Quantitative Issues in Cancer Research Working Seminar

Gopal Kotecha
Doctoral Student, Department of Biostatistics, Harvard University

“Regulatory Approval Prediction Models”

ABSTRACT: Despite improvements in technology, drug discovery has become slower and more expensive over the last few decades, with the cost of developing a new drug roughly doubling every decade. At the same time, there has been a near exponential increase in the number of clinical trials carried out. This has created an opportunity to use data science methods to predict clinical trial success and regulatory approval. These prediction models can help manage drug trial portfolios. We consider various approaches to this.