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

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 combines hospital and community data into a single dynamic and predictive virtual representation of the patient. Digital twins operationalize 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.