How can the National Cancer Institute incentivize innovation in genetic epidemiologic research with the prize authority recently given to all federal agencies by Congress?
Under authority of the America Creating Opportunities to Meaningfully Promote Excellence in Technology, Education, and Science (America COMPETES) Act, federal agencies like the National Institutes of Health are encouraged to use challenges and prizes to find innovative solutions to complex scientific problems.
Current and past federal challenges are posted on Challenge.gov and range from fairly simple contests (NLM & You: The Video Contest) to far more complicated challenges aimed at more grand challenges of the 21st century (My Air, My Health Challenge).
What Do YOU Think?
We are interested in exploring how the use of challenges could be expanded to address burning questions in the field of genetic epidemiology of complex diseases, as well as foster collaboration with diverse fields or engage citizen scientists.
We are looking for feedback on what genetic epidemiology problems could best be solved through open innovation. For example:
- What is the best variant calling procedure to identify putative polymorphic sites?
- What is the best algorithm for predicting the effect of genetic variants on protein function?
- Can we use prizes, challenges or games to predict phenotype from genotype?
What do YOU think of the above topics? In your opinion, what is the most pressing genetic epidemiology question which could best be solved through open innovation?
Elizabeth M. Gillanders, Ph.D., is Chief of the Epidemiology and Genomics Research Program’s (EGRP) Host Susceptibility Factors Branch. She manages its research portfolio and initiatives focusing on factors that influence personal susceptibility to cancer in humans. Additionally, Dr. Gillanders has been involved in several trans-NIH activities related to the implementation of the NIH data sharing policies, as well as several trans-NIH activities designed to address the analytical challenges for studying gene-gene and gene-environment interactions, complex phenotypes, and next generation sequencing.
Leah Mechanic, Ph.D., M.P.H., is a Program Director in the EGRP’s Host Susceptibility Factors Branch. Her responsibilities include management of a portfolio of grants related to factors modulating susceptibility to cancer and serving as a Division representative for trans-NCI efforts to ensure access to and use of high quality biospecimens. Additionally, Dr. Mechanic has been involved in several trans-NIH activities designed to address the analytical challenges for studying gene-gene and gene-environment interactions, complex phenotypes, and next generation sequencing.
Eric (Rocky) Feuer, Ph.D., is Chief of the Surveillance Research Program’s Statistical Methodology and Applications Branch. He is the author of more than 150 papers in the areas of cancer control modeling, statistical methods for the analysis, interpretation, and presentation of population-based cancer statistics; development of new cancer progress measures; and survival analysis.
Huann-Sheng Chen, Ph.D., is a mathematical statistician and program director in the Statistical Methodology and Applications Branch of the Surveillance Research Program. Dr. Chen’s research areas focus on statistical genetics and genetic epidemiology. He has also been involved in research on the patterns of cancer incidence rates adjusted for reporting delay, and cancer mortality projections in national and local populations.