NIEHS Grant Will Establish Bioengineering Partnership to Improve Chemical Hazard Testing Paradigms

An interdisciplinary group of researchers at the University of North Carolina at Chapel Hill and Massachusetts Institute of Technology was awarded a five-year $2.5M grant from the National Institute of Environmental Health Sciences (NIEHS) to establish a partnership between environmental health scientists,
biological engineers, chem-informaticians, biostatisticians and geneticists.  The funding comes from a trans-NIH Bioengineering Research Partnerships Program which is specifically designed to encourage basic, applied, and translational bioengineering research that could make a significant contribution to improving human health.

The team, led by Ivan Rusyn, is comprised of four Lead Investigators who each bring a distinct set of tools and intellectual backgrounds to the project:

  • Ivan Rusyn, MD, PhD (PI) - Associate Professor of Environmental Sciences and Engineering (UNC School of Public Health) who is an
    environmental health scientist with a focus on liver toxicology and mouse models of toxicity.

  • Linda Griffith, PhD - S.E.T.I. Professor of Mechanical and Biological Engineering (Massachusetts Institute of Technology) who is a
    world-renowned researcher in the field of liver tissue engineering.

  • Alex Tropsha, PhD - Professor and Chair, Division of Medicinal Chemistry and Natural products (UNC School of Pharmacy) who is a
    leader in the field of quantitative structure activity/toxicity relationship modeling.

  • David Threadgill, PhD - Associate Professor of Genetics (UNC School of Medicine) who is a geneticist and a pioneer for the
    applications of mouse genetics into cancer research and toxicology.

This multidisciplinary team will apply an integrative, systems approach to:

(1) Develop a 3D microscale mouse liver tissue bioreactor that can be applied to high-throughput screening of chemicals. This is a design-directed effort to produce a unique tool that can increase throughput of testing while reducing the number of animals;
(2) To build, test and validate Quantitative Structure-Toxicity Relationship (QSTR) models that employ both chemical and biological descriptors of molecular structures and take into account genetic diversity between individuals. This aim is a discovery-driven approach that will produce a computational method for compound-prioritization based on the chemical structure, multi-dimensional toxicity data that includes -omics endpoints, and information on genetic diversity of the population; and
(3) Validate a fiscally sensible in vivo and in vitro toxicity screening paradigm for a class of allylbenzene derivatives by producing knowledge anchored on the genetic variability present within the population. This aim will test the hypothesis that genetic variability among individuals is a major determinant in the toxic effects of chemical hazards and that the genetic basis for susceptibility can be successfully elucidated using a panel of mouse inbred strains.

November 05, 2007