Combining Quantum-Based Models With Machine Learning Accelerates Drug Discovery
, Research Engineer/Co-Founder, Sorbonne Université/Qubit-Pharmaceuticals
The first stages of drug discovery involve finding a molecule with a good affinity to a protein target of interest. It's a long and costly process with a low success rate, but it can be drastically accelerated and the associated cost mitigated by ‘in silico’ molecular simulations, provided that these are accurate and fast enough. We'll present key advances in that direction that leverage a unique combination of quantum-based approaches with machine learning in a massively multi-GPU context.