For the First Time, Quantum-Enhanced Generative AI Generates Viable Cancer Drug Candidates

Rhea-AI Summary

Zapata AI, in collaboration with Insilico Medicine, the University of Toronto, and St. Jude Children’s Research Hospital, showcases a breakthrough in quantum-enhanced generative AI for drug discovery. The research demonstrates the first instance of a generative model running on quantum hardware outperforming classical models in generating viable cancer drug candidates. The study focuses on developing novel KRAS inhibitors, historically considered 'undruggable'. The quantum-enhanced model produced molecules with superior binding affinity, paving the way for hybrid quantum generative AI in drug discovery.

Insights

Medical Research Analyst

The recent findings from Zapata Computing, in collaboration with Insilico Medicine and academic institutions, signify a noteworthy stride in the realm of drug discovery, particularly in targeting the historically challenging KRAS protein involved in cancer. The utilization of quantum-enhanced generative AI models to produce viable cancer drug candidates represents a significant leap forward from traditional computational methods. The ability of these quantum models to generate molecules with superior binding affinity can potentially accelerate the identification of new therapeutics and streamline the drug development pipeline.

From a medical research perspective, the implications are profound. The KRAS protein has been notoriously difficult to target due to its smooth surface and lack of deep grooves where inhibitors typically bind. The breakthrough in identifying novel inhibitors could pave the way for new treatments for various cancers, including lung, colorectal and pancreatic cancers, which are often driven by KRAS mutations. Moreover, the synthesis and validation of these molecules through cell-based assays suggest a tangible advancement from theoretical models to practical applications, potentially shortening the timeline for preclinical drug development.

Market Research Analyst

From a market perspective, the announcement by Zapata AI regarding its quantum-enhanced generative AI models is poised to disrupt the pharmaceutical industry. The integration of quantum computing in drug discovery processes could lead to a significant reduction in both time and costs associated with the development of new drugs. This efficiency gain is crucial, as the traditional drug discovery process is known for its high costs and lengthy timelines, often spanning over a decade and costing billions of dollars.

The potential market for KRAS inhibitors is substantial, given the prevalence of KRAS mutations across various cancer types. Investors and stakeholders in the pharmaceutical and biotechnology sectors are likely to monitor the progress of Zapata AI's technology closely, as its success could influence drug discovery paradigms and the competitive landscape. Furthermore, the strategic partnership with D-Wave Quantum Inc. suggests a commitment to commercializing this technology, which may have a positive impact on Zapata AI's valuation and attractiveness to investors seeking exposure to innovative healthcare solutions.

Financial Analyst

Analyzing the financial implications, the announcement could be a precursor to potential future revenue streams for Zapata AI and its collaborators. The ability to outperform classical models in generating drug candidates is not only a scientific achievement but also a competitive advantage in the market. The early demonstration of these quantum-enhanced models in producing effective drug leads may attract investment and partnerships from larger pharmaceutical companies seeking to harness this technology for their drug discovery efforts.

Investors should note, however, that while the research is promising, it is still awaiting peer review and the path from drug candidate generation to market approval is fraught with regulatory hurdles and requires substantial investment. Nonetheless, the technological edge provided by quantum computing could lead to a reevaluation of the growth prospects for companies like Zapata AI and Insilico Medicine, as well as their partners in academia and industry. As the technology matures and if further validation in clinical settings is achieved, the financial impact could be significant, particularly if the technology can be generalized to other 'undruggable' targets.

The research demonstrates a breakthrough in applying quantum-enhanced generative AI to drug discovery using today’s quantum devices.

BOSTON--(BUSINESS WIRE)-- Zapata Computing, Inc. (“Zapata AI” or the “Company”), the Industrial Generative AI company, today announced that its scientists, in collaboration with Insilico Medicine, the University of Toronto, and St. Jude Children’s Research Hospital have demonstrated the first instance of a generative model running on quantum hardware outperforming state-of-the-art classical models in generating viable cancer drug candidates. 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. The resulting 15 molecules were then 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 a superior binding affinity over the molecules generated by purely classical models.

“This project is an exciting demonstration of how quantum and classical computing can complement each other to deliver an end-to-end solution,” said Yudong Cao, CTO and co-founder at Zapata AI. “The collaboration between Zapata, UofT, St. Jude and Insilico is also a great example of how the startup and university ecosystems can leverage each other's advantages to drive progress. We’re looking forward to taking this research further to move the discovered molecules through the drug discovery pipeline, apply our methodology to other disease targets, and extend our quantum-enhanced generative AI to other industrial use cases with complex design challenges.”

The research is currently published on ArXiv as it awaits peer review. The study is a follow-up to a study published by the team in 2023, in collaboration with Foxconn, that first showed the promise of quantum generative AI for drug discovery.

“This research provides further validation of the potential of Insilico’s generative AI engine, Chemistry42, to be combined with quantum-augmented generative models in order to develop novel therapeutic possibilities for difficult-to-drug targets in cancer and other indications,” says Alex Zhavoronkov, PhD, founder and co-CEO of Insilico Medicine. “This represents an important early step toward a more advanced drug discovery future and we look forward to working with Zapata AI and Alán Aspuru-Guzik at the University of Toronto to further develop these methods."

The news also follows a recent announcement that Zapata AI has entered a new strategic partnership with D-Wave Quantum Inc. (NYSE: QBTS) (“D-Wave"), with an initial focus on building quantum generative AI models that accelerate the discovery of new molecules for commercial applications. “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. “The best part is this is only the beginning. This is the same tech we are developing into a commercial product in our work with D-Wave, which we expect to bring to market quickly given the advanced commercial maturity of Zapata’s generative AI technology and D-Wave’s annealing quantum computing. We’re looking forward to expanding on this research to discover new molecules for drug discovery and other industrial applications.”

“I have always been excited about the potential of AI and quantum computing for drug and materials discovery,” said Alán Aspuru-Guzik, a professor of Chemistry and Computer Science at the University of Toronto, as well as a co-founder and Scientific Advisor of Zapata AI. “We are just starting to see how to integrate quantum computing modules into the drug discovery pipeline. It is great to see that we were able to successfully discover a new compound to inhibit KRAS. Many questions are open. Although everything you can do in this paper could also be done with a classical computer, it is exciting to see 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.”

The research leveraged the QML Suite Python Package available on Zapata AI’s Orquestra® platform, which can be accessed here.

About Zapata AI

Zapata AI is an Industrial Generative AI company, revolutionizing how enterprises solve complex problems with its powerful suite of Generative AI software. By combining numerical and text-based solutions, Zapata AI empowers industrial-scale enterprises and government entities to leverage large language models and numerical generative models better, faster, and more efficiently delivering solutions to drive growth, savings and unprecedented insight. 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. On September 6, 2023, Zapata AI entered into a definitive business combination agreement with Andretti Acquisition Corp. (NYSE: WNNR).

Forward-Looking Statements

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If any of these risks materialize or if assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. While Zapata AI may elect to update these forward-looking statements at some point in the future, Zapata AI specifically disclaims any obligation to do so. These forward-looking statements should not be relied upon as representing Zapata AI’s assessments as of any date subsequent to the date of this communication. Accordingly, undue reliance should not be placed upon the forward-looking statements.

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Zapata AI

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Source: Zapata Computing, Inc.

FAQ

What is the significance of the research collaboration involving Zapata AI, Insilico Medicine, the University of Toronto, and St. Jude Children’s Research Hospital?

The collaboration showcases a breakthrough in quantum-enhanced generative AI for drug discovery, with the quantum model outperforming classical models in generating viable cancer drug candidates.

What were the key findings of the research study on drug discovery?

The study focused on developing novel KRAS inhibitors, historically considered 'undruggable'. The quantum-enhanced generative model produced molecules with superior binding affinity compared to classical models.

What is the outcome of the research collaboration in terms of potential future applications?

The research highlights the potential of hybrid quantum generative AI for drug discovery, aiming to move discovered molecules through the drug discovery pipeline and extend the methodology to other disease targets and industrial use cases.

What strategic partnership did Zapata AI recently enter into, and with whom?

Zapata AI has entered a strategic partnership with D-Wave Quantum Inc. (NYSE: QBTS) to build quantum generative AI models for accelerating the discovery of new molecules for commercial applications.

What are the future plans for Zapata AI based on the research findings?

Zapata AI aims to develop the quantum-enhanced generative AI technology into a commercial product with D-Wave, expecting to bring it to market quickly for drug discovery and other industrial applications.