Multi-omics analytics and biosensors to enable digital twin platforms for P4 medicine

Abstract

P4 medicine, which stands for predictive, preventive, personalized, and participatory, focuses on a proactive model instead of reactive treatments. This paradigm is enabled by the convergence of omics technologies powered by biosensors and digital twins. Omics data (e.g., genomics, proteomics, etc.) can help identify disease risks and guide personalized treatments. Recent progress in flexible, wireless, chip-less, and self-powered biosensors has expanded their functionality toward durable, biocompatible operation, enabling persistent and accurate health tracking. The data collected by these sensors can be fed into digital twin systems, which use computational models to simulate biological processes and treatment responses. When analyzed with AI algorithms, these high-dimensional datasets can be integrated and interpreted to support early, data-driven decision-making. This integrated approach of P4 medicine will help realize the 4 Ps of predictive, preventive, personalized, and participatory healthcare.