Innovative statistical methods for clinical trial pathways supporting regulatory drug approval

Programme overview:
This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to address important applied biomedical research questions in priority areas aligned with industry. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice.

Project overview:
Regulatory approval of new drugs is underpinned by provision of substantial evidence of effectiveness from clinical trials. This is often interpreted as requiring two independent confirmatory trials. Recent innovation in clinical trial design is challenging this interpretation, however, as trials conventionally conducted separately may be combined using an adaptive seamless design.

In collaboration with Boehringer Ingelheim in Germany, this PhD project will focus on statistical methods for trial design and decision-making in adaptive confirmatory clinical trials. This will require a combination of theoretical and computational statistical methods, to explore optimal trial design and synthesis of evidence from different sources.