A two-VAE generative model, fine-tuned with reinforcement learning and a drug-sensitivity critic, produces molecules with high predicted efficacy against specific cancer transcriptomic profiles, but only in silico.
XQ Zhang, CY Yang, XF Rao, and JP Xiong
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PaccMann$^{RL}$: Designing anticancer drugs from transcriptomic data via reinforcement learning
A two-VAE generative model, fine-tuned with reinforcement learning and a drug-sensitivity critic, produces molecules with high predicted efficacy against specific cancer transcriptomic profiles, but only in silico.