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Andrew Hopkins, chief executive of  Exscientia.
‘Being a professor is one of the best jobs in the world’ Andrew Hopkins, chief executive of Exscientia. Photograph: Sophia Evans/The Observer
‘Being a professor is one of the best jobs in the world’ Andrew Hopkins, chief executive of Exscientia. Photograph: Sophia Evans/The Observer

Andrew Hopkins of Exscientia: the man using AI to cure disease

This article is more than 1 year old

The British scientist’s company employs artificial intelligence to drastically cut the time of drug development

It was early one morning in 1996 when Andrew Hopkins, then a PhD biophysics student at Oxford University, had a brainwave as he walked home from a late-night lab meeting.

He was trying to find molecules to fight HIV and to better understand drug resistance.

“I remember this idea struck me that there must be a better way to do drug discovery other than the complex and expensive way everyone was following,” he says. “Why couldn’t we design an automated approach to drug design that would use all the information in parallel so that even a humble PhD student could create a medicine? That idea really stuck with me. I remember almost the exact moment to this day. And that was the genesis of the idea that eventually became Exscientia.”

It was to prove a lucrative brainwave. Hopkins set up the company in 2012 as a spinout from the University of Dundee, where he was by then working as a professor. It uses artificial intelligence (AI) systems, which are being trained to mimic human creativity, to develop new medicines. This involves the use of automated computer algorithms to sift through large datasets to design novel compounds that can treat diseases, and to help select the right patients for each treatment.


CV

Age 50

Family Married with a 10-year-old daughter. He met his wife, Iva Hopkins Navratilova, at Pfizer. Her business, Kinetic Discovery, merged with his to create the experimental biology labs at Exscientia.

Education Dwr-y-Felin comprehensive and Neath College in south Wales; degree in chemistry at Manchester; doctorate in molecular biophysics at Oxford.

Pay £415,000

Last holiday Czech Republic to visit his wife’s family at Easter.

Best advice he has been given “My dad worked in a factory. He said to me: ‘Get a good education and get a job you enjoy doing. It’s worth an extra six grand a year.’ And I definitely got a job I enjoy doing.”

Biggest career mistake “It’s too early to tell.” He quotes Miles Davis: “It’s not the note you play that’s the wrong note – it’s the note you play afterwards that makes it right or wrong.”

Words he overuses “Fundamentally”; “the heart of the matter”.

How he relaxes Reading and dog walking. “I am a bibliophile. I immerse myself in books to relax.”


This approach drastically cuts the time of drug development. Hopkins says that for Exscientia’s pipeline it has typically taken 12 to 15 months from starting a project to identifying a drug candidate, compared with four and a half years in the traditional pharmaceutical industry.

The average cost of developing a medicine is $2bn, according to Deloitte’s latest pharma report, and many drugs fail – the failure rate is 90% for medicines that are in early clinical studies (where they are tested on humans).

Typically, pharma companies make 2,500 compounds to test them against a specific disease, while AI enables Oxford-based Exscientia to whittle down that number to about 250, Hopkins says. “It’s a much more methodical approach.”

Last autumn, the Welsh scientist became one of Britain’s richest entrepreneurs, with a paper fortune of £400m after the company achieved a $2.9bn stock market debut on Nasdaq in New York, making it one of Britain’s biggest biotech firms. Hopkins’s stake of nearly 16% is now worth £170m, as the share price has lost 60% of its value in a bloodbath for Wall Street stocks.

Exscientia was part of a transatlantic trend that is defying government attempts to build a biotech powerhouse in the UK. Abcam, a pioneering Cambridge antibody company, recently announced it was moving its stock market listing from the UK to the US. “We are a British company; we choose to be in Oxford because we can attract global talent,” Hopkins says. “But to be seen as a global company, we listed on what is the global technology index, which is Nasdaq. What we have now is an incredibly international shareholder base from across the world.”

The business came up with the first AI-designed drug to enter clinical trials – a treatment for obsessive-compulsive disorder in partnership with Japan’s Sumitomo, although Sumitomo later decided not to proceed with it. The Japanese firm is currently studying another drug developed by Exscientia, for the treatment of Alzheimer’s disease psychosis, in early human trials.

Hopkins, now 50, fell in love with science thanks to an inspirational chemistry teacher. He has worked as a scientist since the age of 16, when he did a stint in industrial chemistry at the Port Talbot steelworks in south Wales, which he says taught him about the benefits of automation in boosting productivity.

He spent nearly a decade at the US drug giant Pfizer, where he was on a “data warehouse” project that led to some of the first machine-learning applications in the pharmaceutical industry, with the findings published in Nature in 2006.

During the subsequent five years at Dundee University, he further researched applying data mining and machine learning to drug discovery. He says “being a professor is actually one of the best jobs in the world” and gave him the freedom to research AI methods at length. He maintains his links with the university, where he is honorary chair of medicinal informatics at the School of Life Sciences.

Exscientia (which means “from knowledge” in Latin) soon moved to the Schrödinger Building at the Oxford science park, and now employs 450 people worldwide, from Vienna to Boston, Miami and Osaka, equally split between AI engineering, chemistry and biology.

It is building a new robotics laboratory at Milton Park near Oxford, focused on the automation of chemistry and biology to accelerate drug development and its declared goal is “drugs designed by AI, made by robot”. Other pharma companies have also introduced some automation into their processes, but generally lab technology is similar to how it was when he was a student in the 1990s, Hopkins says.

The firm is involved in 30 projects, some in partnership with big pharmaceutical companies including France’s Sanofi and the US firm Bristol Myers Squibb (BMS). It is also working with Oxford University on developing medicines that target neuroinflammation for the treatment of Alzheimer’s disease. Among the firm’s solo projects, a cancer drug for solid tumours is about to go into early clinical trials.

Exscientia is also working on a broader coronavirus pill to rival Paxlovid, the Covid-19 treatment made by Hopkins’s former employer Pfizer. This work is funded by a $1.5m grant from the Bill and Melinda Gates Foundation, which took a stake in Exscientia. The company’s other investors include BMS, Celgene (now a BMS subsidiary) and Germany’s Evotec, as well as Japan’s Softbank, the US fund manager BlackRock and the life science investor Novo Holdings.

Hopkins says the team has identified a set of molecules that could work as a broader treatment for Covid-19, new mutations and other coronaviruses, and that there will be more news later this year. The firm is aiming for a low-cost pill that could be distributed globally and given quickly to people who fall ill to prevent serious illness and hospitalisation. Covid-19 infections are rising again in 110 countries and the World Health Organization’s director general, Tedros Adhanom Ghebreyesus, has warned that the pandemic is far from over.

Firms across the pharmaceutical industry have started using AI in recent years. AstraZeneca is investing heavily in it for its entire research and development infrastructure, and GSK has built an AI team of 120 engineers, with plans to reach 160 next year, making it the largest such in-house team in the industry.

AI systems require a lot of computing power and enormous datasets. Their use should boost the number of new drugs being approved every year – typically 40 to 50 in the US – to many more. Hopkins confidently predicts: “This is the way all drugs will be designed in the future. In the next decade, this technology will become ubiquitous.”

The sub-heading of this article was amended on 31 July 2022. An earlier version referred to the employment of AI to “to drastically reduce the speed of drug development” when “cut the time of drug development” was meant.

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