The development and approval of innovative medical drugs is a prime example for the application of data science methodology.
In this project innovative biostatistical methods ranging from informed bayesian decision making in early drug development (e.g. in basket trials) to causal inference for event history analysis in pivotal phase III trials and so-called „Real World Data“ will be developed. A combined application of those methods could be informed bayesian event history analyses for interim decision making by Data Safety Monitoring Boards in clinical trials.

First supervisor:

Prof. Dr. Kathrin Stucke-Straub, Technische Hochschule Ulm

 

Tandem partner:

Prof. Dr. Jan Beyersmann, Institut für Statistik, Universität Ulm

 

Consulting experts:

Prof. Dr. Hans Kestler, Institut für medizinische Systembiologie, Universität Ulm

Prof. Dr. Michael Munz, Technische Hochschule Ulm