Researchers led by Altuna Akalin at the Max Delbrück Center developed Flexynesis, a deep learning toolkit designed to integrate multi-omics data alongside clinical and imaging information to improve precision oncology decision-making. Published in Nature Communications, Flexynesis enables simultaneous analysis of diverse datasets, including DNA, RNA, protein expression, and medical images, facilitating better diagnosis, prognosis, and therapy selection. Flexynesis is flexible, broadly applicable, and accessible through various software platforms, addressing the challenge of selecting effective treatments in complex cancer cases.