You are here:
High Information Content Toxicity Screening Using Mouse and Human Stem Cell Models of Endocrine Development and FunctionEPA Grant Number: R835163
Title: High Information Content Toxicity Screening Using Mouse and Human Stem Cell Models of Endocrine Development and Function
Investigators: Finnell, Richard H.
Institution: The University of Texas at Austin
EPA Project Officer: Klieforth, Barbara I
Project Period: March 1, 2012 through February 28, 2015
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 , Endocrine Disruptors , Health , Ecosystems , Safer Chemicals
The primary objective of this research is to demonstrate the reliability and sensitivity of using human and mouse stem cells in a highthroughput screening paradigm designed to provide reliable and highly sensitive risk assessment data for chemicals that impact gamete production, embryonic endocrine development and endocrine signalling. It will characterize developmental and endocrine toxicity of select environmental agents using in vitro toxicity testing of human and mouse stem cells. The data produced will be used to develop Bayesian models for developmental toxicity classification and toxicity prediction in humans. Through the incorporation of the chemico-physical properties of the test compound, in vitro toxicity testing using genetically diverse human and mouse stem cell populations, it is possible to ascertain novel data on how these compounds impact on specific intracellular pathways in a dose-response fashion.
The project will result in the rapid assessment of chemicals for adverse effects on the development of gametes, adipocytes, and islet B-cells; and on the adipocyte and B-cell endocrine signaling function in human and murine embryonic stem cells. Based on the data, hierarchical Bayesian models will be developed to establish endpoints that are relevant for human gametic and endocrine development and function.