Precision cardiovascular medicine: shifting the innovation paradigm - Aikawa, Masanori; Sonawane, Abhijeet R.; Chelvanambi, Sarvesh; Asano, Takaharu; Halu, Arda; Matamalas, Joan T.; Singh, Sasha A.; Uchida, Shizuka; Aikawa, Elena; Arenas, Alex; Balligand, Jean-Luc; Giannarelli, Chiara; et al. (Frontiers in Science, 2025)
Despite the development of potent drugs for modifiable risk factors and advances in mechanistic biomedical research, cardiovascular diseases (CVDs) collectively remain the leading cause of death globally, indicating a need for new, more effective therapies. A foundational challenge is the multilevel heterogeneity that characterizes CVDs—from their complex pathobiological mechanisms at the molecular and cellular levels, to their clinical presentations and therapeutic responses at the individual and population levels. This variability arises from individuals’ unique genomic and exposomic characteristics, underscoring the need for precision approaches. Other key challenges include the long navigation times, high costs, and low success rates for drug development, often compounded by the poor “druggability” of new targets. In this article, we explore how these challenges have inspired novel technologies that offer promise in improving health outcomes globally through an integrative precision medicine approach. Key to this transformation is the use of systems biology and network medicine, whereby the application of artificial intelligence to “big data”, ranging from clinical information to unbiased multiomics (e.g., genomics, transcriptomics, proteomics, and metabolomics) can elucidate disease mechanisms, yield novel biomarkers for disease progression, and identify potential drug targets. In parallel, new computational approaches are helping translate these discoveries into novel therapies and overcome druggability barriers. The transition to a precision-based research and innovation paradigm in cardiovascular medicine will require greater interdisciplinary collaboration, data science implementation at every stage, and new partnerships between academia and industry. Global policy leadership is also essential to implement suitable models of research funding and organization, data infrastructures and policies, medicines regulations, and patient access policies promoting equity.