Friday 12 May 2017, 1.00PM
Speaker: Dr. Jonathan Wagg, Roche Pharmaceutical Research and Early Development
The Clinical Pharmacology Disease Modelling Group (CPDMG) aims to better understand the biological basis of inter-patient variability of clinical response to drugs. Improved understanding of how our drugs drive clinical responses informs which combination dosing regimens (“right drugs”) specific patient populations (“right patients”) are most likely to benefit from. Drug evoked responses are driven by drug-molecular-target interactions that perturb target functions. These direct, "proximal effects" (typically activation and/or inhibition of protein function) propagate across the biological processes these targets participate in via “distal effects” to drive clinical responses. "Distal effects" take time to develop, are difficult to predict, and, in many cases drive observed clinical responses.
CPDMG applies Clinical Systems Pharmacology approaches to predict the mechanisms by which drug combinations evoke observed clinical responses. Over the last 2.5 years, CPDMG has successfully applied these data driven approaches to inform key decisions across clinical development programs. Implementation of these approaches requires: (i) integration of prior relevant biological/clinical knowledge with large clinical and “omics” datasets; (ii) application of supervised machine learning to transform this knowledge/data into actionable, clinically relevant, mechanistic insights. In this presentation, key features of these approaches will be discussed by way of clinical examples.
The host for this seminar is Professor Mark Coles.
Telephone: 01904 328845