Despite remarkable progress in cancer precision medicine, drug resistance and low success rates underscore the urgent need for data-driven clinical trial designs. SYNTHESIS uses generative deep learning to integrate multi-omic data from pre- and clinical cancer databases, generating synthetic tumor profiles. This will aid the identification of druggable breast cancer subtypes and their molecular signatures, ultimately boosting clinical trials.