Two shock events rocked Britain’s life sciences sector last week. First, the US company Merck slammed the brakes on a £1 billion London research centre. Then AstraZeneca, the FTSE 100 giant, said it would pause a £200 million investment to expand its research and development arm in Cambridge.

This double blow feels particularly acute in the case of Astra, a home-grown pharmaceuticals champion that has consistently complained about NHS drug pricing policies and a business environment that has grown increasingly challenging.

Merck, known in Europe as MSD, reiterated these concerns, describing the UK as “uninvestable”.

But amid the doom and gloom, could these companies be turning their backs at precisely the wrong moment?

A new generation of drug-discovery companies in the UK are using artificial intelligence to change the game in how medicines are discovered, developed and delivered.

In this regard, ground zero is a one-mile radius around London’s King’s Cross, dubbed the Knowledge Quarter. As a senior scientific adviser to Google DeepMind, I remember the early sparks of the AI explosion — and this has all the same hallmarks.

Revolutionary, AI-powered companies such as Isomorphic Labs and Relation are accelerating the identification of new treatments. They use machine-learning algorithms to predict which compounds will become effective drugs. What once took years of laboratory testing now happens in months through computational modelling.

Companies with AI at the core of their models, in quantitative biology and pharma, are emerging. Hologen, which I helped co-found, is one of this new breed: firms that exploit the power of artificial intelligence to model complex human biology and medical interventions with high precision, making new drugs available for patients rapidly and at lower cost.

Traditional pharmaceutical research takes decades and costs billions. These new ventures are rewriting those rules; they can achieve meaningful milestones at an early stage. A machine-learning algorithm that successfully predicts therapeutic effects might be worth hundreds of millions before any drug reaches clinical trials.

Nor do these firms face the same pricing pressures. They develop platforms and technologies that can be licensed globally. They are not dependent on NHS procurement policies or UK drug-pricing negotiations.

At University College London (UCL), located close to King’s Cross, we have a front-row seat for this. Like other research-intensive universities, my institution has evolved beyond traditional academic research into being a prolific generator of high-growth companies.

• This is the perfect moment for Europe to attract US scientists

Take Autolus Therapeutics. Spun out by UCL Business, the company that takes technologies and innovations developed at the university to market, and led by UCL academics, Autolus harnesses the body’s immune system to fight previously incurable blood cancers. Last November, it gained approval from the US Food and Drug Administration for its breakthrough immunotherapy treating acute lymphoblastic leukaemia. And it has raised $1.1 billion (£800 million), with most of this invested in the UK, including a state-of-the-art manufacturing facility employing 450 people. Other UCL spin-outs have also raised extraordinary sums.

This success is no coincidence.

The proximity to the Francis Crick Institute in King’s Cross creates a unique ecosystem. With world-class basic research taking place metres away from commercial laboratories, the translation of scientific discoveries into viable businesses is accelerated.

We actively create the infrastructure to support entrepreneurship. Incubation programmes provide founders with skills, mentoring, entrepreneurship advice, office space and access to networks.

MSD might be walking away, and Astra is patently unhappy, but global investors have noticed London’s life sciences renaissance.

Venture capital firms traditionally focused on Silicon Valley software companies are opening London offices to gain access to these opportunities. They recognise that AI-driven drug discovery represents a step-change opportunity. It’s no accident that investment in the Knowledge Quarter over the past decade now outpaces other innovation districts such as Kendall Square in Boston. The area hosts 25 per cent of London’s life sciences companies and generates £43.4 billion in economic value annually.

And London as a whole last month overtook San Francisco, New York and Boston for the largest amount of investment raised in life sciences and artificial intelligence: an astonishing $766 million in 2025 so far, according to the data firm Dealroom.

International pharmaceutical companies are quietly acquiring or partnering with these London-based AI companies. They need the technological capabilities that these start-ups possess. There is every chance that MSD will end up licensing technologies developed in the very London ecosystem that it is leaving behind.

Put simply, London may be better positioned for the future of drug discovery than some of the traditional pharmaceutical giants realise.

The government has made life sciences one of its priority sectors, and will be looking closely at last week’s events. Ministers should certainly engage with concerns over research investment and regulatory complexity — but they can also be excited about the remarkable innovation ecosystem developing organically in London.

This quantitative biology revolution doesn’t require subsidies or special economic zones. It needs what London already provides in abundance: world-class research, access to global capital markets, and a critical mass of scientific and entrepreneurial talent.

While we may regret seeing established pharmaceutical companies reconsider their UK commitments, the emergence of this new sector suggests our life sciences future is more promising than headlines suggest.

The next chapter of British medical innovation is being written not in traditional corporate laboratories, but in the dynamic ecosystem where computation meets biology.

Professor Rees is UCL vice-provost (research, innovation & global engagement). He was formerly a senior scientific adviser at DeepMind