Understanding ageing
Traditionally research has focused on either the biological mechanisms of ageing or its social impact. At the Healthy Lifespan Institute we investigate both the biological and social processes that cause ageing, and how the two interact.
Our aim is to better understand the ageing process and how it drives the development of diseases so that we can propose optimum interventions aimed at promoting increased healthy life expectancy.
Identifying healthspan predictors at a population level
We are using big data and machine learning to identify how diseases group together. Using this approach, we can identify causes that lead to the development of specific groups of diseases. This knowledge will help us develop drugs that can treat multiple diseases at once.
By analysing patterns and correlations in the data we can also pinpoint potential causal relationships between behaviours, environments and health. Once causal relationships are proved we can recommend changes for people much earlier in life that prevent or delay the onset of age related disease.
Artificial Intelligence and data analytics
We are identifying the determinants and predictors of multimorbidity and frailty (including socio-economic and environmental factors and biological processes) using Artificial Intelligence approaches.