Bin Li
Takeda Pharmaceuticals International Co., USA
Title: NGS data process and building/testing drug-sensitivity predictive models for both single agents and drug combinations
Biography
Biography: Bin Li
Abstract
Precision medicine approaches to optimize therapeutic efficacy in selected patient populations requires the acquisition and storage of in depth genomic and phenotypic patient information combined with the use of innovative computational platforms for knowledge generation. A critical objective is to discover and clinically apply biomarkers to select patients most likely to respond or least likely to experience adverse events. Here, we discuss various computational efforts to support translational biomarker research for biomarker discovery and the development of predictive signatures for clinical testing. These efforts include: Method evaluation and pipeline building for QC/process clinical NGS data; single agent’s predictive modeling for identifying/validating translational biomarkers for patient stratification; building translational research storage platforms to integrate clinical and omics data and; method development and evaluation for drug combination prediction. Combining predictive modeling and translational platform building efforts, computational bioinformatics will be able to support the identification of biomarkers for patient stratification and disease indication selection.