| dc.description.abstract | The data science paradigm is assuming increasing importance in the development of pharmaceutical products. This is motivated by the need for new methods and technologies to address the challenges of diminishing returns in pharmaceutical R&D. Given the hurdles in developing blockbuster drugs that address the needs of broad patient populations, discovery and development efforts in the past few gears have sought targeted therapies, driven by translational approaches, and for specific patient subgroups. This requires tools and expertise to mine chemical structures, genomic databases, pharmacology data and clinical outcomes, to identify novel targets, generate lead molecules, nominate clinical candidates, select indications and patients, and correlate clinical safety and efficacy with disease biology, mechanism of action, and preclinical findings. Collaborative work among subject matter experts from diverse disciplines including pharmacology, biomarkers, clinical research, biostatistics, pharmacovigilance, and business analytics, is essential to implement this paradigm. This talk will touch upon various areas of preclinical and clinical development, and commercialization, where a data-driven approach can provide useful insights for selection of assets, and optimization of scientific and commercial value. | en_US |
