IBM announced on April 16 that its quantum computing systems played a key role in several international research projects focused on healthcare and biology. The announcement follows the conclusion of the Quantum for Bio (Q4Bio) Supported Challenge Program, established by Wellcome Leap to identify and demonstrate quantum algorithms with potential applications in human health.
The Q4Bio program is significant because it encourages teams to develop solutions for real-world medical problems using quantum technology. With $40 million awarded since its launch in 2023, the initiative required teams to demonstrate algorithms running on more than 50 qubits with circuit depths between 1,000 and 10,000 gates. Five out of six Phase III finalist teams used IBM’s quantum hardware for their work.
One winning project led by Algorithmiq, Cleveland Clinic, and IBM simulated key processes in photodynamic therapy—a cancer treatment involving light-activated drugs—using up to 100 qubits. Sabrina Maniscalco, CEO and co-founder of Algorithmiq, said: “This work provides one of the clearest indications to date that quantum computing can begin to impact real, chemically relevant problems, rather than simplified benchmarks. IBM’s quantum systems enabled execution of circuits at scales approaching 100 qubits and supported the continuous, end-to-end validation loop required to identify real bottlenecks and ensure robustness of the approach.” Dr. Vijay Krishna from Cleveland Clinic added: “Q4Bio showed that when teams with complementary expertise work toward a common goal, they can make meaningful progress on problems that no single discipline can solve alone.”
Other finalists included researchers from Oxford University and Sanger Institute who encoded a whole genome onto an IBM Quantum Heron r2 processor—a world first according to James McCafferty at Sanger Institute—and Infleqtion’s team which identified novel cancer biomarkers using hybrid classical-quantum methods. Fred Chong from Infleqtion said: “Our work has already identified novel cancer biomarkers for clinical evaluation, and future quantum machines will allow us to discover even more promising biomarkers that we hope will improve treatment outcomes.”
Additional collaborations involved Stanford University studying biochemical reactions fundamental to cellular processes using IBM hardware; while a team led by University of Nottingham explored covalent inhibitor design relevant for drug discovery programs targeting diseases like Myotonic dystrophy type 1.
Jay Gambetta, director of IBM Research concluded: “It’s encouraging to see so many research teams implementing QCSC workflows, where classical and quantum resources work together to achieve what neither can alone.” These results suggest that quantum computing is transitioning from experimental demonstrations toward practical tools supporting biological research.
