Population Health Sciences Statistical Consultancy

Together, our team members have extensive experience working on a wide range of research projects including clinical trials and observational studies using patient and health services data, national surveys and various research studies (like the UK birth cohorts, CPRD, UK Biobank, Lambeth DataNet, ONS data and more). For examples of some of our studies please see our portfolio or click on members’ King’s Pure profiles below.

If you would like to request help, we suggest you fill out one of the two forms below to help us understand what you need help with and a team member will get back to you. Our consultancy service works on the principle of collaboration.

For informal enquires, you can reach out to us by emailing: gsttresearch-support@kcl.ac.uk

Our School, Department and Group pages:

• School of Life Course & Population Health Sciences
• Department of Primary Care & Data Science
• Unit for Medical Statistics

Our Team:

Professor Abdel Douiri

Abdel leads Medical Statistics in the School of Life Course & Population Health. He is an applied mathematician by background and involved in a variety of clinical research with world leading research groups in UK and France, and in both academia and industry. His research interests include epidemiology of long-term conditions, predictive medicine and clinical trials design and methodology. Abdel joined the school in 2009 and teaches statistics and epidemiology for both undergraduate medical students and postgraduate Public Health programmes. He is the director of the statistical consultancy services at KCL, and he is also a statistical advisor with the Research Design Service London, Biomedical Research Centre, and King’s College Hospital. He is a Fellow of the Royal Statistical Society and active member with quality improvement section. Abdel is a statistical editor and health economic advisor with Thorax.

Dr Amal Khanolkar

Amal is a social and lifecourse epidemiologist with a keen interest in methodology (especially longitudinal methods), specialising in health inequalities and noncommunicable disease epidemiology. His strengths lie in observational epidemiology and mixed methods, data management and analysis, teaching (basic and advanced epidemiology and biostatistics, methods for health inequalities research and social medicine), project management and supervision of research projects (specifically MSc dissertations and PhD projects). In the past few years, he has developed a strong interest in non-communicable diseases, mental health and specifically in comorbidity between mental and physical health and associated inequalities, especially in marginalised and minority groups. He has significant experience working with the UK birth cohort studies (e.g., Millennium Cohort Study, 1970 British Cohort Study, 1946 National Survey of Health & Development) and national surveys like the Adult Psychiatric Morbidity Survey. Amal is also part of the Stroke Research Group in the Department of Primary Care & Data Science where he conducts research on health inequalities in stroke care and outcomes.

Dr Dina Farran

Dina is a Research Fellow in Early-Phase and Digital Health Trial Statistics at King’s College London, with a multidisciplinary background spanning biostatistics, epidemiology, artificial intelligence, digital health and mental health research. She holds a PhD and an MPH from King’s and has experience in the design, analysis and interpretation of clinical trials and observational studies, including longitudinal data analysis, statistical modelling and prediction, and analysis of complex health datasets using R. Her expertise also includes systematic reviews and meta-analyses, mixed-methods research, and the application of AI and digital technologies to health research. She has extensive experience leading multidisciplinary research projects and developing collaborations across academic, clinical and applied settings.

Bolaji Coker

Bolaji is a Senior Data Manager and Chartered Statistician working jointly between King's College London (KCL) and Guy's and St Thomas' NHS Foundation Trust. He specializes in clinical trials data management, medical statistics, and healthcare informatics. With a multidisciplinary background spanning engineering, bioinformatics, and applied statistics, he plays a key role in managing data registries for major medical research projects. His collaborative research focuses on developing prediction models, implementing federated data analysis, and optimizing outcomes for clinical registries.

Professor Salma Ayis

Salma Ayis a Professor in Medical Statistics at the School of Life Course & Population Health Sciences, King’s College London. Interested and experienced in the application of advanced statistical and econometrics techniques, to investigate the progression of prognostic factors and outcomes in various chronic conditions.

Professor Yanzhong Wang

Yanzhong Wang is Professor of Statistics in Population Health and Head of Medical Statistics at Department of Primary Care & Data Science, King’s College London. After earning his PhD in statistics from the University of Glasgow in 2004, he first worked at Cambridge University on cancer genomics and then Glasgow University on cardiovascular epidemiology and clinical trials before joining King’s in 2009. His current research focuses on target trial emulation (TTE), pharmacoepidemiology, clinical prediction models, and epidemiology of stroke & multimorbidity. He is a module leader for the Master of Public Health (MPH). He leads high-impact research on stroke epidemiology and prognostication, widely reported by the Daily Mail, Telegraph, Guardian and Sky News. He is a director of statistical consultancy providing statistical support to clinical researchers at King's Health Partners. 

To help us understand the kind of help you require, please choose one of the two forms below. You will need to provide brief information on the data type and study design, data type and source, ethical clearance, main exposure(s) and outcomes(s), approximate timeline for the project. We aim to respond within five working days.

• For observational studies including service evaluations:
  Form A (coming soon!)
• For clinical studies:
  Form B (coming soon!)

For informal enquires, you can reach out to us by emailing: gsttresearch-support@kcl.ac.uk

Population Health Sciences Statistical Consultancy,
School of Life Course & Population Health Sciences, 
King’s College London, 
Addison House,
Guy’s Campus, 
London SE1 1UL