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Computational Toxicology Research

Communities of Practice

  • Expand ToxCast™ and determine a prospective assessment of the approach using chemicals currently entering a traditional testing process.
  • Create a consolidated EPA exposure database focused on measured concentrations in exposure and biological media.
  • Provide recommendations on the standards for exposure data representation.
  • Recommend approaches for improving accessibility to EPA human exposure data and for facilitating links between exposure and toxicity data.
  • Discuss novel approaches for characterizing exposure to prioritize chemicals.

EPA's Computational Toxicology Communities of Practice is composed of more than 300 people from over 50 public and private sector organizations who have an interest in encouraging computational toxicology usage and exposure science in helping to implement EPA's mission of protecting human health and the environment. Anyone can join the Communities of Practice and members include staff from EPA, other federal agencies, industry, academic institutions, professional societies, nongovernmental organizations, environmental non-profit groups, state environmental agencies and more.

Monthly meetings are held at EPA's RTP campus, on the fourth Thursday of the month, from 11am-Noon EST/EDT. Teleconferencing is available.

For more information or to be added to the meeting email list, contact Monica Linnenbrink at linnenbrink.monica@epa.gov or (919) 541-1522.

Goals:

  • Develop key partnerships and collaborations with external groups that can facilitate the development of computational tools and exposure information needed to inform chemical prioritization.
  • Review and provide expertise about the chemicals, assays, key target toxicities, data domains for ToxCast™ and how to incorporate chemical exposure into ToxCast™'s chemical screening project. 
  • Identify research needed to improve EPA's computational resources for addressing exposure screening and chemical prioritization.
  • Determine the impact of metabolizing capability, or lack thereof, on the efficiency of the screening assays.
  • Develop a bioinformatic approach to mining the resulting data and identifying signatures of concern.
  • Report the utility of assay results and analysis techniques to categorize pilot chemicals according to known toxicity patterns; revise methods and approaches as dictated by results.

Computational Toxicology Presentation Files

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