| Project Number: |
NCCT-09-05 |
| Location: |
| Research Triangle Park, NC |
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| Title of Project: |
Chemical Structure Classifiers and Approaches for Toxicity Prediction in ToxCast™ |
| Brief Description of Research Project: |
This post doctoral associate will work in conjunction with the ToxCast™ and Tox21 research projects to develop novel methods for chemical classification and toxicity prediction. ToxCast™ is generating a high-throughput screening (HTS) data base for hundreds to thousands of chemicals in hundreds of biochemical, cell-based, and model organism assays. Tox21 is a collaboration between EPA, NTP (National Toxicology Program), and NCGC (NIH Chemical Genomics Center) that is generating HTS data for a larger set of upwards of 10,000 compounds of environmental interest in an expansion of the ToxCast™ paradigm.
Initial modeling efforts are focused on developing predictive toxicity signatures relating HTS results to reference in vivo toxicity endpoints. A key requirement to the success of such efforts will be the integration of chemical clustering concepts based on chemical properties, reactivity and metabolism, with biologically-informed clustering derived from toxicity, mechanistic and HTS data.
A key difference in this approach from traditional structure-activity relationship approaches is the explicit incorporation of HTS biological data in guiding selection of chemical classes, and refinement of traditional chemistry-based classes based on biological data. We envision a layered approach whereby chemical classifications are flexible and tailored to the compound and biological activity space under consideration. This research will take advantage of data mining approaches and informatics methods being developed within and outside the NCCT.
The associate will develop and apply these methods to both the ToxCast™ and larger Tox21 chemical sets, in order to refine toxicity predictions for chemicals and chemical classes and support chemical prioritization for more extensive toxicity testing. |
| High Priority Research Area: |
Computational Toxicology |
| Projected duration of appointment: |
3 years; with option to extend up to 4 years. |
| Educational requirements: |
Ph.D. in chemistry, biochemistry, computational sciences or related fields. |
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| Specialized training and/or experience preferred: |
Strong interest in modeling the relationship of chemicals, and their structure and properties, to biological endpoints, particularly pertaining to environmental toxicology. Expertise in computational chemistry and computer programming is highly desirable, as is some knowledge of statistical methods, informatics, and biology. Oral communication and written presentation skills are also desirable. |
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| Scientific contact/Principal Investigator* |
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