T32 Research Training
Ruth L. Kirschstein National Research Service Award Institutional Predoctoral Training Program in the Neurosciences (T32):
BIG DATA and PRECISION MEDICINE
The Division of Gastroenterology, Hepatology and Nutrition has managed a successful T32 training grant with research trainees for the past ten years. Based on the translational research strengths of the Division and its commitment to complex disease interactions and treatments, the focus of the Division’s T32 program centers on big data and precision medicine in gastroenterology and hepatology.
Training young physicians and scientists for future success with patient-centered solutions requires an innovative training program within a supportive environment. New opportunities and national health care trends inspired our UPMC leadership to create a forward-thinking T32 initiative designed to attract and retain top-quality trainees and to equip a new generation of physicians and scientists.
With the structure of the Division’s successful U01 programs, our T32 trainees will integrate the tools of big data and personalized medicine into clinical and translational research and team teaching. This novel program is designed to:
- Provide rigorous individualized training that encompasses core competencies in translational research methodologies and interdisciplinary professional skills;
- Assemble multidisciplinary mentoring to pilot translational research projects from conceptualization to completion that include Big Data and Personalized Medicine; and
- Support fellows’ future career goals by career coaching and disseminating scholarly activities.
The T32 trainee’s research plan includes an experienced program director and four co-directors who are leaders in clinical-translational research, basic sciences, biomedical informatics, and computational biology. Trainees will receive intense classroom and practical training through the University of Pittsburgh’s Institute for Clinical Research Education (ICRE), followed by core classes and electives in basic, translational, and/or clinical sciences.
Each trainee will work with a mentoring team comprised of a physician, scientists, and a domain expert in big data, who will work with the trainee to develop an individual development plan to ensure compliance with the following:
- Processes all requirements for a graduate degree (Masters or PhD);
- Cultivate individualized projects of importance to patients and digestive disease care;
- Receive program and career mentoring to include submissions of F32s, K awards or other competitive awards; and
- Begin their appropriate career development pathway.
Big Data electives are built into each trainee’s individual development plan (i.e., Foundations of Translational Bioinformatics, Symbolic Methods in Artificial Intelligence, Probabilistic Methods for Computer-Based Decision Support, Machine Learning, Computational Genomics, and Laboratory Methods for Computational Biologists). Additional experience may be gain through participation in existing U01s, multicenter clinical/translational studies, and internships.
There is no precedent for this program—despite a clear need. However, our Division’s ongoing training success demonstrates T32 success and highlights outstanding faculty and a nurturing and energetic environment.
David C. Whitcomb, MD, PhD
Giant Eagle Foundation Professor of Human Genetics
Professor of Medicine, Cell Biology & Physiology and Human Genetics
Director, Pancreas Center
David G. Binion, MD
Professor of Medicine
Director, Nutrition Support
Co-Director & Translational Research Head, IBD Center
For more information:
- University of Pittsburgh Department of Biomedical Informatics (live link to > http://www.dbmi.pitt.edu)
- PITT MED (live link to > http://www.pittmed.health.pitt.edu/story/trying-personalized-medicine)
- The Institute for Precision Medicine (live link to > www.ipm.pitt.edu)
- GREAT Study (live link to > http://www.great.pitt.edu)
- What is Personalized Medicine and What Should It Replace? [Nat Rev Gastroenterol Hepatol] (live link to > https://www.ncbi.nlm.nih.gov/pubmed/22614753