Chronomics Ltd.

Commercial

OFHS250024

Our aim is to use artificial intelligence (AI) to find new ways of identifying people at risk of disease and those who are more likely to respond well to treatments. We will analyse large global health datasets (including Our Future Health) so that different ethnic backgrounds and populations can benefit from these discoveries. We will focus on two types of biomarkers: - Risk biomarkers that show if someone is more likely to develop a disease, helping with early detection and preventative healthcare. - Predictive markers that indicate which treatments are more likely to work for a person, supporting precision medicine. By using data from Our Future Health, we will test which health markers work best for different diseases and how easy they are to use and implement in real-world healthcare. We aim to make some of these tools available to doctors and researchers so they can improve healthcare for more people. Doctors and scientists use biomarkers to understand who is at risk of disease and which treatments work best for different people. Artificial intelligence (AI) can help find these markers by analysing large health datasets. However, most existing research is based on people of European backgrounds, meaning the results may not work as well for everyone. There are also challenges in turning these discoveries into real-world tests that doctors and patients can use. By combining data from Our Future Health with other large global health datasets, we will be able to make the discovered biomarkers more accurate and accessible across diverse populations. Furthermore, we will study the tradeoff between accuracy of the biomarkers and cost/complexity of implementing them in the real-world, so they end up being adopted by healthcare systems and benefiting patients. This research could lead to better ways of preventing and treating diseases for a wider range of people.

This research will improve healthcare by making it easier to predict who might develop a disease and to choose the best treatments for each person. This can lead to earlier interventions and more personalized care, supporting both prevention and precision medicine. For patients, this means getting the right care sooner. For doctors, these new tools will support better decisions when diagnosing and treating illnesses. We plan to make our AI models as accessible as possible, so that other researchers and healthcare systems—such as the NHS—can use and improve them. In the long term, our work could help shape health policies and guidelines, ensuring that everyone benefits from advances in medical technology. Additionally, our models will be trained on data from people with diverse genetic backgrounds and from different environments, ensuring that our tools work well for everyone. We will also publish our findings in open access journals and present them at conferences, making sure our research reaches a wide audience and contributes to better healthcare for all.

Public Health Research

12/09/2025

22/07/2025

TRE