Using Quantum-Enhanced AI to Design Novel KRAS Inhibitors
In a collaborative effort, Zapata Computing (Zapata AI), together with Insilico Medicine, the University of Toronto, and St. Jude Children's Research Hospital, has made significant progress in the application of quantum-enhanced generative artificial intelligence (AI) for drug discovery. Their recent study showcases the use of quantum computing to surpass traditional models in identifying new cancer drug candidates, specifically targeting the historically challenging KRAS inhibitors.
The research utilized a generative AI model operating on a 16-qubit IBM quantum device to produce a million potential drug candidates. These were narrowed down through algorithmic filtering and human evaluation to 15 promising molecules, which underwent synthesis and cell-based assay testing.
Notably, two of these molecules, derived from the quantum-enhanced model, exhibited unique structures and improved efficacy compared to those identified by classical computing methods.
This achievement not only marks a milestone in the integration of quantum computing into the drug discovery process but also demonstrates the potential for quantum and classical computing to work in tandem, offering comprehensive solutions from initial discovery to final drug development. The synergy between Zapata, the University of Toronto, St. Jude, and Insilico exemplifies the productive intersection of startup innovation and academic research in propelling scientific advancement.
The findings, currently under peer review and available on ArXiv, build upon earlier work published in collaboration with Foxconn in 2023. That study first highlighted the potential of quantum generative AI in drug discovery, setting the stage for this latest advancement.
READ MORE: 12 Companies Using Quantum Theory To Accelerate Drug Discovery
Moreover, this research underlines the capabilities of Insilico Medicine's AI engine, Chemistry42, when combined with quantum-augmented models, to tackle complex drug discovery challenges. The collaboration aims to continue refining these methods, pushing the boundaries of what's possible in the search for new treatments for cancer and other diseases.
Zapata AI has also announced a strategic partnership with D-Wave Quantum Inc., focusing on developing quantum generative AI models for the rapid discovery of new molecules. This move towards commercial application underscores the maturity of Zapata's generative AI technology and D-Wave's quantum computing, promising swift progress towards market-ready solutions.
The involvement of Professor Alán Aspuru-Guzik from the University of Toronto highlights the academic support for this initiative, emphasizing the exploratory nature of integrating quantum computing into drug discovery. This research not only achieves a direct outcome in identifying new drug candidates but also paves the way for future advancements with more powerful quantum computers.
Zapata AI, specializing in Industrial Generative AI, leverages its proprietary technology and the Orquestra® platform to enable enterprises and government entities to solve complex problems efficiently. Founded in 2017 and based in Boston, Zapata AI continues to lead in the application of AI and quantum computing to industrial and scientific challenges.
In October 2023, the company announced its plans to become a publicly listed company on the New York Stock Exchange through a business combination with Andretti Acquisition Corp., valuing Zapata AI at a pre-money equity value of $200 million.
This merger leverages Zapata AI's advanced algorithms and over 100 global patents in generative AI and industrial optimization, highlighting its significant role in revolutionizing AI solutions across various industries including life sciences, finance, and automotive, through its Orquestra®.
The transaction, expected to close in the first quarter of 2024, will bolster Zapata AI's growth strategy by providing up to $84 million to its balance sheet, aiming to accelerate innovation, customer acquisition, and market positioning in the rapidly expanding generative AI sector.
Topics: AI & Digital
