Practical improvements to the performance of quantum simulation for drug-protein binding

药物-蛋白质结合量子模拟性能的实际改进

• 批准号: 10001505
• 金额: $ 41.6万
• 依托单位: RIVERLANE LTD
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10001505
• 关键词: Practical; improvements; performance; quantum; simulation

The process of discovering and testing new drugs is very expensive and takes a long time. The average cost of discovering a new drug and bringing it to market has tripled since 2010, reaching almost $3bn in 2018\. Current methods for discovering new drugs are unreliable and involve a 'trial-and-error' approach. Pharmaceutical companies want to reduce the cost and shorten the time it takes to develop a new drug.We want to solve this problem by using quantum computers to speed up the process of drug discovery. This is a fundamentally different approach to using normal or so-called 'classical' computers. In this project, we will use the properties of quantum systems to make big improvements in computational speed and accuracy. Pharmaceutical companies could then identify, screen and simulate new drugs on a computer rather than using expensive, trial-and-error approaches in the laboratory.Some early work has been completed using quantum computers in drug discovery, but there are still many errors using this approach. Another problem is the quantum industry, which is currently very fragmented as it is in such an early stage of development. This project brings together the UK's leading quantum software and hardware companies -- Riverlane and Rigetti UK -- to help solve the technical challenge of reducing errors in quantum computing. We will work together to fine-tune the algorithms and methods used in quantum computing by developing an 'error mitigation layer'. We will also build a computer platform that can be used by the pharmaceutical industry to screen new drugs. To check that it works, we will integrate our new technology into the existing workflows of UK pharmaceutical company, Astex, a global leader in cancer drug discovery.The UK is home to several large pharmaceutical companies. It is also a global leader in quantum technology. Our project therefore has real national value. By bringing Riverlane, Rigetti UK and Astex together, our ambition is to take a first step towards creating a game-changing quantum product for UK pharmaceutical companies to make their drug discovery easier, quicker and cheaper. This project will also allow Riverlane and Rigetti UK to accelerate the development of their software and hardware products to strengthen the UK quantum industry.

发现和测试新药的过程非常昂贵，而且需要很长时间。自2010年以来，发现一种新药并将其推向市场的平均成本增加了两倍，2018年达到近30亿美元。目前发现新药的方法并不可靠，而且需要一种“反复试验”的方法。制药公司希望降低成本，缩短开发新药所需的时间，我们希望通过使用量子计算机来加快药物发现的进程来解决这个问题。这是一种与使用普通或所谓的“经典”计算机完全不同的方法。在这个项目中，我们将利用量子系统的性质在计算速度和精度方面做出很大的改进。然后，制药公司可以在计算机上识别、筛选和模拟新药，而不是在实验室使用昂贵的反复试验的方法。一些早期的工作已经完成，使用量子计算机进行药物发现，但使用这种方法仍然存在许多错误。另一个问题是量子产业，由于处于如此早期的发展阶段，该产业目前非常分散。该项目汇集了英国领先的量子软件和硬件公司--Riverlane和Rigetti UK--以帮助解决减少量子计算中的错误的技术挑战。我们将共同努力，通过开发“误差缓解层”来微调量子计算中使用的算法和方法。我们还将建立一个可供制药行业使用的计算机平台，用于筛选新药。为了确保它起作用，我们将把我们的新技术整合到英国制药公司ASTEX的现有工作流程中，ASTEX是全球抗癌药物发现的领先者。英国有几家大型制药公司。它也是量子技术的全球领先者。因此，我们的项目具有真正的国家价值。通过将Riverlane、Rigetti UK和Astex整合在一起，我们的雄心是朝着为英国制药公司创造一种改变游戏规则的量子产品迈出第一步，使他们的药物发现更容易、更快、更便宜。该项目还将使Riverlane和Rigetti UK加快其软硬件产品的开发，以加强英国的量子产业。