Using Big Data to Find New Uses for Existing Drugs
Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. Integrating and querying such large volumes of data, often spanning domains and residing in diverse sources, presents a daunting challenge. I will introduce a couple of distinct approaches that utilize these data types to systematically evaluate and suggest new disease indications for new and existing drugs.
Dr. Vinod Kumar is a Senior Scientific Investigator in Computational Biology, and a member of the Systematic Drug repositioning group within GlaxoSmithKline Pharmaceuticals. His current research focuses on developing computational methods for drug repurposing to help find new applications for existing drugs. Dr. Kumar is currently the editor of the “Methods in Molecular Biology” series on biomedical literature mining. In the past, he has developed several bioinformatics data mining tools and software for pathway/network visualization and functional genomics analysis. Prior to joining GlaxoSmithKline, Dr.Kumar was an Assistant Professor of Microbiology at Thomas Jefferson University. Dr. Kumar received his PhD in Biochemistry from the Wayne State University School of Medicine and he completed his postdoctoral fellowship at the National Cancer Institute.