A hybrid pipeline combining quantum simulation and AI models to streamline and accelerate drug discovery.
Define atomic structure and simulate target molecules using quantum chemistry principles (e.g. Hamiltonians).
Simulate quantum circuits to estimate molecular energy levels and binding efficiency using platforms like PennyLane.
Use machine learning models to analyze simulation outputs and rank candidate molecules by efficacy and toxicity.
Rediscover known drugs as a proof of concept and validate accuracy by comparing against experimental results.