“Advancing Regulatory Science for Health and Safety”
Regulatory science is an interdisciplinary area of scientific research that aims to enhance the development of safe and effective medical products. Regulatory science relies on a community of scientists from diverse fields to collaborate in new ways, to generate new knowledge that will inform the regulatory decision-making process. ICBI works closely with the Georgetown University Program for Regulatory Science & Medicine to advance cross-institutional regulatory science initiatives.
The project will: 1) Create a high-quality, curated data set of select autoimmune diseases, including genetic loci, proteins, functions and pathways, and other molecular processes involved. 2) Curate a separate data set to link symptoms as described in VAERS to a coded, standard set of terms (created by MeDRA, the Medical Dictionary for Regulatory Activities) to molecular pathways and mechanisms. These data sets will enable Georgetown University and the FDA to support various molecular and informatics analyses.
Response to the oncology drug gemcitabine may be variable in part due to genetic differences in the enzymes and transporters responsible for its metabolism and disposition. The aim of our in silico study was to identify gene variants significantly associated with gemcitabine response that may help to personalize treatment in the clinic. Biomarkers identified in this integrative analysis may contribute insights into gemcitabine response variability. As genotype data become more readily available, similar studies can be conducted to gain insights into drug response mechanisms and to facilitate clinical trial design and regulatory reviews.
Triple negative breast cancer (TNBC) accounts for about 10-17% of all breast cancers and is defined by the lack of estrogen receptors, progesterone receptors and human epidermal growth factor receptor 2 (HER2). The most successful types of treatment target these three receptors. The objective of this study is to identify molecular markers in TNBC patients for drug discovery research and personalized medicine. This research will provide the infrastructure, data, and tools to analyze multi-omics data from TNBC samples to help reviewers at the FDA use this framework for new targeted therapies in breast cancer.
medTurk (inspired by Amazon's Mechanical Turk) supports clinical research by using the ingenuity of humans to extract information from unstructured clinical notes. It's software (i.e., a web server) you host privately. It lets curators answer questions in parallel analogous to the way Amazon Mechanical Turk operates. The answers are then downloadable in CSV for analysis using your favorite software (e.g., R, Excel).
See github.com/ICBI/medturk for detailed information.
EXAMPLES OF OUTCOMES, RESULTS, COLLABORATIONS, IMAGES
Functional interaction network of Guillain-Barre Syndrome associated genes and vaccine ingredients. Genes associated with GBS are represented by circles. “Linker” genes added interconnect the network are represented as diamonds. Red triangles represent vaccine ingredients that interact with genes in the network. Genes highlighted in yellow are present in both the KEGG Influenza A pathway and were significantly up or down regulated following influenza vaccination.
Publications resulting from work in this research platform
McGarvey. P.B., Suzek, B., Baraniuk J. N., Rao, S., Conkright, B., Lababidi, S., Sutherland, A., Forshee, R. and Madhavan S. 2014. “In silico analysis of autoimmune diseases and genetic relationships to vaccination against infectious diseases”. BMC Immunology. Dec 9;15(1):61. PMC4266212
Michael Harris, Krithika Bhuvaneshwar, Thanemozhi Natarajan, Laura Sheahan, Difei Wang, Mahlet G. Tadesse, Ira Shoulson, Ross Filice, Kenneth Steadman, Subha Madhavan, John Deeken. “Pharmacogenomic characterization of gemcitabine response - a framework for data integration to enable personalized medicine.” Pharmacogenetics and Genomics 2014 Feb;24(2):81-93. PMCID: PMC3888473