Members of the Statistical Methods in Medicine group develop and evaluate novel statistical methods of study design and data analysis for use in the pharmaceutical and medical research community.
This methodological research is often conducted in close collaboration with companies and public sector research institutions, and covers pre-clinical and clinical statistics. Several members of the group form the Medical and Pharmaceutical Statistics Research Unit, about which further information can be found at www.mps-research.com
Our main areas of research are:
This work concerns first-in-man studies of new drugs or combinations of drugs. Past research has considered the design of Phase I oncology trials, where subjects are patients and responses are toxicities, and healthy volunteer studies, where responses are pharmacokinetic and pharmacodynamic assessments. Work is focused on developing novel Bayesian decision procedures for determining the optimal dose to be taken forward for subsequent evaluations.
This line of research mainly concerns non-compartmental estimation of pharmacokinetic parameters such as the area under the concentration versus time curve for sparse sampling schemes.
Adaptive designs for clinical trials
Our research in this area focuses on multiple testing procedures that ensure control of the proportion of false positive findings. Additional work is looking at estimation at the end of such studies as well as simultaneous confidence intervals.
Strategies for research prioritisation in children
Decision frameworks that assess the need for separate studies in children are developed. Additional work looks at developing Bayesian designs for trials in rare diseases as well as procedures that formally incorporate relevant existing information when determining the optimal dose of a medicine for use in children.