The annual CCAIM Symposium showcased cutting-edge research from across the CCAIM community while bringing together experts from academia, healthcare and industry to discuss the future of AI in biomedicine.
On 10 June 2026, students, researchers, faculty members and industry partners from across the Cambridge Centre for AI in Medicine (CCAIM) gathered for the annual CCAIM Symposium.
The event provided an opportunity to showcase the breadth of research taking place across the centre while bringing together experts from academia, healthcare and industry to discuss some of the most pressing challenges at the intersection of artificial intelligence, machine learning and medicine.
Opening the symposium, Prof Mihaela van der Schaar highlighted two themes that would define the day: building AI for bioscience and understanding how AI can help address the complexity of modern clinical trials.
Building AI for Bioscience
The first half of the sessions focused on how advances in AI are enabling new approaches to biological discovery.
Across talks spanning genomics, infectious disease, drug discovery and scientific reasoning, speakers demonstrated how machine learning is increasingly helping researchers uncover patterns within complex biological systems and generate new scientific insights.
Professor James Lee (The Francis Crick Institute) explored how computational methods are helping researchers translate genetic discoveries into a deeper understanding of autoimmune disease biology. By identifying how genetic risk variants influence disease mechanisms, this work aims to support the development of more effective treatments for conditions such as Crohn’s disease.
Professor David Bentley (University of Colorado Anschutz, CCAIM Faculty) presented work using machine learning to investigate the dynamics of human gene transcription, illustrating how AI can reveal previously hidden biological signals and generate new hypotheses for experimental validation.
The keynote from Dr John Lees (EMBL-EBI) challenged attendees to think critically about where AI can have the greatest impact in medicine. Drawing on examples from microbial genomics, antibiotic discovery and foundation models, he emphasised the importance of starting with meaningful biological questions rather than applying AI for its own sake.
Other presentations from CCAIM affiliated students and postdocs highlighted emerging approaches for predicting cellular behaviour, accelerating drug discovery and translating AI-generated hypotheses into interpretable scientific equations, demonstrating the growing role of AI throughout the scientific discovery process.
Reimagining Clinical Trials
The second half of the sessions shifted focus towards how AI can support the translation of scientific discoveries into clinical impact.
Across presentations from CCAIM researchers and external collaborators, speakers explored topics ranging from autonomous clinical AI systems and healthcare decision-making to structural biology approaches that could enable next-generation drug discovery. For example, Dr Radoslav Enchev (The Francis Crick Institute) discussed scalable experimental-computational workflows for structural biology, while Dr Tom Callender (University of Cambridge, CCAIM Faculty) examined the challenges of evaluating and regulating increasingly autonomous AI systems in healthcare.
Together, these talks highlighted both the opportunities and challenges associated with deploying AI across the biomedical pipeline, from discovery science through to clinical care and clinical research.
Bringing Together Diverse Perspectives
Beyond the research presentations, the symposium also featured two panel discussions on AI for Biodiscovery and AI for Clinical Trials.
Bringing together researchers, clinicians and industry leaders, the discussions highlighted one of CCAIM’s defining strengths: creating opportunities for experts across the biomedical ecosystem to engage directly with one another. While these communities often work on different timescales and face distinct challenges, the panels demonstrated a shared ambition to accelerate scientific discovery and improve patient outcomes.
The AI for Biodiscovery panel explored how advances in generative AI are beginning to reshape the scientific process itself. Panellists discussed the growing use of AI as a research tool, from hypothesis generation to experimental design, and reflected on how attitudes towards AI in science have evolved. Rather than asking whether researchers use AI, the conversation has shifted towards understanding how they use it, and how it can be applied effectively and responsibly to produce better scientific outcomes.
The AI for Clinical Trials panel focused on how AI could help transform one of the most complex and resource-intensive stages of medical innovation. Discussions highlighted the need for better decision-making throughout the clinical trial lifecycle, moving beyond traditional measures of statistical significance towards approaches that prioritise clinical impact. Panellists also emphasised the importance of greater collaboration across academia, healthcare systems, industry and regulators, alongside improved data sharing and transparency. Looking ahead, the discussion explored how AI could make clinical trials more adaptive and efficient, helping researchers identify unsuccessful trials earlier and focus resources on interventions with the greatest potential to benefit patients.
Throughout both discussions, a common theme emerged: the future of AI in medicine will depend not only on advances in algorithms, but on collaboration between those developing new technologies, generating biological insights, delivering healthcare and translating discoveries into real-world impact.
Looking Forward
The 2026 CCAIM Symposium showcased the breadth of expertise across the CCAIM community and its collaborators, highlighting how AI is increasingly shaping both biological discovery and clinical research.
From understanding the mechanisms of disease to rethinking the future of clinical trials, the symposium demonstrated the potential of interdisciplinary collaboration to tackle some of the most important challenges in medicine.
We would like to thank all speakers, attendees and partners for contributing to another successful symposium and look forward to continuing these conversations throughout the year.