A virtual cancer cell that predicts what a drug will do before you test it

Perturbation foundation models trained on Perturb-seq, CRISPR screens and compound-response atlases aim to predict transcriptional and viability responses to unseen perturbations and combinations. The critical missing element is prospective, blinded validation against held-out wet-lab experiments and, eventually, clinical outcomes. Without that, these models risk repeating the overfitting seen in earlier drug-response prediction efforts.