Computational Toxicology

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It integrates data from various sources, including molecular biology, chemistry, and pharmacology, to develop predictive models for assessing the toxicity of substances.</div><div><a href="https://toxicology.blog/knowledgebase/why-is-computational-toxicology-important" title="Why is Computational Toxicology Important?"><h3>Why is Computational Toxicology Important?</h3></a>Traditional toxicological methods involve extensive <a href="https://toxicology.blog/about/index/animal-testing" title="animal testing" target="_blank">animal testing</a> and in vitro experiments, which can be time-consuming, costly, and ethically challenging. Computational toxicology offers an alternative by providing quicker, more cost-effective, and humane approaches to toxicity assessment. It helps in the early identification of potentially hazardous chemicals, thus enhancing <a href="https://toxicology.blog/about/index/public-health" title="public health" target="_blank">public health</a> and <a href="https://toxicology.blog/about/index/environmental-safety" title="environmental safety" target="_blank">environmental safety</a>.</div><div><a href="https://toxicology.blog/knowledgebase/what-are-the-key-components-of-computational-toxicology" title="What are the Key Components of Computational Toxicology?"><h3>What are the Key Components of Computational Toxicology?</h3></a>Computational toxicology encompasses several key components:</div><div> <a href="https://toxicology.blog/about/index/data-integration" title="Data Integration" target="_blank">Data Integration</a>: Combining data from various sources such as genomics, proteomics, and chemical properties.<br> <a href="https://toxicology.blog/about/index/predictive-modeling" title="Predictive Modeling" target="_blank">Predictive Modeling</a>: Developing computational models to predict the toxicity of chemicals.<br> <a href="https://toxicology.blog/about/index/bioinformatics" title="Bioinformatics" target="_blank">Bioinformatics</a>: Analyzing biological data using computational tools.<br> <a href="https://toxicology.blog/about/index/cheminformatics" title="Cheminformatics" target="_blank">Cheminformatics</a>: Applying computational techniques to chemical data to predict toxicological properties.</div><div><a href="https://toxicology.blog/knowledgebase/how-are-predictive-models-developed" title="How are Predictive Models Developed?"><h3>How are Predictive Models Developed?</h3></a>Predictive models in computational toxicology are developed using various machine learning and statistical techniques. These models are trained on large datasets containing information about known toxic and non-toxic chemicals. Features such as molecular structure, physicochemical properties, and biological interactions are used to train these models. Techniques like <a href="https://toxicology.blog/about/index/quantitative-structure-activity-relationship-(qsar)-models" title="Quantitative Structure-Activity Relationship (QSAR) models" target="_blank">Quantitative Structure-Activity Relationship (QSAR) models</a>, <a href="https://toxicology.blog/about/index/neural-networks" title="neural networks" target="_blank">neural networks</a>, and <a href="https://toxicology.blog/about/index/support-vector-machines" title="support vector machines" target="_blank">support vector machines</a> are commonly employed.</div><div><a href="https://toxicology.blog/knowledgebase/what-are-the-applications-of-computational-toxicology" title="What are the Applications of Computational Toxicology?"><h3>What are the Applications of Computational Toxicology?</h3></a>Computational toxicology has a wide range of applications:</div><div> <a href="https://toxicology.blog/about/index/drug-development" title="Drug Development" target="_blank">Drug Development</a>: Identifying potential toxicities of drug candidates early in the development process.<br> <a href="https://toxicology.blog/about/index/environmental-risk-assessment" title="Environmental Risk Assessment" target="_blank">Environmental Risk Assessment</a>: Assessing the impact of chemicals on ecosystems.<br> <a href="https://toxicology.blog/about/index/regulatory-toxicology" title="Regulatory Toxicology" target="_blank">Regulatory Toxicology</a>: Supporting regulatory agencies in evaluating chemical safety.<br> <a href="https://toxicology.blog/about/index/personalized-medicine" title="Personalized Medicine" target="_blank">Personalized Medicine</a>: Understanding individual variability in response to toxic substances.</div><div><a href="https://toxicology.blog/knowledgebase/what-are-the-challenges-in-computational-toxicology" title="What are the Challenges in Computational Toxicology?"><h3>What are the Challenges in Computational Toxicology?</h3></a>Despite its potential, computational toxicology faces several challenges:</div><div> <a href="https://toxicology.blog/about/index/data-quality" title="Data Quality" target="_blank">Data Quality</a>: Ensuring the accuracy and reliability of data used in models.<br> <a href="https://toxicology.blog/about/index/model-validation" title="Model Validation" target="_blank">Model Validation</a>: Validating predictive models to ensure their applicability and robustness.<br> <a href="https://toxicology.blog/about/index/interdisciplinary-collaboration" title="Interdisciplinary Collaboration" target="_blank">Interdisciplinary Collaboration</a>: Coordinating efforts among experts from different fields.<br> <a href="https://toxicology.blog/about/index/ethical-concerns" title="Ethical Concerns" target="_blank">Ethical Concerns</a>: Addressing ethical issues related to data privacy and the use of animal data.</div><div><h3>Future Directions in Computational Toxicology</h3>The future of computational toxicology is promising, with ongoing advancements in computational power, machine learning algorithms, and data availability. Emerging technologies like <a href="https://toxicology.blog/about/index/artificial-intelligence-(ai)" title="artificial intelligence (AI)" target="_blank">artificial intelligence (AI)</a> and <a href="https://toxicology.blog/about/index/big-data" title="big data" target="_blank">big data</a> analytics are expected to further enhance the predictive capabilities of computational toxicology. Additionally, increasing emphasis on <a href="https://toxicology.blog/about/index/green-chemistry" title="green chemistry" target="_blank">green chemistry</a> and sustainable practices will drive the adoption of computational methods in toxicity assessment.</div></div> </div> <div id="recent_papers"> <br><hr /><br><h2 class="heading1">Relevant Publications</h2> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38810721" target='_blank' title="Toward structure-multiple activity relationships (SMARts) using computational approaches: A polypharmacological perspective.">Toward structure-multiple activity relationships (SMARts) using computational approaches: A polypharmacological perspective.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38752675" target='_blank' title="An automated computational data pipeline to rapidly acquire, score, and rank toxicological data for ecological hazard assessment.">An automated computational data pipeline to rapidly acquire, score, and rank toxicological data for ecological hazard assessment.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38199258" target='_blank' title="The comprehensive prediction of carcinogenic potency and tumorigenic dose (TD) for two problematic N-nitrosamines in food: NMAMPA and NMAMBA using toxicology in silico methods.">The comprehensive prediction of carcinogenic potency and tumorigenic dose (TD) for two problematic N-nitrosamines in food: NMAMPA and NMAMBA using toxicology in silico methods.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38223665" target='_blank' title="Efficiency of pharmaceutical toxicity prediction in computational toxicology.">Efficiency of pharmaceutical toxicity prediction in computational toxicology.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38524439" target='_blank' title="Machine Learning Models for Prediction of Xenobiotic Chemicals with High Propensity to Transfer into Human Milk.">Machine Learning Models for Prediction of Xenobiotic Chemicals with High Propensity to Transfer into Human Milk.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38593686" target='_blank' title="Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.">Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38548154" target='_blank' title="Mechanistic insight into biotransformation of novel triazine-based flame retardant 1,3,5-Tris(2,3-Dibromopropyl)-1,3,5-triazinane-2,4,6-trione by human cytochrome P450s.">Mechanistic insight into biotransformation of novel triazine-based flame retardant 1,3,5-Tris(2,3-Dibromopropyl)-1,3,5-triazinane-2,4,6-trione by human cytochrome P450s.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38627326" target='_blank' title="The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.">The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/39091793" target='_blank' title="Deep Learning-based Modeling for Preclinical Drug Safety Assessment.">Deep Learning-based Modeling for Preclinical Drug Safety Assessment.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/39134399" target='_blank' title="Physiologically-based pharmacokinetic model of in vitro porcine ear skin permeation for drug delivery research.">Physiologically-based pharmacokinetic model of in vitro porcine ear skin permeation for drug delivery research.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/39128516" target='_blank' title="Identifying the toxic mechanisms of emerging electronic contaminations liquid crystal monomers and the construction of a priority control list for graded control.">Identifying the toxic mechanisms of emerging electronic contaminations liquid crystal monomers and the construction of a priority control list for graded control.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38591687" target='_blank' title="Molecular modeling of the carbohydrate corona formation on a polyvinyl chloride nanoparticle and its impact on the adhesion to lipid bilayers.">Molecular modeling of the carbohydrate corona formation on a polyvinyl chloride nanoparticle and its impact on the adhesion to lipid bilayers.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38415890" target='_blank' title="In Silico Acute Aquatic Hazard Assessment and Prioritization Using a Grouped Target Site Model: A Case Study of Organic Substances Reported in Permian Basin Hydraulic Fracturing Operations.">In Silico Acute Aquatic Hazard Assessment and Prioritization Using a Grouped Target Site Model: A Case Study of Organic Substances Reported in Permian Basin Hydraulic Fracturing Operations.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38467999" target='_blank' title="Machine learning-based models to predict aquatic ecological risk for engineered nanoparticles: using hazard concentration for 5% of species as an endpoint.">Machine learning-based models to predict aquatic ecological risk for engineered nanoparticles: using hazard concentration for 5% of species as an endpoint.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38503103" target='_blank' title="Association of phthalate exposure with type 2 diabetes and the mediating effect of oxidative stress: A case-control and computational toxicology study.">Association of phthalate exposure with type 2 diabetes and the mediating effect of oxidative stress: A case-control and computational toxicology study.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38722351" target='_blank' title="Synergistic Activity of Noble Trimetallic Nanofluids: Unveiling Unprecedented Antimicrobial Potential and Computational Insights.">Synergistic Activity of Noble Trimetallic Nanofluids: Unveiling Unprecedented Antimicrobial Potential and Computational Insights.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38745696" target='_blank' title="A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.">A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38874513" target='_blank' title="Prediction of the Liver Safety Profile of a First-in-Class Myeloperoxidase Inhibitor Using Quantitative Systems Toxicology Modeling.">Prediction of the Liver Safety Profile of a First-in-Class Myeloperoxidase Inhibitor Using Quantitative Systems Toxicology Modeling.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/38857761" target='_blank' title="Preface to the Special Issue of Food and Chemical Toxicology on \"New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century\".">Preface to the Special Issue of Food and Chemical Toxicology on \"New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century\".</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> <div class='publication-block'> <div style='margin-bottom: 10px;line-height: 24px;'> <a href="https://pubmed.ncbi.nlm.nih.gov/39049896" target='_blank' title="Oxidation Mechanism and Toxicity Evolution of Linalool, a Typical Indoor Volatile Chemical Product.">Oxidation Mechanism and Toxicity Evolution of Linalool, a Typical Indoor Volatile Chemical Product.</a> </div> <p><strong>Issue Release:</strong> 2024</p> </div> </div> </div> <div id="way2buy_left_banner_1" class="rightads"></div> </div> <div class="col-md-4 mt-50"> <style> .qa-container1 { width: 100%; max-width: 800px; text-align: left; } .qa-item1 { margin: 10px 0; border-bottom: 1px solid #e5e5e5; padding-bottom: 16px; } .qa-item1 a { text-decoration: none; color: #000; font-size: 15px; font-weight: bold; font-weight: 500 !important; } 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