Artificial Intelligence and Network Medicine: Path to Precision Medicine

Lucia Altucci, Lina Badimon, Jean-Luc Balligand, Jan Baumbach, Alberico L Catapano, Feixong Cheng, Dawn DeMeo, Rajat Gupta, Marcus Hacker, Yang-Yu Liu, Joseph Loscalzo, Sabrina Maniscalco, J�rg Menche, Giulia Menichetti, Paolo Parini, Harald H H W Schmidt, Marinka Zitnik
NEJM AI. 2025 Sep;2(9):10.1056/aira2401229. doi: 10.1056/aira2401229. Epub 2025 Aug 28.
Abstract
Over the past two decades, network medicine (NM) has evolved to help define disease mechanisms, identify drug targets, and guide increasingly precise therapies. In recent years, the integration of NM with artificial intelligence (AI), particularly deep learning techniques, has evolved with increasing applications. AI techniques help elucidate complex disease mechanisms and define precise therapies. The depth of useful, mechanistic information implicit in molecular interaction networks and prior deep learning successes provide a rational basis for combining NM and AI in the analyses of large multiomic datasets to enhance the speed, predictive precision, and biological insights of the computational process. In this review, we provide a summary of concepts related to the combined use of AI and NM as a path to precision medicine, illustrating the success of this joint approach to biomedical complexity and its ongoing challenges.