The MHRA leads three new government-backed projects using AI-driven approaches to make medicines safer and bring treatments to patients more quickly.
A new study will use artificial intelligence (AI) and NHS data to predict side effects from drug combinations before they reach patients. This is among three Medicines and Healthcare products Regulatory Agency (MHRA) projects backed by government funding, announced today (22 October 2025), to modernise how medicines and medical technologies are tested and approved - ensuring faster access for patients, while maintaining the highest safety standards.
Millions of people in the UK take several medicines every day. In England, around 1 in 7 people (8.4 million) are regularly prescribed five or more medicines . While most combinations are safe, some can interact in ways that cause harmful side effects. These can mean repeated GP visits, changes to prescriptions, or even hospital stays before treatments are adjusted - adding strain for patients, carers and the NHS.
Scientists from the MHRA, working with PhaSER Biomedical and the University of St Andrews, and backed with £859,650 funding from the UK Government's Regulatory Innovation Office's AI Capability Fund - which supports regulators to test new, faster ways of bringing safe innovation - will use AI to help spot these interactions. The system will look for patterns in anonymised NHS data showing how different medicines behave when used together, focusing on cardiovascular medicines. These signals will then be tested in the lab using human-based models that mimic how drugs are processed in the body.
The goal is a reliable tool that doctors can use to better understand how combinations of medicines affect people in real life, improving how treatments are prescribed together so patients get the safest and most effective care, tailored to them, more quickly. This personalised approach could help prevent some of the side effects linked to medicines, which are estimated to cause around one in six hospital admissions in England and cost the NHS more than £2 billion every year .
The tool could also transform how new medicines are discovered and tested. Around nine in ten promising drugs fail late in development because early trials can't always predict how they'll work in real patients. Using AI and real-world health data that reflect the diversity of patients and how they take medicines, scientists can spot risks and successes earlier, giving regulators stronger evidence for faster, well-informed decisions. This can cut delays and costs for developers, bring new treatments to patients sooner, and strengthen the UK's global position in life sciences innovation.
The project will also produce practical guidance for developers on using AI and real-world data alongside traditional trial evidence, helping the field develop.
Lawrence Tallon, Chief Executive of the MHRA, said:
"People are living longer and managing more conditions, often with multiple medicines, so our safety systems must keep up. By using new tools and real-world health data, the MHRA is delivering practical solutions that protect patients and speed access to effective treatments, making regulation safer, smarter and more inclusive. Government backing lets us drive this work forward and set an example internationally. Together with piloting new approaches to improve consistency and efficiency across the regulatory lifecycle, from early advice to licensing, we will show how modern regulation can deliver for patients and the life sciences sector."
Julian Beach, Interim Executive Director Healthcare Quality and Access at the MHRA, supervising the study, said:
"The launch of this project will demonstrate how AI and advanced modelling can be built into drug development to design smarter, more efficient clinical trials. By understanding how medicines work together, we can generate stronger, more realistic evidence to support new treatments and ultimately reduce avoidable harm. We encourage researchers and industry to share pilot data, methods or ideas, and
