The Editorial Board of Cambridge Prism: Precision Medicine is delighted to announce a call for papers for an upcoming special issue focused on "Demystifying AI’s role in Precision Medicine." 

The special issue aims to explore the transformative potential of artificial intelligence in the healthcare landscape, with a focus on elucidating its capabilities, challenges, and ethical considerations in precision medicine. As precision medicine seeks to customise healthcare approaches based on individual genetic, environmental, and lifestyle characteristics, AI is positioned as a key driver in analysing complex biological data, identifying novel diagnostics, and personalising treatment strategies.

While AI in precision medicine holds significant promise, demystifying its capabilities and limitations is crucial for effective integration into healthcare. AI can facilitate tailored medical treatments by analysing vast datasets to uncover patterns and predictive insights, thereby improving diagnostics, treatment plans, and patient outcomes. However, there is a risk of hype and fear due to overestimation of AI’s capabilities or potential adverse impacts, leading to unrealistic expectations, ethical concerns, and resistance from healthcare professionals.

This special issue invites submissions on key themes including the practical applications of machine learning algorithms in patient stratification, the role of AI in drug discovery and development, and the enhancement of clinical decision-making processes through data-driven insights. 

The Editors aim to address challenges such as ensuring data privacy, mitigating algorithmic bias, and integrating AI into existing healthcare infrastructures, with an emphasis on the need for transparent AI systems and equitable access to advanced healthcare technologies.  Work that explores data governance, ethics and policy angles that could help accelerate integration as well as acceleration of use of health data will also be welcomed. 

Clear communication about what AI can and cannot do, along with discussions about the challenges of adoption and integration is essential. Educating stakeholders—including clinicians, patients, and policymakers—about AI's practical applications can foster trust and promote informed decision-making. This special issue aims to support education and engagement by exploring AI's transformative potential in advancing precision medicine and optimising healthcare delivery.

We invite original research articles, reviews, case studies, and perspective pieces that engage with, but are not limited to, the following themes:

1. AI’s role in transforming the development and testing of precision therapeutics
2. Development, Adoption, and Deployment of AI in Diagnostics
3. The application of AI in Clinical Practice
   • Innovations and case studies on AI integration in clinical settings.
   • Impact of AI on patient outcomes and decision-making processes.
4. Emerging Trends Driving the Future of AI in Healthcare:
   • Breakthrough technologies and methodologies.
   • Projections for AI advancements influencing life sciences and  healthcare.
5. Challenges in Developing AI for Precision Medicine:
   • Addressing biases and ensuring ethical AI solutions.
   • Data security, privacy, and fairness.
6. Challenges in Deploying AI in Healthcare Settings:
7. Issues of integration, scalability, and procurement.
8. Overcoming operational and regulatory hurdles.
9. Public and profession support for AI

Submission deadline: 1 July 2025

Lead Editor

Dr Claire Bloomfield, Scenario Director Corporate Development, Insitro, UK

As the Senior Director of International Corporate Development at insitro, I lead the development and execution of novel collaborative data partnerships that enable AI-driven drug discovery. With over 18 years of experience in the health data and life sciences sector, I have a passion for creating and delivering innovative solutions that improve health outcomes and accelerate research. Previously, I was the Director and SRO for the Data for R&D Programme at the NHS England Centre for Improving Data Collaboration, where I oversaw the strategy and delivery of NHS and Government investments in health data for research and innovation. Before joining the NHS, I was the CEO of the UK National Centre of Excellence for Artificial Intelligence in Medical Imaging (NCIMI) at the University of Oxford, where I led a consortium of 14 hospitals, 13 industry partners, and world-leading academic researchers in AI, imaging, data science, and ethics. My academic background is in neuroscience, and I hold a DPhil from the University of Oxford assessing preclinical models of schizophrenia, and several executive education certificates from the Said Business School.

Guest Editors

Dr Ken Sutherland - Canon Medical Research Europe Ltd., UK

Ken Sutherland is a Director of the Board and is also Assistant to the Chief Technology Executive of Canon Medical Systems in Japan.

He serves as an industry representative on the MRC’s Translational Research Group, advisor to EPSRC and has previously served as a lay member of the Court of Glasgow University and as an advisory board member of the Scottish Lifesciences Association. He is a Fellow of the Royal Society of Edinburgh and was recently elected as a fellow of the Royal Academy of Engineering.

Ken studied Electronics and computer science at Edinburgh University and gained a PhD in image analysis and four years postdoctoral research experience in medical image analysis. He returned to Edinburgh in August 2007 to join Canon Medical as R&D General Manager following his previous post of Operations Director for a European multinational where he ran their imaging R&D facility in Cambridge.

Professor Sotirios A. Tsaftaris - University of Edinburgh

Sotirios A. Tsaftaris is currently Chair (Full Professor) in Machine Learning and Computer Vision at the University of Edinburgh. He holds the Canon Medical/Royal Academy of Engineering Chair in Healthcare AI (since 2019).

Since 2024, he is the Director for the EPSRC-funded Causality in Healthcare AI Hub with Real Data (CHAI). He is an ELLIS Fellow of the European Lab for Learning and Intelligent Systems (ELLIS) of Edinburgh’s ELLIS Unit. Since 2023 he is a visiting researcher with Archimedes RC a research centre of excellence in AI in Athens, Greece. Between 2016 and 2023 he was a Turing Fellow with the Alan Turing Institute.