Research Grants/Fellowships/SBIR

Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments

EPA Grant Number: R835166
Title: Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments
Investigators: Rusyn, Ivan , Tropsha, Alex , Wright, Fred A.
Current Investigators: Rusyn, Ivan , Chiu, Weihsueh , Tropsha, Alex , Wright, Fred A.
Institution: University of North Carolina at Chapel Hill
Current Institution: Texas A & M University , North Carolina State University
EPA Project Officer: Klieforth, Barbara I
Project Period: July 1, 2012 through June 30, 2016
Project Amount: $1,200,000
RFA: Developing High-Throughput Assays for Predictive Modeling of Reproductive and Developmental Toxicity Modulated Through the Endocrine System or Pertinent Pathways in Humans and Species Relevant to Ecological Risk Assessment (2011) RFA Text |  Recipients Lists
Research Category: Computational Toxicology , Health , Ecosystems , Safer Chemicals

Objective:

The Carolina Center for Computational Toxicology (Center for Computational Toxicology Exit) is a broad, interdisciplinary partnership with a mission to devise novel experimental approaches and computational tools/methods with direct relevance to EPA’s research and regulatory objectives. We will continue our productive research in support of Tox21 and NexGen by focusing on the following Objectives: (1) Develop a quantitative high-throughput screening (qHTS) approach to probe differential chemical effects in a population-based in vitro system; (2) Provide the computational toxicology solutions for risk characterization in NexGen assessments with a focus on point-of-departure and population variability; and (3) Develop cheminformatics-based, as well as enhanced chemical-biological, models of in vivo reproductive and developmental toxicity that rely on concomitant exploration of chemical descriptors and population-based screening data.

Approach:

The Center has a demonstrated track-record of developing predictive modeling solutions highly relevant to NexGen and Tox21 programs. Under Objective 1, we will perform qHTS experiments using a panel of 1000+ genetically diverse/defined human lymphoblast cell lines representative of 9 human populations. We will collect concentration-response cytotoxicity data on hundreds of chemicals selected for EPA’s endocrine-disruption screening program 21 (ESDP21). Under Objective 2, we will use qHTS data from Objective 1 and publicly available genotyping and gene expression data to define pathways that may be responsible for differential sensitivity of human cell lines with an emphasis on the endocrine-disruption and other chemicalperturbed pathways. Also, we will utilize our expertise in toxicology, risk assessment, statistics and modeling and develop prototype examples of chemical prioritization and evaluation in the tiered NexGen assessments. Under Objective 3, using historical data, we will build rigorous QSAR as well as chemical-biological models for compounds known to bind or activate several major steroid and hormone receptors implicated in reproductive/developmental toxicity. In addition, using data from Objective 1, we will develop models of reproductive/developmental toxicity by taking into account population diversity and, pathway information from Objective 2.

Expected Results:

The Center will develop new methods and tools, and will continue to collaborate closely with EPA, Tox21 and other environmental scientists. New in vitro populationbased assays and computer-based models that fill critical gaps in risk assessment will be developed and delivered. The emphasis will be placed on their usability by the risk assessment community and the investigative toxicologists alike. The synthesis of data from a variety of sources will move the field of computational toxicology from a hypothesis-driven toward predictive science.

Publications and Presentations:

Publications have been submitted on this project: View all 27 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 16 journal articles for this project

Progress and Final Reports:

2013 Progress Report
2014 Progress Report
2015 Progress Report