10086327OncoSelect: Machine-learning enabled precision-oncology tool for renal cell carcinomaClosedCollaborative R&DInnovate UKM:MBio is an innovative UK-SME supporting the British bioscience ecosystem in achieving scientific, clinical and commercial success through conducting deep data-led analysis and using machine-learning derived insights from its multi-omic oncology datasets. These datasets have the potential to support in predicting treatment-response based on individual patient tumour genetic makeups. In this project, M:MBio will develop a machine-learning enabled tool, 'OncoSelect' specifically for Renal Cell Carcinoma (RCC) that will improve diagnostic precision and stratify patients against the most appropriate treatments, based on their genomic data. The project will involve building predictive models to identify which patients are most likely to respond to different treatments or experience specific adverse events based on their genetic makeup within RCC. M:MBio will be working closely with clinical experts Weatherden to ensure that the stratification tools are based on sound scientific principles and align with clinical practice. OncoSelect's outputs will be validated using retrospective and prospective studies, continuously refining/iterating algorithms based on real-world feedback and new data. Targeted stratification of patients based on genomics data involves the use of genetic information to identify specific groups of patients who are likely to respond better to certain treatments or have a higher risk of developing certain diseases. This approach allows for more personalised and effective healthcare, as medical professionals can tailor their treatments and interventions to the individual patient's genetic makeup. The process involves analysing the patient's genomics data to identify genetic markers that may be associated with particular diseases or treatments, and then using this information to design a targeted treatment plan. Advances in genomics research have led to an increase in the use of targeted stratification in healthcare, and this trend is expected to continue as more genomic data becomes available. The consortium will initially collect and analyse data on patient demographics, medical histories, genetic profiles, and other relevant factors. Various algorithmic and statistical techniques will be used to identify the relevant genomic markers that are associated with RCC or treatments of interest. To develop targeted stratification tools, the consortium will use a combination of machine-learning/artificial intelligence, network analysis, and data visualisation techniques. Overall, the goal will be to enable more personalised and effective treatment options for patients by identifying and targeting specific subgroups with different clinical needs and treatment outcomes. OncoSelect will improve diagnostic precision and stratify patients to the most appropriate treatments based on their genomic data, unique within RCC.