Summary of the project

We will establish integrated research between mathematical studies with mathematical data analysis and modeling analysis, and experimental studies on physiological interaction and control between organs. In particular, we develop DNB (Dynamical Network Biomarkers) theory and its complementary theory & AI like spatiotemporal information transforming learning to detect the pre-disease states (Mebyo) and deviation from healthy states, respectively, at ultra-early timing before tipping points to disease states and propose methodology for Ultra-Early Medicine based on such ultra-early detection as well as treatments with control theory on physiological networks. The long-term purpose of this project is to realize a society equipped with ultra-early disease prediction and intervention systems by 2050.

Milestone by year 2030

Based on mathematical & AI studies, we will develop methodology of network medicine to detect early warning signals of diseases in the pre-disease states before diseases will really occur and to cure imminent diseases before the onsets by network control.

Milestone by year 2025

We will develop methodology for detecting early warning signals of diseases in pre-disease states before the onsets by analyzing various biological and medical data on the basis of mathematical data analysis and mathematical modeling analysis.