Integration of Mixtures Toxicology, Toxicogenomics and Statistics.

Virginia Commonwealth University, Richmond VA

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): The objective of this training grant is to train biostatisticians to work in inter-disciplinary collaborative teams addressing the problems associated with evaluating the effects of relevant environmental chemical mixtures or in the area of toxicogenomics. A key to the success of this venture is the joining of the efforts of key scientists (genomic or mixtures toxicologists, environmental epidemiologists and biostatisticians) in the fields of chemical mixtures or toxicogenomics with trainees from a department of biostatistics. The goal is for trainees to gain an understanding of and experience working on statistical issues for these two important areas of toxicology. These trainees will be qualified to hold unique positions in governmental agencies, academia, and industry where properly evaluating risks associated with relevant chemical exposures is becoming increasingly important. The trainees will be Ph.D. students in the Department of Biostatistics at the Virginia Commonwealth University (VCU), where they will pursue pre-doctoral training in the discipline of biostatistics. Additional expertise will be achieved through work on dissertation/research topics that are pertinent to the field of mixtures or toxicogenomics and through collaborative work with toxicologists and/or environmental epidemiologists actively working in their area of interest. Through these research projects, students will gain experience collaborating with a team of experts working to understand the relationship between environmental exposures and human disease susceptibility. The trainees will assist in the design of studies, conduct appropriate power analyses, analyze resulting data, write reports with proper interpretation of the results, and participate in a collaborative team to produce one or more manuscripts for peer-review publication. In addition, the trainees will have dissertation topics developing statistical methodology for issues involved in the design and analysis of data resulting from chemical mixtures studies or high-throughput technologies.