Data Science and Population Health

This Theme’s Focus

Genomics in healthcare
Therapeutic target prioritisation
Addressing multiple long-term conditions through data-driven studies
Risk prediction and screening

Large population studies investigating the links between genetics and disease, such as the 100,000 Genomes Project, NIHR BioResource and the UK BioBank have created huge amounts of data on health and disease and further studies large and small continue to create valuable data every day. The rapidly increasing availability of complex health data provides an exceptional opportunity to transform health outcomes at individual and population levels as well as to enhance healthcare efficiency.

The goal of the Data Science and Population Health theme is to make use of these enormous amounts of data to improve early detection and prevention of heart attacks, strokes, dementia, infections and cancers in the UK over the next decade. Working with other themes across the NIHR Cambridge BRC, we will develop, evaluate and distribute complementary computational systems and tools that can identify and interpret important, usable patterns hidden in large, diverse and constantly growing biomedical data sets.

Our efforts and tools will help us to understand the early origins of disease, identify promising targets for intervention and untangle the complexities of multiple long-term conditions, ultimately improving the lives.

We are building the infrastructure, expertise and oversight framework that will allow us to maintain and enhance our international leadership in this field, as well as reflect our strong values: promoting equity and avoiding bias in healthcare, embedding patients and public representatives in our leadership and operational structures, and ensuring our research benefits underserved and marginalised communities.

We work highly collaboratively with partners like, i.e. EMBL-European Bioinformatics Institute (key partner for initiatives like the Polygenic Risk Score Catalog) and Health Data Research UK (in particular, the Molecules to Health Records and Big Data for Complex Disease Driver Programmes).

Theme Leads

Michael Inouye

Professor of Systems Genomics & Population Health
Email: mi336@medschl.cam.ac.uk

Professor Angela Wood

Professor of Health Data Science in the Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, Cambridge.
Email: amw79@medschl.cam.ac.uk

Meet our researchers

The Data Science and Population Health theme will address two overarching research questions:

How can research in biostatistics, machine learning and artificial intelligence (AI) be used equitably and at scale to improve healthcare in diverse settings?

How can a “molecule to e-health record” strategy combining multiple kinds information (such as genetics, imaging, test results and health records) from millions of UK individuals, improve understanding, treatment and prediction of multiple long-term conditions?

For more Information

You can watch previous talks from our research teams on YouTube.

Read about ‘Behind the Curtain’ where a piece of research was turned into theatrical production and post-show discussion looking at the health information hidden in your DNA. The piece is available to watch online or you can read the paper.

Working with patients and the public

Researchers in this theme work closely with patients and members of the public to strengthen lay participation in their research.

Listen to the podcast below for the latest in Health Data Insights.
The theme has its own PPIE group. If you’d like to find out more about this or would like to join, please click on our Ongoing PPIE Opportunities page for contact details.

Podcast: Health Data Science Insights – Cambridge

Passionate about transforming health, researchers from Population Health and Data Science are hosting a podcast for health data science researchers and the public called ‘Health Data Science Insights – Cambridge’. Based in the Cardiovascular Epidemiology Unit at the University of Cambridge, they collaborate nationally and internationally and explore topics like Trusted Research Environments, ethical considerations, AI and multiomics.

Join Dr Alexia Sampri, Dr Elena Raffetti, Dr Elias Allara as they engage with leading experts and explore all things health data science.

You can listen to the ‘Health Data Science Insights – Cambridge’ podcast on popular platforms like Apple Podcasts Spotify and Podscan

Latest News

Genomics lab reading samples - NIHR Cambridge BRC image

Research collaboration offers new polygenic score insights in type 2 diabetes and related co-morbidities

March 11, 2025

An on-campus collaboration between NIHR Cambridge BRC-funded…

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Polygenic Score Catalog increases diversity and usability of genetic data

October 3, 2024

A paper highlighting changes to the Polygenic Score (PGS)…

Photo by National Cancer Institute on unsplash.com

‘Gene misbehaviour’ widespread in healthy population

July 25, 2024

NIHR Cambridge BRC researchers have been involved in…

Photo of Angela Wood - wearing a blue top and necklace

Prestigious NIHR Research Professorship awarded to Cambridge researcher

November 23, 2023

Congratulations to co-theme lead for the NIHR Cambridge BRC Data Science and Population Health theme, Professor Angela Wood, who has been awarded an NIHR research professorship.

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Cambridge researchers listed among world’s most influential researchers

November 21, 2022

Congratulations to our NIHR Cambridge BRC theme leads who have been named in the Clarivate listings of the ‘world’s most influential researchers.’

Person typing code into laptop: Free for use under the Pixabay Content Licence.

World first for AI and machine learning to treat Covid patients worldwide

September 15, 2021

Researchers across the world have used artificial intelligence to predict Covid patients’ oxygen needs on a global scale.

Previous Next

Data Science and Population Health Case Studies

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Predicting risk of cancer, heart attacks and other diseases using DNA

October 16, 2024

The human genome (the complete set of genetic information in…

Image of risk calculator to predict risk of heart attack and stroke

New risk calculators to predict people at high risk of heart attacks and stroke

October 16, 2024

Cambridge-led working groups and the European Society of…

Informing healthcare policy with COVID-19 data

October 16, 2024

The SARS-CoV-2 virus has resulted in more than 235 million…

Screening and Treatment for Abdominal Aortic Aneurysm

October 16, 2024

Cambridge researchers led a randomised trial to see whether…

Laptop with notepad: Image by StartupStockPhotos from Pixabay.

Reviewing the NHS Health Check programme

October 16, 2024

The NHS Health Check programme was introduced across England…

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Data Science and Population Health Publications

Using machine learning to model older adult inpatient trajectories from electronic health records data

January 17, 2023

Factors Associated with Significant Weight Loss in Hospitalised Patients with COVID-19: A Retrospective Cohort Study in a Large Teaching Hospital

November 23, 2022

Unquantifiably low aldosterone concentrations are prevalent in hospitalised COVID-19 patients but may not be revealed by chemiluminescent immunoassay

August 30, 2022

Difficulty and help with activities of daily living among older adults living alone during the COVID-19 pandemic: a multi-country population-based study

March 31, 2022

Validation of the 4C Deterioration Model for COVID-19 in a UK teaching hospital during Wave 2

November 16, 2021

The NIHR Cambridge BRC is part of the NIHR and hosted by Cambridge University Hospitals NHS Foundation Trust in partnership with the University of Cambridge. We are at the heart of the Cambridge Biomedical Campus, Europe’s largest health research area.

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Contact Us

Cambridge Biomedical Research Centre
Box 277
Hills Road
Cambridge
CB2 0QQ

Tel: 01223 348490

NIHR Cambridge Biomedical Research Centre @cambridgebrc ·

8 Jan

The Cambridge-led IVORY trial has shown that targeting the immune system, by giving a low-dose of aldesleukin, could prevent future heart attacks by nearly 8%.

Learn more about the study >>https://bit.ly/4aLzW6Q

@CUH_NHS @Cambridge_Uni @NIHRresearch @RoyalPapworth

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Milner Therapeutics Institute @themilnerinst ·

6 Jan

📣 The Milner Consortium Call returns with its sixth call for research proposals. Academic researchers – join our Q&A webinar to learn more and ask questions about the Call!

🗓️ 22 Jan ⏰ 10am 📍 Online

🔗 Register: https://ow.ly/5PMb50XCIuF

🔗 More info: http://www.milner.cam.ac.uk/consortiumcall/

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NIHR Cambridge Biomedical Research Centre @cambridgebrc ·

5 Jan

👉 Want to help shape a future trial focused on preventing falls in older people?
👉 Are you an older adult and/or family member/carer? 👉 Free on Wed 21st Jan 2026 at 13.30 for an online group?
👉 Contact James Piercy - james@brainhrc.org
@CUH_NHS @NIHRBrainHRC @Cambridge_Uni

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NIHR Cambridge Biomedical Research Centre @cambridgebrc ·

31 Dec

🎉Wishing everyone a very Happy New Year!🎉
Thinking of making a #NewYearsResolution?
Are you interested in giving feedback on the #research we do?
Live in the #EastOfEngland?
Then why not join our Patient & Public Involvement Panel >> https://bit.ly/3LlRX1c
@CUH_NHS

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NIHR Cambridge Biomedical Research Centre @cambridgebrc ·

24 Dec

Merry Christmas and a happy #NewYear from the #NIHR #Cambridge BRC!!
#Thankyou to all our amazing staff, everyone who has supported us and all those who took part in #research this year!
@CUH_NHS @Cambridge_Uni @NIHRresearch

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NIHR Cambridge Biomedical Research Centre @cambridgebrc ·

22 Dec

🥳 As 2025 draws to a close, we’ve put together a snapshot of some of our key research stories over the year.
🥳 We’d like to thank everyone who took part in, or contributed to our research over 2025!
To learn more >>
@CUH_NHS @Cambridge_Uni @NIHRresearch

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Data Science and Population Health

This Theme’s Focus

Theme Leads

Michael Inouye

Professor Angela Wood

The Data Science and Population Health theme will address two overarching research questions:

For more Information

Working with patients and the public

Podcast: Health Data Science Insights – Cambridge

Latest News

Data Science and Population Health Case Studies

Data Science and Population Health Publications

Contact Us

Useful Links