For the First Time, Quantum-Enhanced Generative AI Generates Viable Cancer Drug Candidates
The research points to a promising future of hybrid quantum generative AI for drug discovery using today’s quantum devices.
- The research points to a promising future of hybrid quantum generative AI for drug discovery using today’s quantum devices.
- In the study, the researchers utilized generative AI to develop novel KRAS inhibitors, a critical focus in cancer therapy historically deemed “undruggable” due to its intrinsic biochemical properties.
- Generative models running on classical hardware, quantum hardware (specifically, a 16-qubit IBM device), and simulated quantum hardware generated one million drug candidates each, which were then filtered algorithmically and by humans.
- “For the first time ever, we’ve been able to produce real effective drug lead molecules with quantum-enhanced generative AI,” said Christopher Savoie, CEO and co-founder of Zapata AI.