Quantum Computing Accelerates Drug Discovery: 20x Speedup Achieved by IonQ, AstraZeneca & AWS

IonQ, AstraZeneca, Amazon Web Services, and NVIDIA collaborated to demonstrate a quantum-accelerated computational chemistry workflow, achieving a speed increase of over 20 times compared to previous implementations. The research, focused on simulating a Suzuki-Miyaura reaction, a key process in small molecule drug synthesis, integrated IonQ’s Forte quantum processing unit with NVIDIA’s CUDA-Q platform via Amazon Braket and AWS ParallelCluster. This hybrid quantum-classical approach has reduced the expected runtime for complex chemical modelling from months to days, and the results will be showcased at the ISC High Performance conference in Hamburg, Germany, from June 10 to 13, 2025.

A collaborative effort between IonQ, AstraZeneca, Amazon Web Services (AWS), and NVIDIA has accelerated computational time for simulating the Suzuki-Miyaura reaction – a critical step in the synthesis of small molecules used in drug development – by over 20 times. Prior implementations of this simulation required months to complete; however, the new workflow reduces this timeframe to days while maintaining accuracy. This demonstrated workflow exemplifies a practical application of hybrid computing, where quantum processors accelerate specific, computationally intensive stages within broader high-performance computing (HPC) pipelines. The approach recognises that quantum computers will not replace classical systems entirely, but rather augment them by tackling problems where they offer a demonstrable advantage.

Building on previous IonQ demonstrations, this work confirms that hybrid quantum-classical approaches can outperform purely classical methods in specific applications. IonQ’s quantum systems demonstrated scalability by running the most complex chemical simulation on their hardware to date, pushing the boundaries of current quantum capabilities. The ability to model catalytic reactions with increased speed and precision enables more thorough analysis of complex chemical systems, potentially optimising drug development routes and reducing associated costs.

NVIDIA H200 GPUs further accelerated processing within the AWS environment, contributing to the overall performance gain. This successful implementation of this workflow underscores the potential of quantum computing to address computational bottlenecks in pharmaceutical research and development, paving the way for future innovations in drug discovery. This advancement stems from a hybrid quantum-classical workflow integrating IonQ’s Forte quantum processing unit with the NVIDIA CUDA-Q platform, accessed through Amazon Braket and utilising AWS ParallelCluster services.