Dr. Schipper is a Professor and Director of the division of Biostatistics and Bioinformatics in the Department of Radiation Oncology. He also has a joint appointment as Professor of Biostatistics. He has developed web apps implementing prediction models and clinical decision aids which have been widely used. He has authored or co-authored more than 170 papers published in peer-reviewed journals.

Clinical Trial Design: Optimal design of early phase cancer clinical trials must make efficient use of the typically small patient sample sizes to address study objectives and inform subsequent trials while also protecting the safety of trial subjects. Our group has proposed approaches for optimally incorporating dose expansion cohorts in early phase trials, an extension of the popular phase I CRM design to accommodate
uncertainly in toxicity assessment and extended small n SMART designs to include continuous tailoring variables for second stage randomization. I have also participated in development of guidelines for content of statistical analysis plans for early phase trials.

Development and Application of Statistical Methods for Personalized Medicine: One of Dr. Schippers long standing interests is use of statistical models to individualize treatment for cancer patients and thus improve patient outcomes. We are working on this in two areas. The first addresses the problem of how to optimize a radiation treatment plan. We have proposed an approach in which the clinicians define a utility function that captures the desirability of multivariable patient outcomes including multiple toxicity and efficacy measures. Then the optimal plan is defined as the plan that maximizes the expected utility which can be calculated from statistical models for the individual outcomes included in the utility definition. In the second approach, we are integrating models for cancer mortality, other cause mortality and overall treatment effects from randomized clinical trials to provide individual estimates of treatment benefit.