ProfessorAllan Lawrie

Allan’s research focuses on understanding why pulmonary hypertension develops, progresses, and presents differently between individuals. A core theme of his work is disease heterogeneity and examining how biological mechanisms interact with behavioural, environmental, and socioeconomic factors to shape disease onset, severity, and clinical outcomes. This approach reflects a broader aim to move beyond single‑factor disease models towards more personalised and prevention‑focused cardiovascular care.

Central to this programme is the use of real‑world data to improve early diagnosis and disease monitoring. Through the My Heart Counts programme and related studies, Allan’s research integrates routinely collected healthcare data with information captured through smartphones and wearable devices, including physical activity and other passive health measures. Working across academia, healthcare, and industry, his team applies artificial intelligence and machine‑learning approaches to large‑scale NHS datasets, multi‑omic data, and digital phenotyping to identify early risk patterns, patient subgroups, and disease trajectories.

By combining molecular biology with population‑scale digital health approaches, Allan’s work aims to develop scalable and generalisable digital biomarkers that support earlier identification of pulmonary and cardiovascular disease, enable real‑time monitoring, and inform targeted, non‑pharmacological interventions that can be deployed across healthcare systems.