Digital twins for cardiopulmonary medicine: the case for pulmonary aterial hypertension

Abstract The management of pulmonary arterial hypertension (PAH), like so many diseases, currently relies on episodic data from clinic visits, which offers limited insight into a patient’s disease trajectory and dynamic clinical decisions. Patient digital twins present a technological solution that combine hospital and community data into a single dynamic and predictive virtual representation of the patient. Digital twins operationalise real-world observational inference at the individual level, functioning as a complementary decision-support tool alongside trial evidence. This review introduces the concept of a patient digital twin and provides a roadmap for the development, evaluation, and potential implementation of a patient digital twin for PAH. The resulting twin has the potential to change PAH care pathways, shifting PAH care from reactive to proactive management.