Harnessing polypharmacology in precision oncology (360G-Wellcome-204735_Z_16_Z)

The serendipitous discovery of new targets of drugs questions the prevalent view of drugs as selective inhibitors of a single protein. However, how the binding to several proteins – termed polypharmacology – influences clinical safety and efficacy is poorly understood. During this project, I will analyse clinical, omics and chemical data to uncover the impact of polypharmacology in precision oncology. Firstly, I will analyse data from clinical trials performed at the Royal Marsden Hospital to identify the drugs taken by patient super-responders or those drugs that produced unexplained side-effects. This clinical data will be integrated with chemical data available via the knowledgebase canSAR and used to predict polypharmacology using recently developed chemoinformatic methods. Predicted off-tragets will then be experimentally validated. Finally, I will use available clinical and omics data to identify predictive biomarkers of the newly identified off-targets. Overall, I propose a unique project that has not been attempted before due to the combination of multidisciplinary skills, data and environment required. This project has the potential to transform our understanding of drug action and to yield new biomarkers that can quickly be translated to extend the use of existing cancer drugs in the clinic for the benefit of cancer patients.