A new UK clinical study, AI-VISION, aims to enhance treatment for triple-negative breast cancer (TNBC). The project unites cancer specialists, data scientists, and physicists to explore varying patient responses to treatment. AI-VISION secured a 1 million grant from Innovate UK to fund research intended to improve treatment decisions for TNBC patients.
"Methods developed for studying deep space are now being used to interpret genomic and clinical information." - Professor Richard Massey
Durham University's Cross-Disciplinary Contribution
Researchers from Durham University's Institute for Computational Cosmology and Department of Physics are contributing their expertise in data analysis and complex system modeling to the study. These statistical and computational skills are being applied to analyze biological and clinical data from cancer patients to identify patterns related to treatment outcomes. Professor Richard Massey is leading Durham's involvement. This cross-disciplinary strategy is key to the study's objective of using artificial intelligence to connect tumor molecular data with clinical results.
Identifying Biomarkers for Personalized Treatment
The AI-VISION project plans to profile tissue samples from individuals previously treated for early TNBC to identify reliable biomarkers. These biomarkers could indicate a patient's potential response to chemotherapy, with or without immunotherapy. By integrating data from various sources, the study seeks to advance beyond current standard care practices, which primarily rely on clinical observations. Successful outcomes from this research could facilitate more personalized cancer treatments and encourage future cross-disciplinary collaborations.