This two day hybrid workshop will introduce attendees to a variety of computational methods and approaches to assess health risks arising from exposure to toxic chemicals. Existing toxicological methods are often insufficient to test ever growing lists of new chemicals. The development of computational strategies using high-throughput in vitro and in vivo toxicology data is a powerful approach to predict the potential health risks of chemicals that have not been fully tested in the laboratory or in experimental animals.
By the end of the workshop, participants will be familiar with the following topics:
- How best to curve fit and display cytotoxicity data
- How to create highly dimensional and informative data visualizations
- The EPA’s CompTox dashboard and database
- ToxPi: the Toxicological Prioritization Index (ToxPi) framework
- How to interpolate and extrapolate human exposure risk across multiple data sources and techniques
- How to find and choose relevant databases and repositories of high-throughput toxicological data and navigate their interfaces.
- Statistical techniques to analyze chemical mixtures and their relationships to health outcomes
Audience & Requirements
Grad/PhD students, early-state investigators, and established PI’s at all career stages are welcome. We particularly encourage trainees and early-stage investigators to participate, as well as those who want a basic overview of computational toxicology. Other requirements include: