---
title: "IonQ, AstraZeneca, NVIDIA, and AWS showcase quantum-accelerated drug development workflows"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/243730944.md"
description: "IonQ has successfully developed a quantum-accelerated computational chemistry workflow in collaboration with AstraZeneca, Amazon Web Services, and NVIDIA. This workflow demonstrates a quantum-classical hybrid computing model that enhances the speed and efficiency of drug development, particularly in the Suzuki-Miyaura reaction. By integrating IonQ's Forte quantum processing unit with NVIDIA's CUDA-Q platform, the research team achieved an end-to-end solution time improvement of over 20 times, reducing the expected runtime from \"months\" to \"days.\""
datetime: "2025-06-09T13:39:03.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/243730944.md)
  - [en](https://longbridge.com/en/news/243730944.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/243730944.md)
---

> Supported Languages: [简体中文](https://longbridge.com/zh-CN/news/243730944.md) | [繁體中文](https://longbridge.com/zh-HK/news/243730944.md)


# IonQ, AstraZeneca, NVIDIA, and AWS showcase quantum-accelerated drug development workflows

According to the Zhitong Finance APP, IonQ (IONQ.US) announced that its research project in collaboration with AstraZeneca (AZN.US), Amazon Web Services (AMZN.US), and NVIDIA (NVDA.US) has achieved results, successfully developing and demonstrating a quantum-accelerated computational chemistry workflow. According to IonQ, the designed workflow showcases a quantum-classical hybrid computing model that can provide solutions to complex drug development challenges and is expected to enhance the speed and efficiency of the drug development process.

This collaboration focuses on a key step in the Suzuki-Miyaura reaction, which is a type of chemical transformation reaction used for synthesizing small molecule drugs. By integrating IonQ's Forte Quantum Processing Unit (QPU) with NVIDIA's CUDA-Q platform (accelerated by Amazon Braket services equipped with NVIDIA H200 GPUs) and AWS ParallelCluster services, the research team achieved an end-to-end solution time improvement of over 20 times compared to previous benchmarks.

IonQ noted that this technology reduces the overall expected runtime from "months" to "days" while maintaining computational accuracy. Eric Kessler, General Manager of Amazon AWS's Braket business, stated, "By combining quantum computers on Amazon Braket with AWS's scalable GPU resources, we are assisting AstraZeneca in exploring future applications of quantum computers in accelerating computational chemistry research."

IonQ emphasized that this achievement demonstrates that hybrid quantum computing can overcome computational limitations in high-precision molecular modeling and support the analysis of more complex chemical systems

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