Utilizing AI and biobanking for drug target-biomarker validation in personalized melanoma treatment

Purpose and goal

The project aims to identify and validate novel therapeutic targets and biomarkers for personalized melanoma treatment by integrating advanced AI and machine learning with extensive biobank data from the Human Melanoma Proteome Atlas (HMPA), enabling more effective individual diagnostics and therapies.

Expected effects and result

Expected outcomes include identifying robust therapeutic targets and biomarkers enabling improved patient stratification and personalized treatment strategies. The project also aims to enhance diagnostic precision, prognostic accuracy, and reduce melanoma mortality through AI-driven analyses of tumor heterogeneity.

Planned approach and implementation

The project will implement an integrated approach combining proteomics and spatial omics data with advanced AI and digital pathology methods. Functional validation of identified targets will be performed using preclinical models, with continuous clinical collaboration to ensure direct translation of results into clinical practice.