HOME- Bryn Mawr Conference
- Workshops & Training
- 2010 Oxford (Discovery)
- 2010 Oxford (ADMET)
- Hardy, B
- Hardy, L
- Jeliazkova, N
- Judson, R
- Leahy, D
- Li, J
- Myatt, G
- Rydberg, P
- Tsaioun, K
- Wiseman, J
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- 2009 Oxford (Discovery)
- 2009 Oxford (ADMET)
- 2008 Oxford
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| About Richard Judson (U.S. Environmental Protection Agency) |
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Dr. Judson is with the EPA National Center for Computational Toxicology where he is developing databases and computer applications to predict and model toxicological effects of a wide range of chemicals. He is a member of the EPA ToxCast team where he leads the bioinformatics efforts. His team has developed the ACToR (Aggregated Computational Toxicology Resource) database and application which is compiling all publicly available data on environmental chemicals. Prior to joining the EPA, Dr. Judson was founder of GAMA BioConsulting, a bioinformatics consulting company. From 1999-2006, Dr. Judson was Senior Vice President and Chief Scientific Officer with Genaissance Pharmaceuticals. Prior assignments included CuraGen from 1997-1998 and Sandia National Laboratories from 1990-1996. Dr. Judson has a BA in Chemistry and Chemical Physics from Rice University and an MA and PhD in Chemistry from Princeton University.
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Building and Testing Mechanism-Based Models of Chemical Toxicity using Data from the U.S. EPA ToxCast Program
Richard Judson (U.S. EPA, National Center for Computational Toxicology)
The U.S. EPA ToxCast program is using in vitro assay data and chemical descriptors to build predictive models for in vivo toxicity endpoints. In vitro assays measure activity of chemicals against molecular targets such as enzymes and receptors (measured in cell-free and cell-based systems in binding, agonist and antagonist modes), in addition to cellular phenotypes and pharmacokinetic-related parameters. Over 600 separate assays were run in concentration response format to derive AC50 or LEC values for each chemical-assay combination. This collection of data are being used to build predictors of in vivo toxicity endpoints derived from chronic/carcinogenicity studies in rats and mice, prenatal developmental toxicity studies in rats and rabbits, and two-generation reproduction studies in rats. The models use both raw assay data as inputs, but also derived parameters such as pathway and disease perturbation scores that summarize chemical activity across either published pathways or disease-gene collections. Also used are combinations of potency data (concentrations at which chemical activity turns on) and efficacy (magnitude of effect), plus variance around mean estimates. This session will show how to interpret the ToxCast data and how to use the data to build signatures of endpoints including liver tumors, cleft palate and reproductive fitness. Users will run simple models and learn to judge the value of the models in terms of specificity, sensitivity and other statistical metrics, and how to balance statistical and biological merits. These models are put into the context of prioritization for further testing, and initial prioritization plans will be discussed. The example analyses will be carried out using a set of R functions, but no R programming experience is necessary.
Additionally, we will show how the in vitro assay data can be fit into an open source ontology that allows for integration into the OpenTox Framework. This will allow participants to use this information for their own case study projects to explore different modeling strategies.
This work may not necessarily reflect official Agency policy.
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