find and fix bugs in that code, that similar process can start to occur with scientific data where maybe there is an inconsistency or maybe there's a pattern in the data that you didn't recognize as, but somebody else does. &nbsp; 00;24;48;27 - 00;25;16;08 So, I think there's a lot to be learned from the process that the open-source software world witnessed and experienced. I think certainly in both cases, putting your either your code or your data out there as a vulnerable feeling for a lot of people. So, helping create a comfort level to get past that vulnerability is really important for the success of both. &nbsp; 00;25;16;08 - 00;25;44;21 But I think when you look at the long-term benefits of open science, I personally believe that the quality of work will go up. And when you pull it back to pediatrics, I think some of the very interesting work in pediatrics revolves around rare disease. And so no single organization is likely to have the numbers of patients with these rare diseases that they can independently gain the insights they need to. &nbsp; 00;25;44;21 - 00;26;13;12 So, collaborating and sharing data is essential for so many areas of pediatric research in particular. Well, for all the acronym fans out there, we talk about FAIR principles. That stands for findability, accessibility, interoperability and reusability. So yeah, I guess on a scale of 1 to 10, how close do you think we are to being FAIR? It'll vary from place to place, but I would just pull a number out of the air. &nbsp; 00;26;13;12 - 00;26;36;29 On average, I would give us a six or seven. Okay, already. Good. But probably going to get better is how I kind of interpret that answer. Yeah. So, one of the guests I pestered with the open science questions was Amy Dockser Marcus of the Wall Street Journal. She wrote a book called, “We The Scientists: How a Daring Team of Parents and Doctors Forged a New Path for Medicine.” &nbsp; 00;26;37;01 - 00;27;10;13 And basically, it's about patient-scientist-doctor collaborations and how that approach could get us to solutions faster. Do you see these collaborations happening? Are doctors and scientists more open to listening to and including patients and their caregivers? Yeah, I'm really seeing, you know, exciting changes in that. I mentioned earlier that we have patient and parent community advisory groups that are increasingly engaged and active in our research strategy. &nbsp; 00;27;10;16 - 00;27;44;14 And it's really shifting from just sometimes those initiatives start with us just telling those groups about what we're doing. But now it's really shifting to how can we do it better and how can we work through these barriers to recruitment, How can we make sure that we're reaching underserved populations? So, I find this whole engagement model to be a really exciting development, and it's really gaining much needed momentum. &nbsp; 00;27;44;16 - 00;28;12;13 And I find it inspiring and motivating to hear, you know, parents of children who have gone through a very difficult health conditions share their stories because that motivates me as well and motivates my colleagues. So, it really is an exciting development that's really picked up momentum. Well, thinking about the technology part, researchers kind of have to figure out what the appropriate tools are and deal with. &nbsp; 00;28;12;14 - 00;28;30;28 Okay, is this data I need and legacy on premises systems or can I get to it in the cloud? And you touched on this a little bit earlier about how you have a cloud solution, but you still also have some hybrid situations. Are you a hybrid guy or do you think all things in the cloud is the way to go? &nbsp; 00;28;30;28 - 00;29;02;13 Which way do you lean? My approach to everything is what are your requirements? And then I will help you fulfill your requirements. And so increasingly we can fulfill many of those requirements with an exclusively cloud-based model. Where it's interesting is that not only are there functional requirements, but there's cost requirements. And so, the hybrid model can often still be delivered with lower cost than a cloud exclusive model. &nbsp; 00;29;02;15 - 00;29;34;06 So, we're trying to be sensitive to the budgetary constraints of especially some of our early career investigators and offer a hybrid model to them as a way to get started without incurring the sometimes high costs of working in any of the major cloud providers. So, everybody in nearly every field that there is thinking about and talking about AI now and how it could change things dramatically. &nbsp; 00;29;34;08 - 00;29;59;06 What are you thinking about AI and machine learning when it comes to scientific research? Is it all positive and will it speed discovery and solutions getting to market? Or are you also waving the caution flag and trying to manage expectations? Because I think about how the combination of open science and it could get really interesting. &nbsp; 00;29;59;09 - 00;30;33;14 Yeah, I currently take a nuanced and cautious stance on AI and machine learning. If you're using those resources for data analysis, I see a lot of value to them. There's so many as we deal with these rapidly growing large datasets, the capacity of our minds to do the pattern recognition is limited. And so, AI and ML are great at pattern recognition in data. &nbsp; 00;30;33;14 - 00;31;24;04 And so, I think as a tool to support data analysis, I'm very positive. I worry more about the application and clinical practice of AI. I mean, being a member of the Ethical AI Initiative of the Center for Practical Bioethics in Kansas City, and I'm very impressed with the approach that they take and they deliver a workshop that is focused on if you're either buying a system that reports to be AI enabled or building something, what are the variety of ethical considerations that you should be considering? &nbsp; 00;31;24;06 - 00;31;55;11 And a particular area of concern is around health equity. And because we know that so many of these systems are trained on data sets that are skewed towards non-diverse populations. So, if that's what you're training these models with, and they will reinforce the inequities in health care. So, I think for some of those larger scale applications, we need to have a deliberate, careful and intentional approach. &nbsp; 00;31;55;13 - 00;32;22;24 It's not to say that there won't be positive uses of AI and ML, but I do think as we get closer to patient facing application, we need to be more intentional and more deliberate. Well, I want to be in a really good mood for the rest of the day, so could you tell us about research that's going on right now at Children's Mercy and some things that you're particularly excited about? &nbsp; 00;32;22;27 - 00;32;59;02 Yeah, and again, as I mentioned earlier, I really enjoy and thrive on the variety of work here. So I'm fortunate to collaborate, for example, with Dr. Bridgette Jones, who does research on health disparity and asthma. I'm fortunate to work with our Genome Center for Genomic Medicine, where they have a very large community facing project called Genomic Answers for Kids and focused on identifying the genetic basis for rare diseases. &nbsp; 00;32;59;05 - 00;33;28;23 I'm fortunate to collaborate with a wide group of experts on some of my own research where we use large de-identified clinical data from Oracle Health. So, two recent things we evaluated were how often and this is at a national level, are youth and young adults who present in the emergency room with a migraine, how often are they treated with an opioid? &nbsp; 00;33;28;25 - 00;33;59;29 The ideal would be 0 to 2%. We noticed that more than 20% of those youth and young adults nationally are treated with an opioid. So that type of research can then lend to process changes that challenge providers to reflect on their ordering patterns. So, the variety of really exciting research that we do at Children's Mercy is just something that excites me a lot. &nbsp; 00;34;00;03 - 00;34;32;15 Yeah, and on the genomics side, how close are we to, you know, all the exciting articles we read about the entire genome being mapped to the extent that we can go on and find the marker that is causing this rare disease and switch it off. Well, the very last part is where things get hard. But we've made huge strides in the recognition of the genetic basis for different rare health conditions. &nbsp; 00;34;32;18 - 00;35;09;01 Sometimes just finding that can lead to the realization that it's similar to a condition that presents differently but has a treatment available. And then you can try that medication on the patient with that genetic variant. And so those are the initial successes. I think the gene therapy type interventions that you might be alluding to, they're starting to regain some momentum, but that's going to be a long process. &nbsp; 00;35;09;04 - 00;35;42;17 So do you think people like me who just ask the question that I asked have over or heightened expectations? It's like, what is that balance between where the public thinks we should be and where actual research really is? Yeah, I think and that gets back to the even some of the societal topics that we were touching on earlier, where on the one hand there's elements of society that want research to move faster and to do more. &nbsp; 00;35;42;19 - 00;36;19;15 And then there's other elements that are much more of the go slow. And so, again, as a scientific community, finding that right balance and how we communicate about our work is really critical. And it's something that we really need to put an increased focus on to, you know, on the one hand, make sure that the advances that are complete and ready are utilized, which, you know, we all want that and that the emerging advances that people are participating in studies that they know that it is safe to participate in studies. &nbsp; 00;36;19;17 - 00;36;46;16 And then when the results of those studies are completed, that they're comfortable utilizing the output of that research. Well, for the last question, we'll stick with that societal aspect. You are an Oracle Council member, so you already know this, but Oracle believes that for the good of global health and humanity, we must understand and serve the needs of research and researchers at every level. &nbsp; 00;36;46;18 - 00;37;13;10 And it feels like we're facing bigger things like food security, disease prevention. Nobody needs another pandemic. What's your view on how research is only going to get more vital? And the pressure on research is only going to go up for kind of holding the earth and the species together? Yeah, that's a great question. And I am an optimist about research. &nbsp; 00;37;13;10 - 00;37;47;13 I believe that the work we do in research matters to the public and to the world. The examples you gave of food security, climate change, pandemics are all the, you know, major emerging concerns that all types of research are going to play a role in the solutions to those problems. And then I would pull us back to the question of how different would things have been if the pandemic had been ten years ago. &nbsp; 00;37;47;13 - 00;38;23;03 And to me, the research into many vaccines and rapid molecular diagnostics, those are all things that made the response to the pandemic. What it was, again, far from perfect, but much more effective than it would have been ten years ago were it not for all of the research that supported those developments. And I think that same mindset would apply to the other large scale problems and challenges that you mentioned. &nbsp; 00;38;23;05 - 00;38;44;00 Dr. Hoffman, thank you again for joining us today. You know, a lot of times our listeners will want to learn more about what you talked about or even get in touch with you. Is there any way they can do that? Sure. I'm on Twitter at Mark Hoffman K.C. I'm also on LinkedIn and my bio is available on the Children's Mercy website. &nbsp; 00;38;44;03 - 00;40;56;11 Great. We appreciate that. If you are interested in how Oracle can simplify and accelerate your research, you can check out Oracle dot com slash research. And join us next time on Research in Action. &nbsp; &nbsp; "> <meta itemprop="image" content="https://assets.libsyn.com/secure/item/27317634"> <meta property="og:url" content="https://researchinaction.libsyn.com/transforming-healthcare-research-with-technologys-latest-capabilities"> <meta property="og:title" content="Research in Action: Transforming healthcare research with technology's latest capabilities"> <meta property="og:description" content="How do you connect the needs of researchers to the capabilities of technology? What are the main stages of research and the challenges faced at each stage? And will AI and machine learning speed up research and get solutions to market faster? We will learn those answers and more in this episode with Dr. Mark Hoffman, the Chief Research Information officer for Children’s Mercy and the Children’s Mercy Research Institute, a position he has held since 2016. Dr. Hoffman earned his doctorate in Bacteriology from the University of Wisconsin-Madison. He later joined Cerner as a software engineer where he advanced to the role of Vice President for Genomics and Research. Dr. Hoffman was also part of the faculty at the University of Missouri Kansas City (UMKC) in the Departments of Biomedical and Health Informatics and Pediatrics. His formal training in research and experience in software development has prepared him to connect the needs of researchers to the capabilities of technology. His work is focused on identifying the best capabilities possible to meet rapidly changing requirements in genomics, public health, and big data. Dr. Hoffman is an inventor of 22 issued patents, a member of the American Academy of Inventors, a TED talk alumnus, and an award-winning healthcare product developer. You can learn more about Dr. Hoffman and Children’s Mercy here: Learn more about Oracle for Researcher here: ---------------------------------------------------------- Episode Transcript 00;00;00;00 - 00;00;26;02 What are the three main stages of research and the challenges each are facing? How are researchers handling the new federal policies around data sharing? And will AI and machine learning speed research and get solutions to market faster? We'll get those answers and more on this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research. &nbsp; 00;00;26;02 - 00;00;49;21 I'm Mike Stiles. And today our guest is Dr. Mark Hoffman, who is the Chief Research Information Officer for Children's Mercy and the Children's Mercy Research Institute. That's a position he's held since 2016. Dr. Hoffman earned his doctorate in bacteriology from the University of Wisconsin-Madison and later joined Cerner as a software engineer, where he went on to be Vice President for genomics and research. &nbsp; 00;00;49;24 - 00;01;17;11 Dr. Hoffman was also part of the faculty at the University of Missouri, Kansas City, and the Departments of Biomedical and Health Informatics and Pediatrics. Now, because he's had formal training and research and real-world experience in software development, he's kind of uniquely qualified to talk about what researchers need when it comes to technology. His work focuses on identifying the best capabilities to meet requirements in genomics, public health and big data that are always changing. &nbsp; 00;01;17;14 - 00;01;38;22 He's an inventor of 95 issued patents, a member of the American Academy of Inventors, a TED Talk alumnus, and an award-winning health care product developer. And honest to gosh, that's about the shortest intro I could come up with for someone who is so accomplished. So, we're glad you are with us today, Dr. Hoffman. Well, thanks, Mike. I look forward to talking with you. &nbsp; 00;01;38;24 - 00;02;05;06 Our audience is going to be particularly lucky that they decided to stream this episode because there's a lot to cover. But first of all, what got you into research to begin with? Kind of what led you to each step along the way to where you are now at Children's Mercy? Well, it's a long story, but, you know, I think as a kid, I was always curious and I enjoyed Legos and, you know, taking things apart. &nbsp; 00;02;05;06 - 00;02;36;00 And so, in hindsight, I see all the foundations. And that took me a while to realize that my interests are really split between doing science and building technologies. And so, I see myself as very fortunate to have a role that lets me keep one foot in each of those areas of interest. So, you went when you made the decision to go to Cerner and go into that software development world. &nbsp; 00;02;36;02 - 00;03;05;24 What inspired you to do that? It's interesting. When I was in graduate school studying bacteriology, I was funded by an NIH program that if you're in the life sciences, you were required to take coursework outside the life sciences. I chose to do that in computer science. And then the other requirement was you were required to do an industry internship one summer. &nbsp; 00;03;05;26 - 00;03;31;27 Most of my peers chose to do that in pharma. I chose instead to do my internship at a software development company that does bioinformatics software development. Realized how much I liked that type of work and building things that get used in the real world. It's funny, but to this day, some of the features that I developed are still part of their application suite. &nbsp; 00;03;31;27 - 00;04;04;27 So, I learned from that that I enjoy the software and technology and development process. When there was the opportunity to join Cerner as a software engineer. I jumped at it and happened to be in their microbiology product line, so I was able to talk with the clients about what they were struggling with in the lab, understand that, and then translate that into whatever changes were needed in the software. &nbsp; 00;04;05;00 - 00;04;26;28 Did you expect that to be the case that you would be able to keep a foot in both sides on both the technology and the research side? Or was that something like you never thought that could happen? I didn't plan it this way, but I feel very fortunate that I'm able to exercise so many of my different interests. &nbsp; 00;04;27;00 - 00;05;12;19 So obviously children's mercy benefits from your professional expertise, but behind that you've got a real personal commitment and passion for the work that you're doing that kind of increases your value even more. If you're willing, tell us about that personal connection. And just in general, both Cerner and Children's Mercy are based in Kansas City. And as a parent, while I was working at Cerner, over time, both of our children have needed inpatient care at Children's Mercy Hospital and just the compassion and caring and quality of care and the creativity that we often saw with some of our children's physicians. &nbsp; 00;05;12;22 - 00;05;55;21 The willingness to keep trying things until they could help our kids work through their different health concerns has made a huge impression on me. Now, when I walk through the hospital and see parents with their kids who are going through really some of the most difficult situations you can imagine, I try to take a moment and share a smile or, you know, hold the elevator for a parent. I'm just trying to even though I'm not involved in patient care, I just really am empathetic to those families and see that as really kind of my connection to purpose. &nbsp; 00;05;55;24 - 00;06;35;13 What are the unique differences between a children's centered health care provider like that and, say, a regular adult hospital? What are the biggest differences that the staff has to operate with? I think probably the key difference is with adult medicine, you're really working primarily with the patient and they're making their own decisions. In pediatrics, you're working with children and they're their care providers so that there's more voices involved, you know, with younger children. &nbsp; 00;06;35;14 - 00;07;08;04 It's really is the care providers who are making those decisions with teenagers and adolescents, they certainly will have their own voice into the decision making. So that's really a key difference in pediatrics. I think pediatric medicine is interesting because it's both very cautious but also very willing to innovate. And I find that often to be a really interesting dynamic. &nbsp; 00;07;08;06 - 00;07;33;07 So you were a fan, as it were, of Children's Mercy before you started working there? Absolutely. That was a big part of my decision-making process to come here. So how did that come about that you started working for Children's Mercy? And what exactly do you do there? So, I made the difficult decision to move forward in my career in 2013. &nbsp; 00;07;33;09 - 00;07;58;04 The step that I took was to join the University of Missouri, Kansas City School of Medicine, join the faculty there and form what we called the Center of Health Insights. Through those negotiations, Children's Mercy funded 25% of my role at the university. And so, I already had not quite one foot, but at least a few toes in the door. &nbsp; 00;07;58;06 - 00;08;26;19 And I spent a lot of time building relationships with Children's Mercy. About three years into that, there was some hiring of senior leadership for the Research Institute, and I was involved in that and made the case that I'm seeing other organizations create the Chief Research Information Officer role. That idea stuck and I was hired as our first chief Research Information Officer. &nbsp; 00;08;26;21 - 00;08;50;09 So it sounds like what you want, what you're kind of your North star is to make sure researchers at Children's Mercy can tap into the best technical resources and experts out there, because especially medical researchers, everyone expects them to find answers quickly. You know, there are waiting to be helped. So. What's a typical day like for a chief research information officer? &nbsp; 00;08;50;12 - 00;09;27;09 I tell everybody there really is no typical day. Sometimes I'm down in the weeds talking through technical issues and then in the next meeting can be talking with organizational ownership about high level strategy. Part of what I enjoy is the variety in my role. I don't support any single clinical area of research. So, one meeting just yesterday was with our neurology department, where we're doing research into telemedicine and that can support rural communities where children have epilepsy. &nbsp; 00;09;27;11 - 00;09;55;25 And so there was that meeting and then there was another meeting within the same 24 hours about long read genomic sequencing with our genome center. So just context shifting and you know, always with the theme though, of trying to find ways for technology to be an enabler. All too often my peers in research feel that technology sometimes creates a barrier. &nbsp; 00;09;55;25 - 00;10;25;08 And so, one of my goals is just to try to reduce the barriers and increase the opportunities. And for you, it seems like, you know, you actually see the faces of the people that this research is trying to help. Does that add yet another motivational personal element behind kind of your mission there? Absolutely. I think through the pandemic, the entire work model for people in technology in particular has changed. &nbsp; 00;10;25;10 - 00;10;55;26 I know many of us spent a long time working from home and when I was able to start coming back on site, I just find it very motivating to go to the hospital cafeteria or, you know, get out of my research and technology bubble and be among the patients and families. Well, you've met researchers of every kind all over the world, people just like those who listen to this podcast and you know how they define success and also know what challenges they face. &nbsp; 00;10;55;28 - 00;11;25;06 I'll get to what those are in a second, but let's kind of define research. The stages are basic, translational and clinical. What exactly are those stages and how do you maneuver through those to get to actual innovation? I look at those where I see basic research as working with either molecules, cells or even animal models to understand the biological process. &nbsp; 00;11;25;09 - 00;11;57;14 And then the first level of translational research is taking a subset of those basic findings and exploring whether they may have a role to play in clinical practice. So sometimes that can also be where things start to be defined in an animal model. And then you start when something looks promising, you start working through early-stage clinical trials for safety, and then you start working with patient populations. &nbsp; 00;11;57;17 - 00;12;32;08 And then ultimately, if something's successful and does seem to benefit patients, then it gets rolled into practice and then there's an additional layer that we call outcomes research, where periodically it's important to review whether, you know, those new interventions or new tests really are making a positive difference in patient outcomes. That's kind of how I like to conceptualize the different phases of both basic and translational research. &nbsp; 00;12;32;10 - 00;13;06;17 Well, I'm assuming the challenges and opportunities are different depending on what kind of research we're talking about. So, let's start with your world of clinical research. What makes life unnecessarily harder for clinical researchers and does technology offer any help? I think no matter who I spoke with, recruitment into clinical trials is a continuing challenge. And I do think that data and technology have a helpful role to play in that. &nbsp; 00;13;06;20 - 00;13;37;07 Some of our work, as well as some work within Oracle or Oracle Health, is focused on using large de-identified data sets to evaluate the feasibility of doing research at a particular setting. Do they have enough patients who might meet the inclusion criteria? And so, I do think that data and technology have a role to play in the recruitment challenge. &nbsp; 00;13;37;10 - 00;14;05;23 That's kind of interesting that that recruiting for some of these trials is so difficult. What's the reluctance? You know, people have these conditions, it seems like they would be more than willing to try, you know, something? Why the reluctance? I think there's a number of factors. One is sometimes the designers of a study are maybe overly optimistic about the population. &nbsp; 00;14;05;26 - 00;14;36;01 Sometimes they underestimate the concerns that patients and their families may have. So that's one factor. I think as a scientific community, we need to continue working on how we communicate with the public, especially now, you know, with what I think of as the epidemic of mis- and dis-information. Those may not be preventing people from joining studies, but certainly they impact the willingness to utilize the benefits of research. &nbsp; 00;14;36;04 - 00;15;19;10 Yeah. Do you worry about the level of trust declining in health care researchers? I mean, the pandemic probably we took a hit with that. It's you know, that's a really interesting topic because on the one hand, I often reflect on the pandemic and if it had been ten years ago how different and much worse it would have been, because it really would have been unheard of to have in lab diagnostic tests within weeks, at home, testing within months, and a functional and safe vaccine within a year. &nbsp; 00;15;19;12 - 00;16;16;09 Ten years ago, that would not have been possible. And that's exclusively because of our capacity and in doing clinical research. I think, though, there's a lot of challenging dynamics in play that as a scientific community, we just need to keep getting out into the public, explaining in accessible terms what research is about and why it matters. One thing that we're very intentional about here at Children's Mercy is we have both parent and youth advisory boards, and so we work with them closely as we develop new research initiatives so that they're at the table and they're also out in the community, in the community, sharing the work that's happening here, because that's in so many ways &nbsp; 00;16;16;09 - 00;16;44;18 far more effective to hear from your neighbors, your friends at work than it is to hear from, you know, those of us who are doing the technical work. Well, kind of same question for those at the basic or fundamental research level, what are their biggest headaches? And, you know, is technology being applied to those headaches? Yeah, I think I wouldn't necessarily call them so much headaches. &nbsp; 00;16;44;18 - 00;17;21;07 But, you know, all categories of research, of course, feel that funding is always a challenge. I think for basic research, the volume of data that many techniques, not all, but many generate, creates an exciting opportunity for people who work in data science. For example, genomic sequencing, you know, is highly automated now, but the volume of data that any one genomic evaluation can generate is massive as well as, you know, very complex. &nbsp; 00;17;21;07 - 00;17;48;14 And so, the informatics and data science opportunities to analyze these growing volume of data is really exciting. Yeah, it feels like even though there are different research stages, there's obviously overlap when it comes to some of the roadblocks and opportunities to knock those roadblocks down. I mean, what do you see as kind of the shared pain points? You mentioned funding, I guess that goes across all stages. &nbsp; 00;17;48;17 - 00;18;27;09 Yeah, I think especially in a clinical setting there, there's a very high focus on cybersecurity. So, the research community is not always as involved in that as they probably needed to be. So, you know, we even have a lot of considerations that we incorporate into making sure that our systems, our data are secure to the highest standards. So that also my team tries to insulate the researchers from that type of work because we want them to be focused on doing science. &nbsp; 00;18;27;09 - 00;18;53;28 And in many organizations, we see researchers who have to get their hands in some of these other processes and technology issues. So a key part of what I see as my role and my team's role is insulating the researchers from those types of concerns. Yeah, which I'm sure they greatly appreciate. Obviously, there is a lot of compute resources that are required. &nbsp; 00;18;54;00 - 00;19;28;24 So, I imagine one of your challenges is to make sure these folks have the kind of compute resources they need. Yeah, and that's really an exciting area. We have recently completed the migration for our Genome Center of their bioinformatics pipeline from an on-premise data center to a completely cloud-based system. And we're excited that we're starting to see that gain of efficiencies from that, you know, moving that to a complete cloud model. &nbsp; 00;19;28;24 - 00;20;01;12 We have other projects that are more of a hybrid model. We do have a data center and our new research institute building. So, I'm excited about the new world where we can really offer computational and storage resources at a totally different scale than was needed ten years ago or even five years ago. Well, I know you're part of the Oracle Research Industry Strategy Council, a group that talked about a lot of the same stuff, pretty recently. &nbsp; 00;20;01;12 - 00;20;24;14 Just this May actually. So, one of the topics of discussion was how some researchers who are federally funded are kind of I don't know if struggling is the right word, but dealing with new policies around data storage and data sharing. The NIH has gotten real serious about those policies earlier this year. Why are these policies like FAIR principles coming down now? &nbsp; 00;20;24;17 - 00;20;56;13 And how ready are researchers to cope with those new protocols? Plus, whatever else may pop up in terms of regulation? Yeah, I think the change in policy reflects a realization on the funders that, you know, despite the expectation that researchers would share all of most of their data that was generated with those taxpayer funds, that that wasn't happening at the consistency level that they expected. &nbsp; 00;20;56;14 - 00;21;33;02 So, the major change this year is that that expectation is articulated much more forcefully. And so now anybody doing federally funded research is expected to make any data that does not include protected health information available to the community. I think some researchers are already doing that. So again, in the genomics world, that's already a fairly common practice. But in other areas it will require some change and different ways of thinking. &nbsp; 00;21;33;04 - 00;22;06;12 I'm not seeing a high level of anxiety or concern about it. I think it's something that we can work through. It's a matter of right sizing the solution. So, we don't want to oversize how we accommodate the new regulations, but we want to make sure that all of our researchers are equipped to be compliant. The reluctance that there is to data sharing is that just concerns about proprietary stuff or researchers are thinking about going to market with this. &nbsp; 00;22;06;12 - 00;22;31;02 And, you know, they want to keep it close to the vest. Sometimes that's the case. I think sometimes it's also academic competitive concerns. So, if you're competing for grant funding with the same people who could download your data, are you giving you know, there's concern that you're giving them, if not a head start, at least the capacity to catch up faster than they otherwise would have. &nbsp; 00;22;31;04 - 00;23;05;04 Does technology help in any way to adhere to these new policies and facilitate that kind of data sharing? I definitely believe it can. There's a variety of portals that can enable researchers to share their data. I think many of these have features that researchers like so that you can track how often your data assets are downloaded. In some cases, you can get a sense for, you know, where are the downloads originating. &nbsp; 00;23;05;07 - 00;23;39;10 What I think will be interesting over the next few years. Right now, in academia, tenure decisions are made based on publications and how often your papers are cited and so forth. I think if we can see a movement towards rewarding, how often is your data downloaded and accessed and utilized and rewarding, you know, academics that do that. I think that will be a real important factor in changing the culture around that. &nbsp; 00;23;39;12 - 00;24;04;28 So, in a couple of past episodes, I actually did ask our guests about this concept of open science that's grounded in FAIR principles. From what I've learned, open science doesn't mean, you know, anything goes, everybody dive in. It's all chaos. There is still scientific rigor. What does open science mean to you? What's open about it and what's still closed about it? &nbsp; 00;24;05;00 - 00;24;48;24 I think data sharing is a key part of open science, you know, and this is where having one foot in technology and one foot in science is helpful because if you look at the open-source software movement, there was very similar cultural resistance to that. But then as people realized that if you put your software code out for the public and they find and fix bugs in that code, that similar process can start to occur with scientific data where maybe there is an inconsistency or maybe there's a pattern in the data that you didn't recognize as, but somebody else does. &nbsp; 00;24;48;27 - 00;25;16;08 So, I think there's a lot to be learned from the process that the open-source software world witnessed and experienced. I think certainly in both cases, putting your either your code or your data out there as a vulnerable feeling for a lot of people. So, helping create a comfort level to get past that vulnerability is really important for the success of both. &nbsp; 00;25;16;08 - 00;25;44;21 But I think when you look at the long-term benefits of open science, I personally believe that the quality of work will go up. And when you pull it back to pediatrics, I think some of the very interesting work in pediatrics revolves around rare disease. And so no single organization is likely to have the numbers of patients with these rare diseases that they can independently gain the insights they need to. &nbsp; 00;25;44;21 - 00;26;13;12 So, collaborating and sharing data is essential for so many areas of pediatric research in particular. Well, for all the acronym fans out there, we talk about FAIR principles. That stands for findability, accessibility, interoperability and reusability. So yeah, I guess on a scale of 1 to 10, how close do you think we are to being FAIR? It'll vary from place to place, but I would just pull a number out of the air. &nbsp; 00;26;13;12 - 00;26;36;29 On average, I would give us a six or seven. Okay, already. Good. But probably going to get better is how I kind of interpret that answer. Yeah. So, one of the guests I pestered with the open science questions was Amy Dockser Marcus of the Wall Street Journal. She wrote a book called, “We The Scientists: How a Daring Team of Parents and Doctors Forged a New Path for Medicine.” &nbsp; 00;26;37;01 - 00;27;10;13 And basically, it's about patient-scientist-doctor collaborations and how that approach could get us to solutions faster. Do you see these collaborations happening? Are doctors and scientists more open to listening to and including patients and their caregivers? Yeah, I'm really seeing, you know, exciting changes in that. I mentioned earlier that we have patient and parent community advisory groups that are increasingly engaged and active in our research strategy. &nbsp; 00;27;10;16 - 00;27;44;14 And it's really shifting from just sometimes those initiatives start with us just telling those groups about what we're doing. But now it's really shifting to how can we do it better and how can we work through these barriers to recruitment, How can we make sure that we're reaching underserved populations? So, I find this whole engagement model to be a really exciting development, and it's really gaining much needed momentum. &nbsp; 00;27;44;16 - 00;28;12;13 And I find it inspiring and motivating to hear, you know, parents of children who have gone through a very difficult health conditions share their stories because that motivates me as well and motivates my colleagues. So, it really is an exciting development that's really picked up momentum. Well, thinking about the technology part, researchers kind of have to figure out what the appropriate tools are and deal with. &nbsp; 00;28;12;14 - 00;28;30;28 Okay, is this data I need and legacy on premises systems or can I get to it in the cloud? And you touched on this a little bit earlier about how you have a cloud solution, but you still also have some hybrid situations. Are you a hybrid guy or do you think all things in the cloud is the way to go? &nbsp; 00;28;30;28 - 00;29;02;13 Which way do you lean? My approach to everything is what are your requirements? And then I will help you fulfill your requirements. And so increasingly we can fulfill many of those requirements with an exclusively cloud-based model. Where it's interesting is that not only are there functional requirements, but there's cost requirements. And so, the hybrid model can often still be delivered with lower cost than a cloud exclusive model. &nbsp; 00;29;02;15 - 00;29;34;06 So, we're trying to be sensitive to the budgetary constraints of especially some of our early career investigators and offer a hybrid model to them as a way to get started without incurring the sometimes high costs of working in any of the major cloud providers. So, everybody in nearly every field that there is thinking about and talking about AI now and how it could change things dramatically. &nbsp; 00;29;34;08 - 00;29;59;06 What are you thinking about AI and machine learning when it comes to scientific research? Is it all positive and will it speed discovery and solutions getting to market? Or are you also waving the caution flag and trying to manage expectations? Because I think about how the combination of open science and it could get really interesting. &nbsp; 00;29;59;09 - 00;30;33;14 Yeah, I currently take a nuanced and cautious stance on AI and machine learning. If you're using those resources for data analysis, I see a lot of value to them. There's so many as we deal with these rapidly growing large datasets, the capacity of our minds to do the pattern recognition is limited. And so, AI and ML are great at pattern recognition in data. &nbsp; 00;30;33;14 - 00;31;24;04 And so, I think as a tool to support data analysis, I'm very positive. I worry more about the application and clinical practice of AI. I mean, being a member of the Ethical AI Initiative of the Center for Practical Bioethics in Kansas City, and I'm very impressed with the approach that they take and they deliver a workshop that is focused on if you're either buying a system that reports to be AI enabled or building something, what are the variety of ethical considerations that you should be considering? &nbsp; 00;31;24;06 - 00;31;55;11 And a particular area of concern is around health equity. And because we know that so many of these systems are trained on data sets that are skewed towards non-diverse populations. So, if that's what you're training these models with, and they will reinforce the inequities in health care. So, I think for some of those larger scale applications, we need to have a deliberate, careful and intentional approach. &nbsp; 00;31;55;13 - 00;32;22;24 It's not to say that there won't be positive uses of AI and ML, but I do think as we get closer to patient facing application, we need to be more intentional and more deliberate. Well, I want to be in a really good mood for the rest of the day, so could you tell us about research that's going on right now at Children's Mercy and some things that you're particularly excited about? &nbsp; 00;32;22;27 - 00;32;59;02 Yeah, and again, as I mentioned earlier, I really enjoy and thrive on the variety of work here. So I'm fortunate to collaborate, for example, with Dr. Bridgette Jones, who does research on health disparity and asthma. I'm fortunate to work with our Genome Center for Genomic Medicine, where they have a very large community facing project called Genomic Answers for Kids and focused on identifying the genetic basis for rare diseases. &nbsp; 00;32;59;05 - 00;33;28;23 I'm fortunate to collaborate with a wide group of experts on some of my own research where we use large de-identified clinical data from Oracle Health. So, two recent things we evaluated were how often and this is at a national level, are youth and young adults who present in the emergency room with a migraine, how often are they treated with an opioid? &nbsp; 00;33;28;25 - 00;33;59;29 The ideal would be 0 to 2%. We noticed that more than 20% of those youth and young adults nationally are treated with an opioid. So that type of research can then lend to process changes that challenge providers to reflect on their ordering patterns. So, the variety of really exciting research that we do at Children's Mercy is just something that excites me a lot. &nbsp; 00;34;00;03 - 00;34;32;15 Yeah, and on the genomics side, how close are we to, you know, all the exciting articles we read about the entire genome being mapped to the extent that we can go on and find the marker that is causing this rare disease and switch it off. Well, the very last part is where things get hard. But we've made huge strides in the recognition of the genetic basis for different rare health conditions. &nbsp; 00;34;32;18 - 00;35;09;01 Sometimes just finding that can lead to the realization that it's similar to a condition that presents differently but has a treatment available. And then you can try that medication on the patient with that genetic variant. And so those are the initial successes. I think the gene therapy type interventions that you might be alluding to, they're starting to regain some momentum, but that's going to be a long process. &nbsp; 00;35;09;04 - 00;35;42;17 So do you think people like me who just ask the question that I asked have over or heightened expectations? It's like, what is that balance between where the public thinks we should be and where actual research really is? Yeah, I think and that gets back to the even some of the societal topics that we were touching on earlier, where on the one hand there's elements of society that want research to move faster and to do more. &nbsp; 00;35;42;19 - 00;36;19;15 And then there's other elements that are much more of the go slow. And so, again, as a scientific community, finding that right balance and how we communicate about our work is really critical. And it's something that we really need to put an increased focus on to, you know, on the one hand, make sure that the advances that are complete and ready are utilized, which, you know, we all want that and that the emerging advances that people are participating in studies that they know that it is safe to participate in studies. &nbsp; 00;36;19;17 - 00;36;46;16 And then when the results of those studies are completed, that they're comfortable utilizing the output of that research. Well, for the last question, we'll stick with that societal aspect. You are an Oracle Council member, so you already know this, but Oracle believes that for the good of global health and humanity, we must understand and serve the needs of research and researchers at every level. &nbsp; 00;36;46;18 - 00;37;13;10 And it feels like we're facing bigger things like food security, disease prevention. Nobody needs another pandemic. What's your view on how research is only going to get more vital? And the pressure on research is only going to go up for kind of holding the earth and the species together? Yeah, that's a great question. And I am an optimist about research. &nbsp; 00;37;13;10 - 00;37;47;13 I believe that the work we do in research matters to the public and to the world. The examples you gave of food security, climate change, pandemics are all the, you know, major emerging concerns that all types of research are going to play a role in the solutions to those problems. And then I would pull us back to the question of how different would things have been if the pandemic had been ten years ago. &nbsp; 00;37;47;13 - 00;38;23;03 And to me, the research into many vaccines and rapid molecular diagnostics, those are all things that made the response to the pandemic. What it was, again, far from perfect, but much more effective than it would have been ten years ago were it not for all of the research that supported those developments. And I think that same mindset would apply to the other large scale problems and challenges that you mentioned. &nbsp; 00;38;23;05 - 00;38;44;00 Dr. Hoffman, thank you again for joining us today. You know, a lot of times our listeners will want to learn more about what you talked about or even get in touch with you. Is there any way they can do that? Sure. I'm on Twitter at Mark Hoffman K.C. I'm also on LinkedIn and my bio is available on the Children's Mercy website. &nbsp; 00;38;44;03 - 00;40;56;11 Great. We appreciate that. If you are interested in how Oracle can simplify and accelerate your research, you can check out Oracle dot com slash research. And join us next time on Research in Action. &nbsp; &nbsp; "> <meta property="og:image" content="http://assets.libsyn.com/show/446736?height=250&width=250&overlay=true"> <meta property="og:image:width" content="250"> <meta property="og:image:height" content="250"> <meta name="twitter:card" content="player"> <meta name="twitter:image" content="https://assets.libsyn.com/secure/item/27317634?height=250&width=250&overlay=true"> <meta name="twitter:player" content="https://play.libsyn.com/embed/episode/id/27317634/theme/modern/tdest_id/3743343"> <meta name="twitter:player:width" content="640"> <meta name="twitter:player:height" content="200"> <meta name="twitter:player:stream" content="https://traffic.libsyn.com/secure/researchinaction/Research_in_Action_S01_E16.mp3"> <meta name="twitter:player:stream:content_type" content="audio/mpeg"> <meta name="twitter:title" content="Research in Action: Transforming healthcare research with technology's latest capabilities"> <meta name="twitter:description" content="How do you connect the needs of researchers to the capabilities of technology? What are the main stages of research and the challenges faced at each stage? And will AI and machine learning speed up research and get solutions to market faster? We will learn those answers and more in this episode with Dr. Mark Hoffman, the Chief Research Information officer for Children’s Mercy and the Children’s Mercy Research Institute, a position he has held since 2016. Dr. Hoffman earned his doctorate in Bacteriology from the University of Wisconsin-Madison. He later joined Cerner as a software engineer where he advanced to the role of Vice President for Genomics and Research. Dr. Hoffman was also part of the faculty at the University of Missouri Kansas City (UMKC) in the Departments of Biomedical and Health Informatics and Pediatrics. His formal training in research and experience in software development has prepared him to connect the needs of researchers to the capabilities of technology. His work is focused on identifying the best capabilities possible to meet rapidly changing requirements in genomics, public health, and big data. Dr. Hoffman is an inventor of 22 issued patents, a member of the American Academy of Inventors, a TED talk alumnus, and an award-winning healthcare product developer. You can learn more about Dr. Hoffman and Children’s Mercy here: Learn more about Oracle for Researcher here: ---------------------------------------------------------- Episode Transcript 00;00;00;00 - 00;00;26;02 What are the three main stages of research and the challenges each are facing? How are researchers handling the new federal policies around data sharing? And will AI and machine learning speed research and get solutions to market faster? We'll get those answers and more on this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research. &nbsp; 00;00;26;02 - 00;00;49;21 I'm Mike Stiles. And today our guest is Dr. Mark Hoffman, who is the Chief Research Information Officer for Children's Mercy and the Children's Mercy Research Institute. That's a position he's held since 2016. Dr. Hoffman earned his doctorate in bacteriology from the University of Wisconsin-Madison and later joined Cerner as a software engineer, where he went on to be Vice President for genomics and research. &nbsp; 00;00;49;24 - 00;01;17;11 Dr. Hoffman was also part of the faculty at the University of Missouri, Kansas City, and the Departments of Biomedical and Health Informatics and Pediatrics. Now, because he's had formal training and research and real-world experience in software development, he's kind of uniquely qualified to talk about what researchers need when it comes to technology. His work focuses on identifying the best capabilities to meet requirements in genomics, public health and big data that are always changing. &nbsp; 00;01;17;14 - 00;01;38;22 He's an inventor of 95 issued patents, a member of the American Academy of Inventors, a TED Talk alumnus, and an award-winning health care product developer. And honest to gosh, that's about the shortest intro I could come up with for someone who is so accomplished. So, we're glad you are with us today, Dr. Hoffman. Well, thanks, Mike. I look forward to talking with you. &nbsp; 00;01;38;24 - 00;02;05;06 Our audience is going to be particularly lucky that they decided to stream this episode because there's a lot to cover. But first of all, what got you into research to begin with? Kind of what led you to each step along the way to where you are now at Children's Mercy? Well, it's a long story, but, you know, I think as a kid, I was always curious and I enjoyed Legos and, you know, taking things apart. &nbsp; 00;02;05;06 - 00;02;36;00 And so, in hindsight, I see all the foundations. And that took me a while to realize that my interests are really split between doing science and building technologies. And so, I see myself as very fortunate to have a role that lets me keep one foot in each of those areas of interest. So, you went when you made the decision to go to Cerner and go into that software development world. &nbsp; 00;02;36;02 - 00;03;05;24 What inspired you to do that? It's interesting. When I was in graduate school studying bacteriology, I was funded by an NIH program that if you're in the life sciences, you were required to take coursework outside the life sciences. I chose to do that in computer science. And then the other requirement was you were required to do an industry internship one summer. &nbsp; 00;03;05;26 - 00;03;31;27 Most of my peers chose to do that in pharma. I chose instead to do my internship at a software development company that does bioinformatics software development. Realized how much I liked that type of work and building things that get used in the real world. It's funny, but to this day, some of the features that I developed are still part of their application suite. &nbsp; 00;03;31;27 - 00;04;04;27 So, I learned from that that I enjoy the software and technology and development process. When there was the opportunity to join Cerner as a software engineer. I jumped at it and happened to be in their microbiology product line, so I was able to talk with the clients about what they were struggling with in the lab, understand that, and then translate that into whatever changes were needed in the software. &nbsp; 00;04;05;00 - 00;04;26;28 Did you expect that to be the case that you would be able to keep a foot in both sides on both the technology and the research side? Or was that something like you never thought that could happen? I didn't plan it this way, but I feel very fortunate that I'm able to exercise so many of my different interests. &nbsp; 00;04;27;00 - 00;05;12;19 So obviously children's mercy benefits from your professional expertise, but behind that you've got a real personal commitment and passion for the work that you're doing that kind of increases your value even more. If you're willing, tell us about that personal connection. And just in general, both Cerner and Children's Mercy are based in Kansas City. And as a parent, while I was working at Cerner, over time, both of our children have needed inpatient care at Children's Mercy Hospital and just the compassion and caring and quality of care and the creativity that we often saw with some of our children's physicians. &nbsp; 00;05;12;22 - 00;05;55;21 The willingness to keep trying things until they could help our kids work through their different health concerns has made a huge impression on me. Now, when I walk through the hospital and see parents with their kids who are going through really some of the most difficult situations you can imagine, I try to take a moment and share a smile or, you know, hold the elevator for a parent. I'm just trying to even though I'm not involved in patient care, I just really am empathetic to those families and see that as really kind of my connection to purpose. &nbsp; 00;05;55;24 - 00;06;35;13 What are the unique differences between a children's centered health care provider like that and, say, a regular adult hospital? What are the biggest differences that the staff has to operate with? I think probably the key difference is with adult medicine, you're really working primarily with the patient and they're making their own decisions. In pediatrics, you're working with children and they're their care providers so that there's more voices involved, you know, with younger children. &nbsp; 00;06;35;14 - 00;07;08;04 It's really is the care providers who are making those decisions with teenagers and adolescents, they certainly will have their own voice into the decision making. So that's really a key difference in pediatrics. I think pediatric medicine is interesting because it's both very cautious but also very willing to innovate. And I find that often to be a really interesting dynamic. &nbsp; 00;07;08;06 - 00;07;33;07 So you were a fan, as it were, of Children's Mercy before you started working there? Absolutely. That was a big part of my decision-making process to come here. So how did that come about that you started working for Children's Mercy? And what exactly do you do there? So, I made the difficult decision to move forward in my career in 2013. &nbsp; 00;07;33;09 - 00;07;58;04 The step that I took was to join the University of Missouri, Kansas City School of Medicine, join the faculty there and form what we called the Center of Health Insights. Through those negotiations, Children's Mercy funded 25% of my role at the university. And so, I already had not quite one foot, but at least a few toes in the door. &nbsp; 00;07;58;06 - 00;08;26;19 And I spent a lot of time building relationships with Children's Mercy. About three years into that, there was some hiring of senior leadership for the Research Institute, and I was involved in that and made the case that I'm seeing other organizations create the Chief Research Information Officer role. That idea stuck and I was hired as our first chief Research Information Officer. &nbsp; 00;08;26;21 - 00;08;50;09 So it sounds like what you want, what you're kind of your North star is to make sure researchers at Children's Mercy can tap into the best technical resources and experts out there, because especially medical researchers, everyone expects them to find answers quickly. You know, there are waiting to be helped. So. What's a typical day like for a chief research information officer? &nbsp; 00;08;50;12 - 00;09;27;09 I tell everybody there really is no typical day. Sometimes I'm down in the weeds talking through technical issues and then in the next meeting can be talking with organizational ownership about high level strategy. Part of what I enjoy is the variety in my role. I don't support any single clinical area of research. So, one meeting just yesterday was with our neurology department, where we're doing research into telemedicine and that can support rural communities where children have epilepsy. &nbsp; 00;09;27;11 - 00;09;55;25 And so there was that meeting and then there was another meeting within the same 24 hours about long read genomic sequencing with our genome center. So just context shifting and you know, always with the theme though, of trying to find ways for technology to be an enabler. All too often my peers in research feel that technology sometimes creates a barrier. &nbsp; 00;09;55;25 - 00;10;25;08 And so, one of my goals is just to try to reduce the barriers and increase the opportunities. And for you, it seems like, you know, you actually see the faces of the people that this research is trying to help. Does that add yet another motivational personal element behind kind of your mission there? Absolutely. I think through the pandemic, the entire work model for people in technology in particular has changed. &nbsp; 00;10;25;10 - 00;10;55;26 I know many of us spent a long time working from home and when I was able to start coming back on site, I just find it very motivating to go to the hospital cafeteria or, you know, get out of my research and technology bubble and be among the patients and families. Well, you've met researchers of every kind all over the world, people just like those who listen to this podcast and you know how they define success and also know what challenges they face. &nbsp; 00;10;55;28 - 00;11;25;06 I'll get to what those are in a second, but let's kind of define research. The stages are basic, translational and clinical. What exactly are those stages and how do you maneuver through those to get to actual innovation? I look at those where I see basic research as working with either molecules, cells or even animal models to understand the biological process. &nbsp; 00;11;25;09 - 00;11;57;14 And then the first level of translational research is taking a subset of those basic findings and exploring whether they may have a role to play in clinical practice. So sometimes that can also be where things start to be defined in an animal model. And then you start when something looks promising, you start working through early-stage clinical trials for safety, and then you start working with patient populations. &nbsp; 00;11;57;17 - 00;12;32;08 And then ultimately, if something's successful and does seem to benefit patients, then it gets rolled into practice and then there's an additional layer that we call outcomes research, where periodically it's important to review whether, you know, those new interventions or new tests really are making a positive difference in patient outcomes. That's kind of how I like to conceptualize the different phases of both basic and translational research. &nbsp; 00;12;32;10 - 00;13;06;17 Well, I'm assuming the challenges and opportunities are different depending on what kind of research we're talking about. So, let's start with your world of clinical research. What makes life unnecessarily harder for clinical researchers and does technology offer any help? I think no matter who I spoke with, recruitment into clinical trials is a continuing challenge. And I do think that data and technology have a helpful role to play in that. &nbsp; 00;13;06;20 - 00;13;37;07 Some of our work, as well as some work within Oracle or Oracle Health, is focused on using large de-identified data sets to evaluate the feasibility of doing research at a particular setting. Do they have enough patients who might meet the inclusion criteria? And so, I do think that data and technology have a role to play in the recruitment challenge. &nbsp; 00;13;37;10 - 00;14;05;23 That's kind of interesting that that recruiting for some of these trials is so difficult. What's the reluctance? You know, people have these conditions, it seems like they would be more than willing to try, you know, something? Why the reluctance? I think there's a number of factors. One is sometimes the designers of a study are maybe overly optimistic about the population. &nbsp; 00;14;05;26 - 00;14;36;01 Sometimes they underestimate the concerns that patients and their families may have. So that's one factor. I think as a scientific community, we need to continue working on how we communicate with the public, especially now, you know, with what I think of as the epidemic of mis- and dis-information. Those may not be preventing people from joining studies, but certainly they impact the willingness to utilize the benefits of research. &nbsp; 00;14;36;04 - 00;15;19;10 Yeah. Do you worry about the level of trust declining in health care researchers? I mean, the pandemic probably we took a hit with that. It's you know, that's a really interesting topic because on the one hand, I often reflect on the pandemic and if it had been ten years ago how different and much worse it would have been, because it really would have been unheard of to have in lab diagnostic tests within weeks, at home, testing within months, and a functional and safe vaccine within a year. &nbsp; 00;15;19;12 - 00;16;16;09 Ten years ago, that would not have been possible. And that's exclusively because of our capacity and in doing clinical research. I think, though, there's a lot of challenging dynamics in play that as a scientific community, we just need to keep getting out into the public, explaining in accessible terms what research is about and why it matters. One thing that we're very intentional about here at Children's Mercy is we have both parent and youth advisory boards, and so we work with them closely as we develop new research initiatives so that they're at the table and they're also out in the community, in the community, sharing the work that's happening here, because that's in so many ways &nbsp; 00;16;16;09 - 00;16;44;18 far more effective to hear from your neighbors, your friends at work than it is to hear from, you know, those of us who are doing the technical work. Well, kind of same question for those at the basic or fundamental research level, what are their biggest headaches? And, you know, is technology being applied to those headaches? Yeah, I think I wouldn't necessarily call them so much headaches. &nbsp; 00;16;44;18 - 00;17;21;07 But, you know, all categories of research, of course, feel that funding is always a challenge. I think for basic research, the volume of data that many techniques, not all, but many generate, creates an exciting opportunity for people who work in data science. For example, genomic sequencing, you know, is highly automated now, but the volume of data that any one genomic evaluation can generate is massive as well as, you know, very complex. &nbsp; 00;17;21;07 - 00;17;48;14 And so, the informatics and data science opportunities to analyze these growing volume of data is really exciting. Yeah, it feels like even though there are different research stages, there's obviously overlap when it comes to some of the roadblocks and opportunities to knock those roadblocks down. I mean, what do you see as kind of the shared pain points? You mentioned funding, I guess that goes across all stages. &nbsp; 00;17;48;17 - 00;18;27;09 Yeah, I think especially in a clinical setting there, there's a very high focus on cybersecurity. So, the research community is not always as involved in that as they probably needed to be. So, you know, we even have a lot of considerations that we incorporate into making sure that our systems, our data are secure to the highest standards. So that also my team tries to insulate the researchers from that type of work because we want them to be focused on doing science. &nbsp; 00;18;27;09 - 00;18;53;28 And in many organizations, we see researchers who have to get their hands in some of these other processes and technology issues. So a key part of what I see as my role and my team's role is insulating the researchers from those types of concerns. Yeah, which I'm sure they greatly appreciate. Obviously, there is a lot of compute resources that are required. &nbsp; 00;18;54;00 - 00;19;28;24 So, I imagine one of your challenges is to make sure these folks have the kind of compute resources they need. Yeah, and that's really an exciting area. We have recently completed the migration for our Genome Center of their bioinformatics pipeline from an on-premise data center to a completely cloud-based system. And we're excited that we're starting to see that gain of efficiencies from that, you know, moving that to a complete cloud model. &nbsp; 00;19;28;24 - 00;20;01;12 We have other projects that are more of a hybrid model. We do have a data center and our new research institute building. So, I'm excited about the new world where we can really offer computational and storage resources at a totally different scale than was needed ten years ago or even five years ago. Well, I know you're part of the Oracle Research Industry Strategy Council, a group that talked about a lot of the same stuff, pretty recently. &nbsp; 00;20;01;12 - 00;20;24;14 Just this May actually. So, one of the topics of discussion was how some researchers who are federally funded are kind of I don't know if struggling is the right word, but dealing with new policies around data storage and data sharing. The NIH has gotten real serious about those policies earlier this year. Why are these policies like FAIR principles coming down now? &nbsp; 00;20;24;17 - 00;20;56;13 And how ready are researchers to cope with those new protocols? Plus, whatever else may pop up in terms of regulation? Yeah, I think the change in policy reflects a realization on the funders that, you know, despite the expectation that researchers would share all of most of their data that was generated with those taxpayer funds, that that wasn't happening at the consistency level that they expected. &nbsp; 00;20;56;14 - 00;21;33;02 So, the major change this year is that that expectation is articulated much more forcefully. And so now anybody doing federally funded research is expected to make any data that does not include protected health information available to the community. I think some researchers are already doing that. So again, in the genomics world, that's already a fairly common practice. But in other areas it will require some change and different ways of thinking. &nbsp; 00;21;33;04 - 00;22;06;12 I'm not seeing a high level of anxiety or concern about it. I think it's something that we can work through. It's a matter of right sizing the solution. So, we don't want to oversize how we accommodate the new regulations, but we want to make sure that all of our researchers are equipped to be compliant. The reluctance that there is to data sharing is that just concerns about proprietary stuff or researchers are thinking about going to market with this. &nbsp; 00;22;06;12 - 00;22;31;02 And, you know, they want to keep it close to the vest. Sometimes that's the case. I think sometimes it's also academic competitive concerns. So, if you're competing for grant funding with the same people who could download your data, are you giving you know, there's concern that you're giving them, if not a head start, at least the capacity to catch up faster than they otherwise would have. &nbsp; 00;22;31;04 - 00;23;05;04 Does technology help in any way to adhere to these new policies and facilitate that kind of data sharing? I definitely believe it can. There's a variety of portals that can enable researchers to share their data. I think many of these have features that researchers like so that you can track how often your data assets are downloaded. In some cases, you can get a sense for, you know, where are the downloads originating. &nbsp; 00;23;05;07 - 00;23;39;10 What I think will be interesting over the next few years. Right now, in academia, tenure decisions are made based on publications and how often your papers are cited and so forth. I think if we can see a movement towards rewarding, how often is your data downloaded and accessed and utilized and rewarding, you know, academics that do that. I think that will be a real important factor in changing the culture around that. &nbsp; 00;23;39;12 - 00;24;04;28 So, in a couple of past episodes, I actually did ask our guests about this concept of open science that's grounded in FAIR principles. From what I've learned, open science doesn't mean, you know, anything goes, everybody dive in. It's all chaos. There is still scientific rigor. What does open science mean to you? What's open about it and what's still closed about it? &nbsp; 00;24;05;00 - 00;24;48;24 I think data sharing is a key part of open science, you know, and this is where having one foot in technology and one foot in science is helpful because if you look at the open-source software movement, there was very similar cultural resistance to that. But then as people realized that if you put your software code out for the public and they find and fix bugs in that code, that similar process can start to occur with scientific data where maybe there is an inconsistency or maybe there's a pattern in the data that you didn't recognize as, but somebody else does. &nbsp; 00;24;48;27 - 00;25;16;08 So, I think there's a lot to be learned from the process that the open-source software world witnessed and experienced. I think certainly in both cases, putting your either your code or your data out there as a vulnerable feeling for a lot of people. So, helping create a comfort level to get past that vulnerability is really important for the success of both. &nbsp; 00;25;16;08 - 00;25;44;21 But I think when you look at the long-term benefits of open science, I personally believe that the quality of work will go up. And when you pull it back to pediatrics, I think some of the very interesting work in pediatrics revolves around rare disease. And so no single organization is likely to have the numbers of patients with these rare diseases that they can independently gain the insights they need to. &nbsp; 00;25;44;21 - 00;26;13;12 So, collaborating and sharing data is essential for so many areas of pediatric research in particular. Well, for all the acronym fans out there, we talk about FAIR principles. That stands for findability, accessibility, interoperability and reusability. So yeah, I guess on a scale of 1 to 10, how close do you think we are to being FAIR? It'll vary from place to place, but I would just pull a number out of the air. &nbsp; 00;26;13;12 - 00;26;36;29 On average, I would give us a six or seven. Okay, already. Good. But probably going to get better is how I kind of interpret that answer. Yeah. So, one of the guests I pestered with the open science questions was Amy Dockser Marcus of the Wall Street Journal. She wrote a book called, “We The Scientists: How a Daring Team of Parents and Doctors Forged a New Path for Medicine.” &nbsp; 00;26;37;01 - 00;27;10;13 And basically, it's about patient-scientist-doctor collaborations and how that approach could get us to solutions faster. Do you see these collaborations happening? Are doctors and scientists more open to listening to and including patients and their caregivers? Yeah, I'm really seeing, you know, exciting changes in that. I mentioned earlier that we have patient and parent community advisory groups that are increasingly engaged and active in our research strategy. &nbsp; 00;27;10;16 - 00;27;44;14 And it's really shifting from just sometimes those initiatives start with us just telling those groups about what we're doing. But now it's really shifting to how can we do it better and how can we work through these barriers to recruitment, How can we make sure that we're reaching underserved populations? So, I find this whole engagement model to be a really exciting development, and it's really gaining much needed momentum. &nbsp; 00;27;44;16 - 00;28;12;13 And I find it inspiring and motivating to hear, you know, parents of children who have gone through a very difficult health conditions share their stories because that motivates me as well and motivates my colleagues. So, it really is an exciting development that's really picked up momentum. Well, thinking about the technology part, researchers kind of have to figure out what the appropriate tools are and deal with. &nbsp; 00;28;12;14 - 00;28;30;28 Okay, is this data I need and legacy on premises systems or can I get to it in the cloud? And you touched on this a little bit earlier about how you have a cloud solution, but you still also have some hybrid situations. Are you a hybrid guy or do you think all things in the cloud is the way to go? &nbsp; 00;28;30;28 - 00;29;02;13 Which way do you lean? My approach to everything is what are your requirements? And then I will help you fulfill your requirements. And so increasingly we can fulfill many of those requirements with an exclusively cloud-based model. Where it's interesting is that not only are there functional requirements, but there's cost requirements. And so, the hybrid model can often still be delivered with lower cost than a cloud exclusive model. &nbsp; 00;29;02;15 - 00;29;34;06 So, we're trying to be sensitive to the budgetary constraints of especially some of our early career investigators and offer a hybrid model to them as a way to get started without incurring the sometimes high costs of working in any of the major cloud providers. So, everybody in nearly every field that there is thinking about and talking about AI now and how it could change things dramatically. &nbsp; 00;29;34;08 - 00;29;59;06 What are you thinking about AI and machine learning when it comes to scientific research? Is it all positive and will it speed discovery and solutions getting to market? Or are you also waving the caution flag and trying to manage expectations? Because I think about how the combination of open science and it could get really interesting. &nbsp; 00;29;59;09 - 00;30;33;14 Yeah, I currently take a nuanced and cautious stance on AI and machine learning. If you're using those resources for data analysis, I see a lot of value to them. There's so many as we deal with these rapidly growing large datasets, the capacity of our minds to do the pattern recognition is limited. And so, AI and ML are great at pattern recognition in data. &nbsp; 00;30;33;14 - 00;31;24;04 And so, I think as a tool to support data analysis, I'm very positive. I worry more about the application and clinical practice of AI. I mean, being a member of the Ethical AI Initiative of the Center for Practical Bioethics in Kansas City, and I'm very impressed with the approach that they take and they deliver a workshop that is focused on if you're either buying a system that reports to be AI enabled or building something, what are the variety of ethical considerations that you should be considering? &nbsp; 00;31;24;06 - 00;31;55;11 And a particular area of concern is around health equity. And because we know that so many of these systems are trained on data sets that are skewed towards non-diverse populations. So, if that's what you're training these models with, and they will reinforce the inequities in health care. So, I think for some of those larger scale applications, we need to have a deliberate, careful and intentional approach. &nbsp; 00;31;55;13 - 00;32;22;24 It's not to say that there won't be positive uses of AI and ML, but I do think as we get closer to patient facing application, we need to be more intentional and more deliberate. Well, I want to be in a really good mood for the rest of the day, so could you tell us about research that's going on right now at Children's Mercy and some things that you're particularly excited about? &nbsp; 00;32;22;27 - 00;32;59;02 Yeah, and again, as I mentioned earlier, I really enjoy and thrive on the variety of work here. So I'm fortunate to collaborate, for example, with Dr. Bridgette Jones, who does research on health disparity and asthma. I'm fortunate to work with our Genome Center for Genomic Medicine, where they have a very large community facing project called Genomic Answers for Kids and focused on identifying the genetic basis for rare diseases. &nbsp; 00;32;59;05 - 00;33;28;23 I'm fortunate to collaborate with a wide group of experts on some of my own research where we use large de-identified clinical data from Oracle Health. So, two recent things we evaluated were how often and this is at a national level, are youth and young adults who present in the emergency room with a migraine, how often are they treated with an opioid? &nbsp; 00;33;28;25 - 00;33;59;29 The ideal would be 0 to 2%. We noticed that more than 20% of those youth and young adults nationally are treated with an opioid. So that type of research can then lend to process changes that challenge providers to reflect on their ordering patterns. So, the variety of really exciting research that we do at Children's Mercy is just something that excites me a lot. &nbsp; 00;34;00;03 - 00;34;32;15 Yeah, and on the genomics side, how close are we to, you know, all the exciting articles we read about the entire genome being mapped to the extent that we can go on and find the marker that is causing this rare disease and switch it off. Well, the very last part is where things get hard. But we've made huge strides in the recognition of the genetic basis for different rare health conditions. &nbsp; 00;34;32;18 - 00;35;09;01 Sometimes just finding that can lead to the realization that it's similar to a condition that presents differently but has a treatment available. And then you can try that medication on the patient with that genetic variant. And so those are the initial successes. I think the gene therapy type interventions that you might be alluding to, they're starting to regain some momentum, but that's going to be a long process. &nbsp; 00;35;09;04 - 00;35;42;17 So do you think people like me who just ask the question that I asked have over or heightened expectations? It's like, what is that balance between where the public thinks we should be and where actual research really is? Yeah, I think and that gets back to the even some of the societal topics that we were touching on earlier, where on the one hand there's elements of society that want research to move faster and to do more. &nbsp; 00;35;42;19 - 00;36;19;15 And then there's other elements that are much more of the go slow. And so, again, as a scientific community, finding that right balance and how we communicate about our work is really critical. And it's something that we really need to put an increased focus on to, you know, on the one hand, make sure that the advances that are complete and ready are utilized, which, you know, we all want that and that the emerging advances that people are participating in studies that they know that it is safe to participate in studies. &nbsp; 00;36;19;17 - 00;36;46;16 And then when the results of those studies are completed, that they're comfortable utilizing the output of that research. Well, for the last question, we'll stick with that societal aspect. You are an Oracle Council member, so you already know this, but Oracle believes that for the good of global health and humanity, we must understand and serve the needs of research and researchers at every level. &nbsp; 00;36;46;18 - 00;37;13;10 And it feels like we're facing bigger things like food security, disease prevention. Nobody needs another pandemic. What's your view on how research is only going to get more vital? And the pressure on research is only going to go up for kind of holding the earth and the species together? Yeah, that's a great question. And I am an optimist about research. &nbsp; 00;37;13;10 - 00;37;47;13 I believe that the work we do in research matters to the public and to the world. The examples you gave of food security, climate change, pandemics are all the, you know, major emerging concerns that all types of research are going to play a role in the solutions to those problems. And then I would pull us back to the question of how different would things have been if the pandemic had been ten years ago. &nbsp; 00;37;47;13 - 00;38;23;03 And to me, the research into many vaccines and rapid molecular diagnostics, those are all things that made the response to the pandemic. What it was, again, far from perfect, but much more effective than it would have been ten years ago were it not for all of the research that supported those developments. And I think that same mindset would apply to the other large scale problems and challenges that you mentioned. &nbsp; 00;38;23;05 - 00;38;44;00 Dr. Hoffman, thank you again for joining us today. You know, a lot of times our listeners will want to learn more about what you talked about or even get in touch with you. Is there any way they can do that? Sure. I'm on Twitter at Mark Hoffman K.C. I'm also on LinkedIn and my bio is available on the Children's Mercy website. &nbsp; 00;38;44;03 - 00;40;56;11 Great. We appreciate that. If you are interested in how Oracle can simplify and accelerate your research, you can check out Oracle dot com slash research. 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What are the main stages of research and the challenges faced at each stage? And will AI and machine learning speed up research and get solutions to market faster? We will learn those answers and more in this episode with Dr. Mark Hoffman, the Chief Research Information officer for Children’s Mercy and the Children’s Mercy Research Institute, a position he has held since 2016. Dr. Hoffman earned his doctorate in Bacteriology from the University of Wisconsin-Madison. He later joined Cerner as a software engineer where he advanced to the role of Vice President for Genomics and Research. Dr. Hoffman was also part of the faculty at the University of Missouri Kansas City (UMKC) in the Departments of Biomedical and Health Informatics and Pediatrics. His formal training in research and experience in software development has prepared him to connect the needs of researchers to the capabilities of technology. His work is focused on identifying the best capabilities possible to meet rapidly changing requirements in genomics, public health, and big data. Dr. Hoffman is an inventor of 22 issued patents, a member of the American Academy of Inventors, a TED talk alumnus, and an award-winning healthcare product developer. You can learn more about Dr. Hoffman and Children’s Mercy here: <a href="https://www.childrensmercy.org/" target="_blank" rel= "nofollow noreferrer noopener">https://www.childrensmercy.org</a> Learn more about Oracle for Researcher here: <a href= "http://www.oracle.com/research">http://www.oracle.com/research</a> ---------------------------------------------------------- Episode Transcript 00;00;00;00 - 00;00;26;02 What are the three main stages of research and the challenges each are facing? How are researchers handling the new federal policies around data sharing? And will AI and machine learning speed research and get solutions to market faster? We'll get those answers and more on this episode of Research in Action. Hello and welcome back to Research in Action, brought to you by Oracle for Research.   00;00;26;02 - 00;00;49;21 I'm Mike Stiles. And today our guest is Dr. Mark Hoffman, who is the Chief Research Information Officer for Children's Mercy and the Children's Mercy Research Institute. That's a position he's held since 2016. Dr. Hoffman earned his doctorate in bacteriology from the University of Wisconsin-Madison and later joined Cerner as a software engineer, where he went on to be Vice President for genomics and research.   00;00;49;24 - 00;01;17;11 Dr. Hoffman was also part of the faculty at the University of Missouri, Kansas City, and the Departments of Biomedical and Health Informatics and Pediatrics. Now, because he's had formal training and research and real-world experience in software development, he's kind of uniquely qualified to talk about what researchers need when it comes to technology. His work focuses on identifying the best capabilities to meet requirements in genomics, public health and big data that are always changing.   00;01;17;14 - 00;01;38;22 He's an inventor of 95 issued patents, a member of the American Academy of Inventors, a TED Talk alumnus, and an award-winning health care product developer. And honest to gosh, that's about the shortest intro I could come up with for someone who is so accomplished. So, we're glad you are with us today, Dr. Hoffman. Well, thanks, Mike. I look forward to talking with you.   00;01;38;24 - 00;02;05;06 Our audience is going to be particularly lucky that they decided to stream this episode because there's a lot to cover. But first of all, what got you into research to begin with? Kind of what led you to each step along the way to where you are now at Children's Mercy? Well, it's a long story, but, you know, I think as a kid, I was always curious and I enjoyed Legos and, you know, taking things apart.   00;02;05;06 - 00;02;36;00 And so, in hindsight, I see all the foundations. And that took me a while to realize that my interests are really split between doing science and building technologies. And so, I see myself as very fortunate to have a role that lets me keep one foot in each of those areas of interest. So, you went when you made the decision to go to Cerner and go into that software development world.   00;02;36;02 - 00;03;05;24 What inspired you to do that? It's interesting. When I was in graduate school studying bacteriology, I was funded by an NIH program that if you're in the life sciences, you were required to take coursework outside the life sciences. I chose to do that in computer science. And then the other requirement was you were required to do an industry internship one summer.   00;03;05;26 - 00;03;31;27 Most of my peers chose to do that in pharma. I chose instead to do my internship at a software development company that does bioinformatics software development. Realized how much I liked that type of work and building things that get used in the real world. It's funny, but to this day, some of the features that I developed are still part of their application suite.   00;03;31;27 - 00;04;04;27 So, I learned from that that I enjoy the software and technology and development process. When there was the opportunity to join Cerner as a software engineer. I jumped at it and happened to be in their microbiology product line, so I was able to talk with the clients about what they were struggling with in the lab, understand that, and then translate that into whatever changes were needed in the software.   00;04;05;00 - 00;04;26;28 Did you expect that to be the case that you would be able to keep a foot in both sides on both the technology and the research side? Or was that something like you never thought that could happen? I didn't plan it this way, but I feel very fortunate that I'm able to exercise so many of my different interests.   00;04;27;00 - 00;05;12;19 So obviously children's mercy benefits from your professional expertise, but behind that you've got a real personal commitment and passion for the work that you're doing that kind of increases your value even more. If you're willing, tell us about that personal connection. And just in general, both Cerner and Children's Mercy are based in Kansas City. And as a parent, while I was working at Cerner, over time, both of our children have needed inpatient care at Children's Mercy Hospital and just the compassion and caring and quality of care and the creativity that we often saw with some of our children's physicians.   00;05;12;22 - 00;05;55;21 The willingness to keep trying things until they could help our kids work through their different health concerns has made a huge impression on me. Now, when I walk through the hospital and see parents with their kids who are going through really some of the most difficult situations you can imagine, I try to take a moment and share a smile or, you know, hold the elevator for a parent. I'm just trying to even though I'm not involved in patient care, I just really am empathetic to those families and see that as really kind of my connection to purpose.   00;05;55;24 - 00;06;35;13 What are the unique differences between a children's centered health care provider like that and, say, a regular adult hospital? What are the biggest differences that the staff has to operate with? I think probably the key difference is with adult medicine, you're really working primarily with the patient and they're making their own decisions. In pediatrics, you're working with children and they're their care providers so that there's more voices involved, you know, with younger children.   00;06;35;14 - 00;07;08;04 It's really is the care providers who are making those decisions with teenagers and adolescents, they certainly will have their own voice into the decision making. So that's really a key difference in pediatrics. I think pediatric medicine is interesting because it's both very cautious but also very willing to innovate. And I find that often to be a really interesting dynamic.   00;07;08;06 - 00;07;33;07 So you were a fan, as it were, of Children's Mercy before you started working there? Absolutely. That was a big part of my decision-making process to come here. So how did that come about that you started working for Children's Mercy? And what exactly do you do there? So, I made the difficult decision to move forward in my career in 2013.   00;07;33;09 - 00;07;58;04 The step that I took was to join the University of Missouri, Kansas City School of Medicine, join the faculty there and form what we called the Center of Health Insights. Through those negotiations, Children's Mercy funded 25% of my role at the university. And so, I already had not quite one foot, but at least a few toes in the door.   00;07;58;06 - 00;08;26;19 And I spent a lot of time building relationships with Children's Mercy. About three years into that, there was some hiring of senior leadership for the Research Institute, and I was involved in that and made the case that I'm seeing other organizations create the Chief Research Information Officer role. That idea stuck and I was hired as our first chief Research Information Officer.   00;08;26;21 - 00;08;50;09 So it sounds like what you want, what you're kind of your North star is to make sure researchers at Children's Mercy can tap into the best technical resources and experts out there, because especially medical researchers, everyone expects them to find answers quickly. You know, there are waiting to be helped. So. What's a typical day like for a chief research information officer?   00;08;50;12 - 00;09;27;09 I tell everybody there really is no typical day. Sometimes I'm down in the weeds talking through technical issues and then in the next meeting can be talking with organizational ownership about high level strategy. Part of what I enjoy is the variety in my role. I don't support any single clinical area of research. So, one meeting just yesterday was with our neurology department, where we're doing research into telemedicine and that can support rural communities where children have epilepsy.   00;09;27;11 - 00;09;55;25 And so there was that meeting and then there was another meeting within the same 24 hours about long read genomic sequencing with our genome center. So just context shifting and you know, always with the theme though, of trying to find ways for technology to be an enabler. All too often my peers in research feel that technology sometimes creates a barrier.   00;09;55;25 - 00;10;25;08 And so, one of my goals is just to try to reduce the barriers and increase the opportunities. And for you, it seems like, you know, you actually see the faces of the people that this research is trying to help. Does that add yet another motivational personal element behind kind of your mission there? Absolutely. I think through the pandemic, the entire work model for people in technology in particular has changed.   00;10;25;10 - 00;10;55;26 I know many of us spent a long time working from home and when I was able to start coming back on site, I just find it very motivating to go to the hospital cafeteria or, you know, get out of my research and technology bubble and be among the patients and families. Well, you've met researchers of every kind all over the world, people just like those who listen to this podcast and you know how they define success and also know what challenges they face.   00;10;55;28 - 00;11;25;06 I'll get to what those are in a second, but let's kind of define research. The stages are basic, translational and clinical. What exactly are those stages and how do you maneuver through those to get to actual innovation? I look at those where I see basic research as working with either molecules, cells or even animal models to understand the biological process.   00;11;25;09 - 00;11;57;14 And then the first level of translational research is taking a subset of those basic findings and exploring whether they may have a role to play in clinical practice. So sometimes that can also be where things start to be defined in an animal model. And then you start when something looks promising, you start working through early-stage clinical trials for safety, and then you start working with patient populations.   00;11;57;17 - 00;12;32;08 And then ultimately, if something's successful and does seem to benefit patients, then it gets rolled into practice and then there's an additional layer that we call outcomes research, where periodically it's important to review whether, you know, those new interventions or new tests really are making a positive difference in patient outcomes. That's kind of how I like to conceptualize the different phases of both basic and translational research.   00;12;32;10 - 00;13;06;17 Well, I'm assuming the challenges and opportunities are different depending on what kind of research we're talking about. So, let's start with your world of clinical research. What makes life unnecessarily harder for clinical researchers and does technology offer any help? I think no matter who I spoke with, recruitment into clinical trials is a continuing challenge. And I do think that data and technology have a helpful role to play in that.   00;13;06;20 - 00;13;37;07 Some of our work, as well as some work within Oracle or Oracle Health, is focused on using large de-identified data sets to evaluate the feasibility of doing research at a particular setting. Do they have enough patients who might meet the inclusion criteria? And so, I do think that data and technology have a role to play in the recruitment challenge.   00;13;37;10 - 00;14;05;23 That's kind of interesting that that recruiting for some of these trials is so difficult. What's the reluctance? You know, people have these conditions, it seems like they would be more than willing to try, you know, something? Why the reluctance? I think there's a number of factors. One is sometimes the designers of a study are maybe overly optimistic about the population.   00;14;05;26 - 00;14;36;01 Sometimes they underestimate the concerns that patients and their families may have. So that's one factor. I think as a scientific community, we need to continue working on how we communicate with the public, especially now, you know, with what I think of as the epidemic of mis- and dis-information. Those may not be preventing people from joining studies, but certainly they impact the willingness to utilize the benefits of research.   00;14;36;04 - 00;15;19;10 Yeah. Do you worry about the level of trust declining in health care researchers? I mean, the pandemic probably we took a hit with that. It's you know, that's a really interesting topic because on the one hand, I often reflect on the pandemic and if it had been ten years ago how different and much worse it would have been, because it really would have been unheard of to have in lab diagnostic tests within weeks, at home, testing within months, and a functional and safe vaccine within a year.   00;15;19;12 - 00;16;16;09 Ten years ago, that would not have been possible. And that's exclusively because of our capacity and in doing clinical research. I think, though, there's a lot of challenging dynamics in play that as a scientific community, we just need to keep getting out into the public, explaining in accessible terms what research is about and why it matters. One thing that we're very intentional about here at Children's Mercy is we have both parent and youth advisory boards, and so we work with them closely as we develop new research initiatives so that they're at the table and they're also out in the community, in the community, sharing the work that's happening here, because that's in so many ways   00;16;16;09 - 00;16;44;18 far more effective to hear from your neighbors, your friends at work than it is to hear from, you know, those of us who are doing the technical work. Well, kind of same question for those at the basic or fundamental research level, what are their biggest headaches? And, you know, is technology being applied to those headaches? Yeah, I think I wouldn't necessarily call them so much headaches.   00;16;44;18 - 00;17;21;07 But, you know, all categories of research, of course, feel that funding is always a challenge. I think for basic research, the volume of data that many techniques, not all, but many generate, creates an exciting opportunity for people who work in data science. For example, genomic sequencing, you know, is highly automated now, but the volume of data that any one genomic evaluation can generate is massive as well as, you know, very complex.   00;17;21;07 - 00;17;48;14 And so, the informatics and data science opportunities to analyze these growing volume of data is really exciting. Yeah, it feels like even though there are different research stages, there's obviously overlap when it comes to some of the roadblocks and opportunities to knock those roadblocks down. I mean, what do you see as kind of the shared pain points? You mentioned funding, I guess that goes across all stages.   00;17;48;17 - 00;18;27;09 Yeah, I think especially in a clinical setting there, there's a very high focus on cybersecurity. So, the research community is not always as involved in that as they probably needed to be. So, you know, we even have a lot of considerations that we incorporate into making sure that our systems, our data are secure to the highest standards. So that also my team tries to insulate the researchers from that type of work because we want them to be focused on doing science.   00;18;27;09 - 00;18;53;28 And in many organizations, we see researchers who have to get their hands in some of these other processes and technology issues. So a key part of what I see as my role and my team's role is insulating the researchers from those types of concerns. Yeah, which I'm sure they greatly appreciate. Obviously, there is a lot of compute resources that are required.   00;18;54;00 - 00;19;28;24 So, I imagine one of your challenges is to make sure these folks have the kind of compute resources they need. Yeah, and that's really an exciting area. We have recently completed the migration for our Genome Center of their bioinformatics pipeline from an on-premise data center to a completely cloud-based system. And we're excited that we're starting to see that gain of efficiencies from that, you know, moving that to a complete cloud model.   00;19;28;24 - 00;20;01;12 We have other projects that are more of a hybrid model. We do have a data center and our new research institute building. So, I'm excited about the new world where we can really offer computational and storage resources at a totally different scale than was needed ten years ago or even five years ago. Well, I know you're part of the Oracle Research Industry Strategy Council, a group that talked about a lot of the same stuff, pretty recently.   00;20;01;12 - 00;20;24;14 Just this May actually. So, one of the topics of discussion was how some researchers who are federally funded are kind of I don't know if struggling is the right word, but dealing with new policies around data storage and data sharing. The NIH has gotten real serious about those policies earlier this year. Why are these policies like FAIR principles coming down now?   00;20;24;17 - 00;20;56;13 And how ready are researchers to cope with those new protocols? Plus, whatever else may pop up in terms of regulation? Yeah, I think the change in policy reflects a realization on the funders that, you know, despite the expectation that researchers would share all of most of their data that was generated with those taxpayer funds, that that wasn't happening at the consistency level that they expected.   00;20;56;14 - 00;21;33;02 So, the major change this year is that that expectation is articulated much more forcefully. And so now anybody doing federally funded research is expected to make any data that does not include protected health information available to the community. I think some researchers are already doing that. So again, in the genomics world, that's already a fairly common practice. But in other areas it will require some change and different ways of thinking.   00;21;33;04 - 00;22;06;12 I'm not seeing a high level of anxiety or concern about it. I think it's something that we can work through. It's a matter of right sizing the solution. So, we don't want to oversize how we accommodate the new regulations, but we want to make sure that all of our researchers are equipped to be compliant. The reluctance that there is to data sharing is that just concerns about proprietary stuff or researchers are thinking about going to market with this.   00;22;06;12 - 00;22;31;02 And, you know, they want to keep it close to the vest. Sometimes that's the case. I think sometimes it's also academic competitive concerns. So, if you're competing for grant funding with the same people who could download your data, are you giving you know, there's concern that you're giving them, if not a head start, at least the capacity to catch up faster than they otherwise would have.   00;22;31;04 - 00;23;05;04 Does technology help in any way to adhere to these new policies and facilitate that kind of data sharing? I definitely believe it can. There's a variety of portals that can enable researchers to share their data. I think many of these have features that researchers like so that you can track how often your data assets are downloaded. In some cases, you can get a sense for, you know, where are the downloads originating.   00;23;05;07 - 00;23;39;10 What I think will be interesting over the next few years. Right now, in academia, tenure decisions are made based on publications and how often your papers are cited and so forth. I think if we can see a movement towards rewarding, how often is your data downloaded and accessed and utilized and rewarding, you know, academics that do that. I think that will be a real important factor in changing the culture around that.   00;23;39;12 - 00;24;04;28 So, in a couple of past episodes, I actually did ask our guests about this concept of open science that's grounded in FAIR principles. From what I've learned, open science doesn't mean, you know, anything goes, everybody dive in. It's all chaos. There is still scientific rigor. What does open science mean to you? What's open about it and what's still closed about it?   00;24;05;00 - 00;24;48;24 I think data sharing is a key part of open science, you know, and this is where having one foot in technology and one foot in science is helpful because if you look at the open-source software movement, there was very similar cultural resistance to that. But then as people realized that if you put your software code out for the public and they find and fix bugs in that code, that similar process can start to occur with scientific data where maybe there is an inconsistency or maybe there's a pattern in the data that you didn't recognize as, but somebody else does.   00;24;48;27 - 00;25;16;08 So, I think there's a lot to be learned from the process that the open-source software world witnessed and experienced. I think certainly in both cases, putting your either your code or your data out there as a vulnerable feeling for a lot of people. So, helping create a comfort level to get past that vulnerability is really important for the success of both.   00;25;16;08 - 00;25;44;21 But I think when you look at the long-term benefits of open science, I personally believe that the quality of work will go up. And when you pull it back to pediatrics, I think some of the very interesting work in pediatrics revolves around rare disease. And so no single organization is likely to have the numbers of patients with these rare diseases that they can independently gain the insights they need to.   00;25;44;21 - 00;26;13;12 So, collaborating and sharing data is essential for so many areas of pediatric research in particular. Well, for all the acronym fans out there, we talk about FAIR principles. That stands for findability, accessibility, interoperability and reusability. So yeah, I guess on a scale of 1 to 10, how close do you think we are to being FAIR? It'll vary from place to place, but I would just pull a number out of the air.   00;26;13;12 - 00;26;36;29 On average, I would give us a six or seven. Okay, already. Good. But probably going to get better is how I kind of interpret that answer. Yeah. So, one of the guests I pestered with the open science questions was Amy Dockser Marcus of the Wall Street Journal. She wrote a book called, “We The Scientists: How a Daring Team of Parents and Doctors Forged a New Path for Medicine.”   00;26;37;01 - 00;27;10;13 And basically, it's about patient-scientist-doctor collaborations and how that approach could get us to solutions faster. Do you see these collaborations happening? Are doctors and scientists more open to listening to and including patients and their caregivers? Yeah, I'm really seeing, you know, exciting changes in that. I mentioned earlier that we have patient and parent community advisory groups that are increasingly engaged and active in our research strategy.   00;27;10;16 - 00;27;44;14 And it's really shifting from just sometimes those initiatives start with us just telling those groups about what we're doing. But now it's really shifting to how can we do it better and how can we work through these barriers to recruitment, How can we make sure that we're reaching underserved populations? So, I find this whole engagement model to be a really exciting development, and it's really gaining much needed momentum.   00;27;44;16 - 00;28;12;13 And I find it inspiring and motivating to hear, you know, parents of children who have gone through a very difficult health conditions share their stories because that motivates me as well and motivates my colleagues. So, it really is an exciting development that's really picked up momentum. Well, thinking about the technology part, researchers kind of have to figure out what the appropriate tools are and deal with.   00;28;12;14 - 00;28;30;28 Okay, is this data I need and legacy on premises systems or can I get to it in the cloud? And you touched on this a little bit earlier about how you have a cloud solution, but you still also have some hybrid situations. Are you a hybrid guy or do you think all things in the cloud is the way to go?   00;28;30;28 - 00;29;02;13 Which way do you lean? My approach to everything is what are your requirements? And then I will help you fulfill your requirements. And so increasingly we can fulfill many of those requirements with an exclusively cloud-based model. Where it's interesting is that not only are there functional requirements, but there's cost requirements. And so, the hybrid model can often still be delivered with lower cost than a cloud exclusive model.   00;29;02;15 - 00;29;34;06 So, we're trying to be sensitive to the budgetary constraints of especially some of our early career investigators and offer a hybrid model to them as a way to get started without incurring the sometimes high costs of working in any of the major cloud providers. So, everybody in nearly every field that there is thinking about and talking about AI now and how it could change things dramatically.   00;29;34;08 - 00;29;59;06 What are you thinking about AI and machine learning when it comes to scientific research? Is it all positive and will it speed discovery and solutions getting to market? Or are you also waving the caution flag and trying to manage expectations? Because I think about how the combination of open science and it could get really interesting.   00;29;59;09 - 00;30;33;14 Yeah, I currently take a nuanced and cautious stance on AI and machine learning. If you're using those resources for data analysis, I see a lot of value to them. There's so many as we deal with these rapidly growing large datasets, the capacity of our minds to do the pattern recognition is limited. And so, AI and ML are great at pattern recognition in data.   00;30;33;14 - 00;31;24;04 And so, I think as a tool to support data analysis, I'm very positive. I worry more about the application and clinical practice of AI. I mean, being a member of the Ethical AI Initiative of the Center for Practical Bioethics in Kansas City, and I'm very impressed with the approach that they take and they deliver a workshop that is focused on if you're either buying a system that reports to be AI enabled or building something, what are the variety of ethical considerations that you should be considering?   00;31;24;06 - 00;31;55;11 And a particular area of concern is around health equity. And because we know that so many of these systems are trained on data sets that are skewed towards non-diverse populations. So, if that's what you're training these models with, and they will reinforce the inequities in health care. So, I think for some of those larger scale applications, we need to have a deliberate, careful and intentional approach.   00;31;55;13 - 00;32;22;24 It's not to say that there won't be positive uses of AI and ML, but I do think as we get closer to patient facing application, we need to be more intentional and more deliberate. Well, I want to be in a really good mood for the rest of the day, so could you tell us about research that's going on right now at Children's Mercy and some things that you're particularly excited about?   00;32;22;27 - 00;32;59;02 Yeah, and again, as I mentioned earlier, I really enjoy and thrive on the variety of work here. So I'm fortunate to collaborate, for example, with Dr. Bridgette Jones, who does research on health disparity and asthma. I'm fortunate to work with our Genome Center for Genomic Medicine, where they have a very large community facing project called Genomic Answers for Kids and focused on identifying the genetic basis for rare diseases.   00;32;59;05 - 00;33;28;23 I'm fortunate to collaborate with a wide group of experts on some of my own research where we use large de-identified clinical data from Oracle Health. So, two recent things we evaluated were how often and this is at a national level, are youth and young adults who present in the emergency room with a migraine, how often are they treated with an opioid?   00;33;28;25 - 00;33;59;29 The ideal would be 0 to 2%. We noticed that more than 20% of those youth and young adults nationally are treated with an opioid. So that type of research can then lend to process changes that challenge providers to reflect on their ordering patterns. So, the variety of really exciting research that we do at Children's Mercy is just something that excites me a lot.   00;34;00;03 - 00;34;32;15 Yeah, and on the genomics side, how close are we to, you know, all the exciting articles we read about the entire genome being mapped to the extent that we can go on and find the marker that is causing this rare disease and switch it off. Well, the very last part is where things get hard. But we've made huge strides in the recognition of the genetic basis for different rare health conditions.   00;34;32;18 - 00;35;09;01 Sometimes just finding that can lead to the realization that it's similar to a condition that presents differently but has a treatment available. And then you can try that medication on the patient with that genetic variant. And so those are the initial successes. I think the gene therapy type interventions that you might be alluding to, they're starting to regain some momentum, but that's going to be a long process.   00;35;09;04 - 00;35;42;17 So do you think people like me who just ask the question that I asked have over or heightened expectations? It's like, what is that balance between where the public thinks we should be and where actual research really is? Yeah, I think and that gets back to the even some of the societal topics that we were touching on earlier, where on the one hand there's elements of society that want research to move faster and to do more.   00;35;42;19 - 00;36;19;15 And then there's other elements that are much more of the go slow. And so, again, as a scientific community, finding that right balance and how we communicate about our work is really critical. And it's something that we really need to put an increased focus on to, you know, on the one hand, make sure that the advances that are complete and ready are utilized, which, you know, we all want that and that the emerging advances that people are participating in studies that they know that it is safe to participate in studies.   00;36;19;17 - 00;36;46;16 And then when the results of those studies are completed, that they're comfortable utilizing the output of that research. Well, for the last question, we'll stick with that societal aspect. You are an Oracle Council member, so you already know this, but Oracle believes that for the good of global health and humanity, we must understand and serve the needs of research and researchers at every level.   00;36;46;18 - 00;37;13;10 And it feels like we're facing bigger things like food security, disease prevention. Nobody needs another pandemic. What's your view on how research is only going to get more vital? And the pressure on research is only going to go up for kind of holding the earth and the species together? Yeah, that's a great question. And I am an optimist about research.   00;37;13;10 - 00;37;47;13 I believe that the work we do in research matters to the public and to the world. The examples you gave of food security, climate change, pandemics are all the, you know, major emerging concerns that all types of research are going to play a role in the solutions to those problems. And then I would pull us back to the question of how different would things have been if the pandemic had been ten years ago.   00;37;47;13 - 00;38;23;03 And to me, the research into many vaccines and rapid molecular diagnostics, those are all things that made the response to the pandemic. What it was, again, far from perfect, but much more effective than it would have been ten years ago were it not for all of the research that supported those developments. And I think that same mindset would apply to the other large scale problems and challenges that you mentioned.   00;38;23;05 - 00;38;44;00 Dr. Hoffman, thank you again for joining us today. You know, a lot of times our listeners will want to learn more about what you talked about or even get in touch with you. Is there any way they can do that? Sure. I'm on Twitter at Mark Hoffman K.C. I'm also on LinkedIn and my bio is available on the Children's Mercy website.   00;38;44;03 - 00;40;56;11 Great. We appreciate that. If you are interested in how Oracle can simplify and accelerate your research, you can check out Oracle dot com slash research. 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