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Geometric data science for cancer precision medicine
Dr Deepak Parashar has published a key research paper proposing a novel geometric framework of Hypersurfaces to describe multidimensional clinical trial designs of precision cancer therapy. The methods are a first cross-disciplinary perspective in utilising embedded Euclidean subspaces to visualise the trial design space of master protocols constituting multiple treatments, multiple tumour-types, and multiple mutations for targeted cancer therapy.
The approach paves the way for visualising multidimensional biomarker data, tumour-agnostic significant associations, integrating multimodal and multi-omic data, and generalisation to higher-dimensional innovative trial designs, offering oncologists guidance in targeting multiple therapies for sensitive groups of patients from diverse datasets.