Integration of Mixtures Toxicology, Toxicogenomics and Statistics.

描述（由申请人提供）：本培训资助的目的是培训生物统计学家在跨学科合作团队中工作，解决与评估相关环境化学混合物或毒物基因组学领域的影响相关的问题。这项事业成功的一个关键是化学混合物或毒物基因组学领域的主要科学家（基因组或混合毒理学家、环境流行病学家和生物统计学家）与生物统计学系的学员共同努力。培训的目的是让学员对这两个重要毒理学领域的统计问题有所了解，并积累相关工作经验。这些受训者将有资格

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.