Zapata Computing, in collaboration with Insilico Medicine and the University of Toronto, has used quantum-enhanced generative AI to generate viable cancer drug candidates for the first time. The team used generative AI to develop novel KRAS inhibitors, a critical focus in cancer therapy. The quantum-enhanced generative model outperformed classical models, producing two molecules with superior binding affinity.
The research, which is awaiting peer review, is a follow-up to a 2023 study that first demonstrated the potential of quantum generative AI for drug discovery. Zapata AI has also announced a strategic partnership with D-Wave Quantum Inc. to build quantum generative AI models for commercial applications.
Quantum-Enhanced Generative AI in Drug Discovery
In a recent study, researchers from Zapata Computing, Inc., Insilico Medicine, and the University of Toronto have successfully utilized quantum-enhanced generative AI to generate viable cancer drug candidates. This marks the first instance of a generative model running on quantum hardware outperforming classical models in this field. The research leverages the capabilities of today’s quantum devices, pointing towards a promising future for hybrid quantum generative AI in drug discovery.
The researchers focused on developing novel KRAS inhibitors, a critical area in cancer therapy that has historically been challenging due to the intrinsic biochemical properties of KRAS, which made it “undruggable”. Generative models running on classical hardware, quantum hardware (specifically, a 16-qubit IBM device), and simulated quantum hardware were used to generate one million drug candidates each. These candidates were then filtered algorithmically and by humans, resulting in 15 molecules that were synthesized and tested through cell-based assays. The two molecules generated by the quantum-enhanced generative model were distinct from existing KRAS inhibitors and showed superior binding affinity over the molecules generated by purely classical models.
Quantum and Classical Computing: A Complementary Approach
Yudong Cao, CTO and co-founder at Zapata AI, highlighted the project as an exciting demonstration of how quantum and classical computing can complement each other to deliver an end-to-end solution. The collaboration between Zapata, UofT, and Insilico is a testament to how the startup and university ecosystems can leverage each other’s advantages to drive progress. The team plans to further this research by moving the discovered molecules through the drug discovery pipeline, applying their methodology to other disease targets, and extending their quantum-enhanced generative AI to other industrial use cases with complex design challenges.
Quantum Generative AI: A Promising Future in Drug Discovery
This research builds on a previous study published by the team in 2023, which first demonstrated the potential of quantum generative AI for drug discovery. Alex Zhavoronkov, PhD, founder and co-CEO of Insilico Medicine, sees this as an important early step towards a more advanced drug discovery future. The team looks forward to further developing these methods with Zapata AI and Alán Aspuru-Guzik at the University of Toronto.
Zapata AI has also recently announced a new strategic partnership with D-Wave Quantum Inc., with an initial focus on building quantum generative AI models that accelerate the discovery of new molecules for commercial applications. Christopher Savoie, CEO and co-founder of Zapata AI, expressed excitement about the potential of this technology, stating that this is only the beginning of their journey towards discovering new molecules for drug discovery and other industrial applications.
Integrating Quantum Computing into Drug Discovery
Alán Aspuru-Guzik, a professor of Chemistry and Computer Science at the University of Toronto and a co-founder and Scientific Advisor of Zapata AI, has always been excited about the potential of AI and quantum computing for drug and materials discovery. He believes that the integration of quantum computing modules into the drug discovery pipeline is just beginning and that this work sets the path for future, more powerful quantum computers to demonstrate their abilities. The global community of researchers will be able to further improve upon this first-of-a-kind experiment.
Zapata AI is a company specializing in Industrial Generative AI, changing how enterprises solve complex problems with its powerful suite of Generative AI software. By combining numerical and text-based solutions, Zapata AI enables industrial-scale enterprises and government entities to leverage large language models and numerical generative models more efficiently. With proprietary science and engineering techniques and the Orquestra® platform, Zapata AI is accelerating Generative AI’s impact in Industry. The Company was founded in 2017 and is headquartered in Boston, Massachusetts.
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