Researchers at the Berlin Institute for Medical Systems Biology have developed Flexynesis, a deep learning framework designed to integrate diverse multi-omics datasets, including genomic, transcriptomic, imaging, and clinical data, facilitating precise cancer diagnosis and personalized therapy selection. The toolkit addresses limitations of prior inflexible deep learning methods, supports multiple modeling tasks, and is distributed via multiple software platforms for accessibility. This promises improved biomarker identification and tailored treatment plans for oncology patients.