Gareth is a Senior Lecturer in Cancer Digital Sciences and Machine Learning at The University of Manchester. As a RadNet funded Senior Lecturer, he will work to establish and lead his new research group focussing on machine and rapid learning. He has extensive experience working on the MCRC’s real world data initiative, aiming to use the clinical and imaging data recorded during radiotherapy patients’ normal care to optimize their cancer treatment. The programme aims to provide medical evidence where clinical trials data is lacking, particularly in under-represented populations.
His research focuses on the development and application of the digital health Learning Healthcare System (LHS) and Rapid Learning concepts. He leads and contributes to research projects that span the workflow of these approaches: innovative data capture and sharing technologies; the use of machine learning to provide clinical insight; and the prospective use of real-world data to evaluate the clinical impact of changes in practice where conventional clinical trials are not practical.
He designed and implemented the informatics research platform and governance framework that enables secure research on linked real-world clinical data assets at the Christie and underpins many of the MCRC’s real world data projects. This facility has supported >80 studies since going live in 2017 resulting >40 peer-reviewed papers and 6 international research prizes. He and Prof. Faivre-Finn were recently awarded an NIHR programme grant to prospectively demonstrate the use of rapid learning for the first time in the radiotherapy clinic. The programme will use real-world data to quickly evaluate the impact of changing radiotherapy care and iteratively optimise this change to the health needs of The Christie’s patients.