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Predictive Toxicology | Combining in vitro and in silico Techniques in Predictive Toxicology Applications
InterAction Meeting Session, Bryn Mawr, Philadelphia, USA
Thursday October 15 and Friday October 16, 2009
Co-Chaired by Richard Judson (US EPA) and Vladimir Poroikov (Institute of Biomedical Chemistry of Russian Academy of Medical Sciences)
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Significant advances are being made in the use of in vitro and in silico techniques to understand and ultimately predict the toxicity of pharmaceutical and industrial chemicals. This session will present a series of talks addressing the use of in vitro screening using cell-based and cell-free techniques, and in silico approaches including QSAR modeling, data mining from growing public sources, pharmacokinetic modeling and pathway-based analysis. Presentations and discussions will focus on practical applications of the methodologies discussed and potential advances and ways forward through development of innovative and effective combinations of in vitro and in silico techniques.
Presenters & Discussions Leaders
Anil Aswani (University of California at Berkeley), A Network-Level Approach to Predictive Toxicology Abstract & Bio....
Ellen Berg (Bioseek), Defining Chemical Target and Pathway Toxicity Mechanisms with Primary Human Cell Systems Abstract & Bio....
Sanji Bhal (ACD/Labs, Inc.), Applications of GALAS Modeling Methodology for the Prediction of Drug Safety Related Properties. Evaluation and Expansion of the Model Applicability Domain Abstract & Bio....
Stephen Bryant (NIH), Toxicology Data Sets in PubChem Abstract & Bio....
Peter Elkin (Mount Sinai School of Medicine, New York), eQuality for All: Extending Automated Quality Measurement of Free Text Clinical Narratives Abstract & Bio....
Christodoulos Floudas (Princeton University), Predicting in vivo Toxicities using Optimal Methods for Re-ordering and Logistic Regression Abstract & Bio....
Robert Fraczkiewicz (Simulations Plus), Modeling Rat Liver Toxicity Signature Using Machine Learning Techniques Abstract & Bio....
Barry Hardy (Douglas Connect), Integrated Predictive Toxicology Application Development Abstract & Bio....
Richard Judson (US EPA), High Throughput Screening of Toxicity Pathways Perturbed by Environmental Chemicals Abstract & Bio....
Fangping Mu (Los Alamos National Laboratory), Computational Xenobiotics Metabolism Prediction System Abstract & Bio....
Kyoung Tai No (Yonsei University), In Silico Prediction of Drug Metabolism in the Liver Abstract & Bio....
Grace Patlewicz (DuPont), Read-across – a Data Gap Filling Technique – Help or Hindrance? A Practical Perspective Abstract & Bio....
Michael Pelekis (Simulations Plus), Not Just 'If' or 'Where', but Also 'How Fast' – Predictive Modeling of Kinetic Constants for CYP-Mediated Metabolism Abstract & Bio....
Vladimir Poroikov (Institute of Biomedical Chemistry of Russian Academy of Medical Sciences), QSAR Modeling of Toxicity: Comparison of Pharmaceutical and Industrial Chemicals Abstract & Bio....
Katya Tsaioun (Apredica), In vitro Models that Predict Major Known Mechanisms of Human Toxicity. Validation, Case Studies and Path Forward
Abstract & Bio....
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Discussion Topics
1. High throughput in vitro screening for predictive toxicology; the ToxCast project
2. Predictive Metabolism / Biotransformation using in silico and in vitro methods
Issues
i. Why is this an issue ?– most in vitro systems don’t do this
ii. What fraction of chemicals are biotransformed?
iii. Possibility of activation and deactivation
iv. Many possible metabolites – need to predict abundance and rates
v. What HTS data can be used to help?
3. Predictive Pharmacokinetics
Issues
i. Need to predict metabolism, absorption and distribution
ii. PBPK models
iii. Link between models and in vitro data
4. QSAR Modeling of Toxicity
Issues
i. Where can we expect success and where not?
ii. Chemical domain issues
iii. Pharmaceuticals vs. industrial chemicals
iv. What endpoints are used for anchoring of models?
5. Pathway-based modeling of toxicity
Issues
i. Need to understand link between pathway and not just target effects of chemicals and their toxicity
ii. Leverage wealth of information from the human genome project
iii. Many cell-based assays really probe pathways and not single targets
6. Novel Cell-based and model organism systems for specific endpoints
a. Issues
i. There are good cell-models or assays for certain endpoints (cancer, ion-channel issues) but a dearth for others
b. Potential examples
i. Developmental – stem cells, zebra fish
ii. Cancer – cell lines, read outs
iii. Inflammation
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