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1)Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo, Japan2)Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan3)Department of Strategic Operating Room Management and Improvement, 4)Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo, Japan6)Department of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan5)Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, JapanTakenori INOMATA1-4), Jaemyoung SUNG1), Masahiro NAKAMURA1, 2, 5), Masao IWAGAMI6), Yuichi OKUMURA1-3), Kenta FUJIO1, 2), Yasutsugu AKASAKI1, 2), Keiichi FUJIMOTO1, 2), Ai YANAGAWA2), Akie MIDORIKAWA-INOMATA4), Ken NAGINO4), Atsuko EGUCHI4), Kunihiko HIROSAWA1, 2), Tianxing HUANG1, 2), Yuki MOROOKA1, 2), Akira MURAKAMI1, 2)Toward P4 Medicine: A Narrative ReviewCorresponding author: Takenori InomataDepartment of Ophthalmology, Juntendo University Graduate School of Medicine3-1-3 Hongo, Bunkyo-ku, Tokyo. 113-8431, JapanTEL: +81-3-5802-1228　FAX: +81-3-5689-0394　E-mail: tinoma@juntendo.ac.jp353rd Triannual Meeting of the Juntendo Medical Society “Medical Research Update” 〔Held on May 22, 2021〕〔Received　Aug. 21, 2021〕〔Accepted　Sep. 13, 2021〕J-STAGE Advance published date: Oct. 25, 2021Copyright © 2021 The Juntendo Medical Society. This is an open access article distributed under the terms of Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original source is properly credited. doi: 10.14789/jmj.JMJ21-0023-RJuntendo Medical Journal2021. 67(6), 519-529Special ReviewsCross-hierarchical Integrative Research Network for Heterogenetic Eye Disease Key words: Big data, mobile health, multi-omics, P4 medicine, heterogeneityJuntendo University Graduate School of Medicine, Tokyo, Japan519Hurrramhon SHOKIROVA1), Jun ZHU1), Maria MIURA1, 2), Mizu KUWAHARA1, 2), 　Society 5.0, a visionary human-centered societal model, fuels economic development and resolves long-standing social problems. The model establishes a technological foundation and social contract to integrate cyberspace into the physical (real) space fully. The medical infrastructure outlined by the model envisions a healthcare paradigm that revolves around preventative, lifelong patient- and population- centered care that functions seamlessly within one’s daily life. 　In satisfying this goal, cross-hierarchical integrative data-driven biological research has received attention due to medical big data and artificial intelligence (AI) technologies, capable of highly accurate and rapid data analysis. However, the collection of big data has been a bottleneck, and the capability of AI analysis is not being utilized to its full potential. In solving this obstacle, we explore mobile health (mHealth) and multi-omics as two rich sources of medical big data. Additionally, we discuss the implications of cross-hierarchical integrative analysis that encompasses all levels of cellular function, from intracellular molecular dynamics to end-phenotypes. This is to understand ocular disease pathology and implement the pillars of P4 (predictive, personalized, preventative, participatory) medicine toward human-centered healthcare.　Here, we discuss notable studies in utilizing mHealth to stratify subjective symptoms, presentations of dry eye disease, and employing multi-omics machine learning targeted at elucidating immunologic mechanisms of corneal allograft rejection and ocular inflammation. We also discuss the role of cross-hierarchical integrative data-driven research in promoting future-oriented healthcare envisioned by the Society 5.0 plan.