Translational Bioinformatics Methods in the Drug-Interaction Research
Lang Li, Indiana University School of Medicine
Wednesday, September 11, 2013
Brickyard (BYENG) 420 [map]
Novel drug interactions can be predicted through large-scale text mining and knowledge discovery from the published literature. Using natural language processing (NLP), the key challenge is to extract drug interaction relationship through the machine learning. Li proposes a hybrid mixture model and tree-based approach to extract drug interaction relationship. This two-pronged approach takes advantage of both the numerical features of reported drug interaction results and the linguistic styles of presenting drug interactions. In this talk, Li will discuss the concept and method of literature-based knowledge discovery in drug interaction research and data mining-based drug interaction research using large electronic medical record databases. Li will discuss the pros and cons and multiple design and analyses strategies for large-scale drug interaction screening studies that use large-scale electronic medical record databases. Li will illustrate these concepts in the context of a translational bioinformatics drug interaction study on myopathy, a muscle weakness adverse drug event, elucidating on both the clinical significance and the molecular pharmacology significance.
Lang Li is the interim director of CCBB. He is an associate professor in Medical and Molecular Genetics, Clinical Pharmacology, and Biostatistics in the Indiana University School of Medicine (IUSM). He received his Ph.D. in biostatistics from the University of Michigan in Ann Arbor, Michigan, before joining the IUSM in 2001. Li also serves as the associate director of the Indiana Institute of Personalized Medicine (IIPM). Professionally, Li serves on multiple NIH study sections. He also serves as the associate editor for the journal Nature: Pharmacometrics and System Pharmacology. He uses informatics, genomics and statistics to investigate drug efficacy and safety. He is interested in both the molecular mechanisms and clinical significance of drug safety and efficacy. During his 13 years tenure in the Indiana University, Li published 130 papers in the peer reviewed journals, and his H-index of his publication is 29. His lab is currently funded by 10 federal funding agency and private foundation.