Quantum Generative Models for Small Molecule Drug Discovery

Understand

Existing drug discovery pipelines take 5-10 years and cost billions of dollars.

• Computational approaches aim to sample from regions of the whole molecular and solid-state compounds called chemical space which could be on the order of 1060 .
• Deep generative models can model the underlying probability distribution of both the physical structures and property of drugs and relate them nonlinearly.
• By exploiting patterns in massive datasets, these models can distill salient features that characterize the molecules.