BioTechX Europe recap: Trends, innovations, and insights

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This year’s BioTechX conference took place on 9-10 October in Basel, the pharma hub of Europe. The event centered around data and AI for driving precision and innovation in pharma and healthcare, converging 3500 global executives, 400 speakers and 50 start-ups under one roof.</span></p> <p><span style="font-weight: 400;">With 16 different tracks, the conference topics covered everything from the management of multiomic data to the digital revolution in pharmaceutical development and the future of personalized medicine. This provided a fertile ground for engaging discussions and collaboration. Ardigen is a proud sponsor of BioTechX Europe and we are thrilled to contribute to fostering such an innovative community of interdisciplinary researchers and top companies. Here are some conference takeaways we want to share with you.</span></p> <h2><b>Healthcare will become more accessible with AI</b></h2> <p><span style="font-weight: 400;">It is no secret that AI is transforming clinical research and propelling the advancement of personalized medicine, but the challenge is making sure that those innovations can be transferred broadly to wide populations. The Keynote Panel Discussion with Sam Khalil (Vice President of Data Insights, Novo Nordisk), Robert McGregor (Tech Platform Head, Clinical Operations, Novartis) and Alexander Krupp (Innovation Lead, Clinical Development and Operations, Bayer) titled “Driving Clinical Development for Affordable Care” focused on addressing the challenge of healthcare accessibility.</span></p> <p><span style="font-weight: 400;">Cost remains one of the main challenges of drug development. Because of that, conditions that affect only small groups of people often lack treatment options. According to the panelists, the effective integration of AI can help reduce the cost of drug development in several ways, including enhancing data analysis and biomarker discovery, doing predictive modeling for personalized treatment, as well as facilitating adaptive clinical trial designs that ensures that diverse populations are represented and also minimizes the cost of trials.</span></p> <p><span style="font-weight: 400;">As Alexander Krupp put it: “As an industry, we really need to step up in our ambition. And that means we don’t need to incrementally improve the way we bring medicines to market. If we reduce the cost of innovation from three billion to just 300 million, that’s not going to change the game. If we reduce it to 30 million, maybe. If we reduce it to three million, so by a factor of 1,000, if we manage doing that, we can bring medications to underserved patients.”</span></p> </div> </div> <div class="container"> <div class="tc-images-row"> <div class="tc-images-row-flex"> <div class="tc-images-row-flex-item"> <div class="tc-images-row-item"> <img src="https://ardigen.com/wp-content/uploads/2024/10/Untitled-presentation.jpg" alt=""> </div> </div> </div> </div> </div> <div class="container"> <div class="tc-simple-chapter" style="overflow: hidden"> <h2><b>The key to success is using data effectively</b></h2> <p><span style="font-weight: 400;">One of the treads that ran through many of the conference discussions was that optimized use of data remains a key for success. Alexander Krupp noted that Bayer placed the emphasis on the secondary use of data that revolves around addressing the pain points of the organization, rather than simply placing all the data in a data lakehouse. This approach helps the company tackle some of the main challenges in the clinical data space, such as improving access to data, ensuring seamless governance, promoting a collaborative environment and making access to AI tools easy.</span></p> <p><span style="font-weight: 400;">Utilizing data efficiently can be done in multiple ways. The first one is by using AI tools to extract insights from it. Machine learning models are very effective at finding “the needle in the haystack”. Therefore, they can help researchers to more deeply understand the patient population, epidemiology, as well as the current standard of care, and treatment guidelines to design more effective methods. </span></p> <p><span style="font-weight: 400;">The second way is to utilize publicly available unstructured information. This can help researchers inform the design of clinical trials and design smaller-scale trials that require less resources to execute and deliver the same statistical powers. As clinical trials are still one of the most costly steps of drug development, companies should focus on optimizing this step to bring down the costs of therapies.</span></p> <h2><b>Scaling AI solutions remains a challenge for organizations</b></h2> <p><span style="font-weight: 400;">For many companies, dealing with the large amounts of data that AI solutions require remains a challenge. Scaling up data infrastructures requires specialized knowledge, especially when it comes to often-overlooked things like operations data. Robert McGregor gave an example of how Novartis focuses its efforts on a specific user group that needs to solve a very specific question. To do so effectively, his team brings insights from multiple systems and combines them to provide actionable information for planning operations: “That allows us to stay reactive and to stay ahead of the curve,” he said.</span></p> <h2><b>Bringing in real-world evidence will deliver additional impact</b></h2> <p><span style="font-weight: 400;">In his short talk, Patrick Loerch, Senior Vice President, Clinical Data Science at Gilead, highlighted the value of incorporating real-world evidence base into medical research. Patient records, for example, hold a wealth of data that can now be fully tapped into thanks to the shift from manual to electronic chart extraction in the pharmaceutical industry. As an example, Loerch used a recent study where researchers tested ChatGPT on oncology charts. The model was able to extract data features with 80% accuracy. But because AI can provide the results within minutes and at a fraction of the cost (around $10), it provides an opportunity to process the charts of hundreds of patients and extract powerful, population-scale insights.</span></p> <h2><b>Bringing in healthcare transformation together</b></h2> <p><span style="font-weight: 400;">It is no accident that BiotechX Europe has secured its spot as one of the biggest gatherings of researchers and innovators working to transform healthcare. This year’s conference was an outstanding event, full of insightful discussions and community building. This is the reason why Ardigen keeps coming back to this conference every year.</span></p> <p><span style="font-weight: 400;">As the BioTechX website states, “We have to work together in an interdisciplinary manner, also across borders of any kind.” Ardigen embodies that ethos in everything we do: from building a world-class team of multi-disciplinary experts to the diversity of partners we serve. 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