Many areas of research in basic, clinical and population sciences continue to demand well-trained biostatisticians who demonstrate scientific knowledge and competencies to be effective collaborators on multidisciplinary research projects. Not only do modern biostatisticians need to be trained on how to apply the wide range of quantitative methods that are needed in biomedical research, but they also need an understanding of the biological bases for diseases and of the biological measures that are collected in biomedical research. Recognizing the demand for biostatisticians with multiple skills, in 2005 we funded the Interdisciplinary Training for Biostatisticians Program with support from the NIGMS, with the goal of training biostatisticians by integrating traditional courses in statistical theory and study design, with courses in biology, and applied internships with biomedical investigators. Between fall 2005 and fall 2013, we trained 21 highly qualified students with excellent academic records and varying backgrounds in economics, mathematics, computer science, business administration and biology. Our trainees are supported by this training program for approximately 2 years, and transition to research assistant positions as they complete the Ph.D. program in typically an additional 3.5 years. By 2014, a total of 9 trainees have completed the Ph.D. program and progressed toward promising careers in academia, research groups in academic and non- academic settings, pharmaceutical companies and contract research organizations. All these trainees graduated with substantial experience in interdisciplinary research collaborations, 2-3 years teaching experience at different levels, a solid research record that includes an average of 18 publications in scientific journals, presentations at national and international conferences in statistics, genetics, clinical trials, and medically oriented conferences. We propose to continue this successful interdisciplinary training program and train 6 post-bachelors, pre- doctoral students per year. Our goals for the next cycle will be (1) to offer a two/three year program that will include coursework along with rotations in bioinformatics, genetics, ethical conduct of research, and clinical trials; (2) to maintain a training program that produces doctoral students in biostatistic with a strong background in statistical methods, biology, and experience in applied research and competencies to function in a fast changing world of data and emerging technologies; and (3) to equip biostatisticians who graduate from the program with a strong record of scientific publications, experience presenting at conferences, experience in interdisciplinary collaborations and in teaching, that prepare them for competitive careers in academia, industry and government. This program will produce students not only with classroom exposure to quantitative skills, but also practical experience as functioning biostatisticians.

Public Health Relevance

Biostatistics plays a fundamental role in biomedical and public health research and there is a growing need to educate biostatisticians to become effective collaborators on clinical and basic science research projects through an interdisciplinary approach. This program plays an important role in educating the future workforce of biostatisticians to be effective collaborators in scientific teams and contribute to the health and wealth of the USA.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Institutional National Research Service Award (T32)
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NIGMS Initial Review Group (TWD)
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Gibbs, Kenneth D
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Boston University
Biostatistics & Other Math Sci
Schools of Public Health
United States
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Fuady, Angga M; Lent, Samantha; Sarnowski, ChloƩ et al. (2018) Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20. BMC Genet 19:72
McIntosh, Avery I; Jenkins, Helen E; White, Laura F et al. (2018) Using routinely collected laboratory data to identify high rifampicin-resistant tuberculosis burden communities in the Western Cape Province, South Africa: A retrospective spatiotemporal analysis. PLoS Med 15:e1002638
Baltrusaitis, Kristin; Brownstein, John S; Scarpino, Samuel V et al. (2018) Comparison of crowd-sourced, electronic health records based, and traditional health-care based influenza-tracking systems at multiple spatial resolutions in the United States of America. BMC Infect Dis 18:403
Wang, Lan; Perez, Jeremiah; Heard-Costa, Nancy et al. (2018) Integrating genetic, transcriptional, and biological information provides insights into obesity. Int J Obes (Lond) :
Mayinger, Michael Christian; Merchant-Borna, Kian; Hufschmidt, Jakob et al. (2018) White matter alterations in college football players: a longitudinal diffusion tensor imaging study. Brain Imaging Behav 12:44-53
Lent, Samantha; Xu, Hanfei; Wang, Lan et al. (2018) Comparison of novel and existing methods for detecting differentially methylated regions. BMC Genet 19:84
Marone, Sarah; Bloore, Katherine; Sebastiani, Paola et al. (2018) Purpose in Life Among Centenarian Offspring. J Gerontol B Psychol Sci Soc Sci :
Gu, Xiaosi; Zhou, Thomas J; Anagnostou, Evdokia et al. (2018) Heightened brain response to pain anticipation in high-functioning adults with autism spectrum disorder. Eur J Neurosci 47:592-601
Weir, Isabelle R; Trinquart, Ludovic (2018) Design of non-inferiority randomized trials using the difference in restricted mean survival times. Clin Trials 15:499-508
Du, Mengtian; Van Ness, Sarah; Gordeuk, Victor et al. (2018) Biomarker signatures of sickle cell disease severity. Blood Cells Mol Dis 72:1-9

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