Side effects from drug interactions to be predicted by AI before reaching patients
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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...Request free trial
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 get in touch with us early so we can work together to develop these approaches and shape the next generation of clinical trials.” Chris Wardhaugh, Chief Executive of PhaSER Biomedical, said: “This collaboration demonstrates a shared commitment between regulators and innovators to redefine how medicines are developed. Our model provides a uniquely human-relevant lens on drug metabolism and safety, while our work with the MHRA ensures that these insights can translate directly into regulatory practice.” AI to speed up scientific advice and approvals – £1,000,000 awarded The MHRA will also pilot the use of AI-assisted tools to support experts in scientific advice, clinical trial assessments and licensing decisions. The system aims to improve efficiency and consistency while keeping all final decisions in human hands. Funded by £1,000,000 via the Regulators' Pioneer Fund, the AI for Regulatory Insight, Safety, and Efficiency (ARISE) programme will demonstrate how regulators can responsibly use AI to strengthen medicine safety, streamline the development of new treatments and enable faster access to new therapies. This programme also contributes to the goals of the Life Sciences Sector Plan to create faster, risk-proportionate, and predictable routes to regulatory approval. Synthetic data – £259,250 awarded Another MHRA project will pilot the use of synthetic (artificial) patient data to support clinical trials in cancer, inflammatory bowel disease and rare paediatric seizure conditions. Previous work suggests synthetic data can be used to strengthen the evidence from clinical trials in rare and underrepresented populations with smaller patient populations. This project will involve a regulatory sandbox that helps translate this into regulatory policy. Funded by £259,250 from the Regulators' Pioneer Fund, this work will test how synthetic data can safely and responsibly supplement evidence for regulatory decisions. Driving innovation and patient safety Together, these three projects – supported by over £2 million in government funding – represent a step change in how medicines and medical technologies are approved and regulated in the UK. By embedding AI and new data approaches into regulatory science, the MHRA is making sure new treatments reach patients faster, while maintaining the highest safety standards. The findings will help shape the next generation of clinical trials and approvals and inform upcoming guidance, including the MHRA's National Commission into the Regulation of AI in Healthcare which brings together patient advocates, clinicians, regulators, and technology companies to advise the MHRA on AI regulation in healthcare. The work also supports the government's ambition to make the UK the most AI-enabled health system in the world, delivering highly personalised care as set out in the 10 Year Health Plan for England, and reinforcing the UK as a global hub for life sciences innovation under the Life Sciences Sector Plan. Notes to editors
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