Dr Samuel P. Leighton
Senior Clinical Research Fellow
- Division of Psychiatry
- Centre for Clinical Brain Sciences
- Institute for Neuroscience and Cardiovascular Research
Contact details
- Email: sleighto@ed.ac.uk
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Address
- Street
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University of Edinburgh
Chancellor's Building
49 Little France Crescent
Edinburgh BioQuarter - City
- Edinburgh
- Post code
- EH16 4SB
Background
Dr Samuel Leighton is a Clinical Senior Research Fellow at the Division of Psychiatry, University of Edinburgh, and Consultant General Adult Psychiatrist for the Intensive Psychiatric Care Unit at Leverndale Hospital, NHS Greater Glasgow & Clyde, specialising in psychosis and severe mental illness. He holds membership of both the Royal College of Psychiatrists (MRCPsych) and the Royal College of Physicians (MRCP(UK)), reflecting his dual training and commitment to excellence in both medicine and psychiatry. His clinical practice spans early intervention in psychosis and the management of complex mental and physical comorbidity.
Dr Leighton is recognised for advancing clinical prediction modelling, machine learning, and causal inference in psychiatry. His research career began with creating digital tools, including creating NHS Greater Glasgow & Clyde’s "GP Antibiotics" mobile app and anoffline-capable electronic healthcare record and SOP suite for BASICS Scotland launched by John Swinney in 2015, and developing expertise in statistical programming. He has since contributed a series of high‑impact first‑author publications across major journals such as Molecular Psychiatry, The British Journal of Psychiatry, The Lancet Digital Health, Schizophrenia Bulletin Open, and Journal of Neurology, Neurosurgery & Psychiatry. He is a strong supporter of open-access research and always publishes all his analytical code online.
His early work demonstrated that the inflammatory chemokine CXCL8 distinguishes between depressed and non‑depressed individuals. This was followed by the first external validation study predicting outcomes in first‑episode psychosis, which generated international collaboration. Working with colleagues across Edinburgh, Birmingham, and Copenhagen, he helped develop validated prediction models for multiple domains of psychosis recovery. His Chief Scientist Office–funded Clinical Academic PhD Fellowship further produced leading studies on prediction in psychosis, methodological appraisal of existing models, and the association between delirium and later dementia risk.
In 2026, Dr Leighton was awarded a UKRI Mental Health Platform Senior Clinical Research Fellowship at the University of Edinburgh. Building on his preliminary work and linking Edinburgh's Metabolic Psychiatry Hub and Cambridge's ImmunoMIND, this fellowship will: • Identify critical causal mechanisms underlying obesity, including early antipsychotic‑induced weight gain, inflammation and insulin resistance. • Develop and test causal actionable prediction models that estimate individualised treatment effects and forecast counterfactual outcomes, enabling genuinely personalised early interventions. • Validate these models in large real‑world datasets and co‑design them with clinicians and people with lived experience to ensure they are clinically meaningful and implementable. • Use target trial emulation to generate new evidence for early obesity‑focused interventions, including those prioritised by people with lived experience.
Dr Leighton’s work has influenced Scottish Government policy on Early Intervention in Psychosis outcome measures in pathfinder sites across Scotland, and he continues to contribute nationally through Healthcare Improvement Scotland. He co‑authored a book chapter on AI‑driven clinical decision support systems and is an active contributor in the emerging field of causal prediction modelling, with perspective pieces and methodological articles shaping debate around actionability in precision psychiatry. He collaborates widely across the UK and internationally including with Dr Rajeev Krishnadas at the University of Cambridge, the Causality in Healthcare AI Hub led by Prof Sotos Tsaftaris at the University of Edinburgh and with Dr Fani Deligianni at the University of Glasgow. He regularly supervises doctoral, medical, and undergraduate research students.
Alongside his academic and clinical commitments, Dr Leighton is a co‑founder and Director of Ben Èideann Limited, producers of internationally distributed Kosher Scotch whisky, and Cask Flow Limited, a Scotch whisky cask investment company, reflecting his wider interest in technology, entrepreneurship, and the practical translation of ideas into real‑world impact. He also serves as a Director of the Scottish Jewish Archives Centre charity, demonstrating a longstanding commitment to historical research, heritage preservation, and community engagement.
CV
159285.pdf
Qualifications
BMedSci(Hons), MBChB, MRCP(UK), MRCPsych, PhD
Responsibilities & affiliations
- 2025 – Present: Member, Psychosis and Schizophrenia Matrix Advisory Group for evidence-based psychological therapies, NHS Education Scotland.
- 2021 – Present: Member, Healthcare Improvement Scotland Expert Reference Group for Psychosis. Advised on the successful roll-out of early intervention psychosis pathfinder sites in NHS Dumfries and Galloway and NHS Tayside. Successfully advocated for specific outcome measures to be collected based on findings from my PhD research.
Open to PhD supervision enquiries?
Yes
Areas of interest for supervision
I welcome enquiries from prospective MSc and doctoral students interested in projects on risk prediction and causal machine learning in severe mental illness. My current research focuses on obesity and cardiometabolic disease in psychosis, and I am keen to support students wishing to develop skills in prediction modelling, causal inference, and the application of advanced analytical methods to clinically meaningful problems in psychiatry.
Current PhD students supervised
2025 – Present: Co-Supervisor for I Lam Leong, University of Cambridge. Project Focus: Causal modelling of physical health outcomes with Clozapine in psychosis.
Research summary
Causal prediction and precision psychiatry Developing fully actionable clinical prediction models that identify intervenable causal factors to support personalised treatment decisions in psychosis and severe mental illness. This includes methodological innovation using causal mediation, counterfactual prediction, and modern evaluation frameworks.
Psychosis-related cardiometabolic risk Investigating mechanisms and prevention of antipsychotic-induced obesity, insulin resistance, and inflammation, and developing tools to target interventions to individuals at highest risk at the right time.
Machine learning and clinical prediction modelling Designing, validating, and critically evaluating multivariable prediction models for outcomes such as remission, recovery, and quality of life in first‑episode psychosis. Particular interests include methodological rigour, reproducibility, and external validation across diverse cohorts.
Target Trial Emulation and real-world evidence Applying causal methods such as Target Trial Emulation to routinely collected healthcare data to examine real-world treatment effects relevant to psychiatry, especially for cardiometabolic interventions in psychosis.
Digital health and medical AI implementation Translating research into clinical tools, including development of mobile apps and contributions to medical‑device–regulated prediction systems. Strong commitment to open science, transparent modelling, and safe deployment of clinical decision support software.
Big‑data psychiatry and long‑term outcomes Using electronic health records and population-scale datasets to investigate trajectories of severe mental illness, including cognitive decline and dementia risk following delirium and psychosis.
Research culture, teaching, and mentorship Supporting the research community through supervision of doctoral and undergraduate students, mentoring early‑career clinicians, delivering workshops on prediction modelling and machine learning, and peer reviewing for leading journals.
Affiliated research centres
Current project grants
04/2026 – Present: Award Holder/Fellow, MRC Grant (UKRI4402): "Causal actionable prediction for early cardiometabolic intervention in psychosis - targeting obesity". Awarded: £246,228.82.
07/2025 – Present: Lead Clinical Partner to Dr Fani Deligianni PI, UKRI Causality in Healthcare AI Hub ‘New to Causality’ Call. Project: "Causal Survival Models for Psychosis: Insights into Risks and Prognosis". Awarded: £62,843 (funding used for a postgraduate research assistant starting March 2026 under my supervision). Currently focussed on Target Trial Emulation of antipsychotic use, QTc prolongation and ICU mortality.
01/2025 – Present: Principal Investigator, NHS GG&C Endowment Fund. Awarded: £14,762. This funded access to all historical linked electronic healthcare record data for patients accepted to the NHS GG&C Esteem early intervention psychosis service between 2015 and 2025 in the West of Scotland Safe Haven.
Past project grants
08/2019 – 03/2023: Principal Investigator, Clinical Academic Training Fellowship, Chief Scientist Office, Scotland (CAF/19/04). Awarded: £238,177.