P4 Medicine Research Articles

Цифровая трансформация здравоохранения: технологические и организационные аспекты

The article shows that the digital transformation of domestic healthcare leads to the emergence of new opportunities for its qualitative development and improvement of the efficiency of services provided, in this regard, such a transformation is one of the key directions of the national Healthcare project implemented in the Russian Federation. It shows how telemedicine, electronic medical records, artificial intelligence, big data analysis, etc. They provide an increase in the efficiency of medical services, allowing the formation of technological and organizational aspects for the effective development of the healthcare system within the framework of the so-called "4p medicine", which largely embodies the paradigm of its development in the digital age. The emergence of 4P medicine represents a transition from a reactive to a proactive model of the healthcare system, focusing on prevention, early detection and personalized treatment in order to improve the effectiveness of the healthcare system and reduce the cost of its operation.

Human centered design of AI-powered Digital Therapeutics for stress prevention: Perspectives from multi-stakeholders' workshops about the SHIVA solution

BackgroundAI-powered Digital Therapeutics (DTx) hold potential for enhancing stress prevention by promoting the scalability of P5 Medicine, which may offer users coping skills and improved self-management of mental wellbeing. However, adoption rates remain low, often due to insufficient user and stakeholder involvement during the design phases. ObjectiveThis study explores the human-centered design potentials of SHIVA, a DTx integrating virtual reality and AI with the SelfHelp+ intervention, aiming to understand stakeholder views and expectations that could influence its adoption. MethodsUsing the SHIVA example, we detail design opportunities involving AI techniques for stress prevention across modeling, personalization, monitoring, and simulation dimensions. Workshops with 12 stakeholders—including target users, digital health designers, and mental health experts—addressed four key adoption aspects through peer interviews: AI data processing, wearable device roles, deployment scenarios, and the model's transparency, explainability, and accuracy. ResultsStakeholders perceived AI-based data processing as beneficial for personalized treatment in a secure, privacy-preserving environment. While wearables were deemed essential, concerns about compulsory use and VR headset costs were noted. Initial human facilitation was favored to enhance engagement and prevent dropouts. Transparency, explainability, and accuracy were highlighted as crucial for the stress detection model. ConclusionStakeholders recognized AI-driven opportunities as crucial for SHIVA's adoption, facilitating personalized solutions tailored to user needs. Nonetheless, challenges persist in developing a transparent, explainable, and accurate stress detection model to ensure user engagement, adherence, and trust.

Enhancing Community Health Programs: Roles, Operations and Data-Driven Innovations

Aims: To examine how data-driven strategies can be integrated into community health programs as innovative approaches for effective operation. Problem Statement: Numerous government engagements in different crucial sectors have limited her concerns about health provision and distribution to many citizens living in remote communities. Health provision characterized with easy accessibility and low cost should not be marginalized and should be the right of every citizen. However, many lives have been lost due to lack of this in some communities. Significance of Study: To curb this, non-profit sectors are now engaging in community health programs to ameliorate the difficulties faced by distanced citizens living in remote localities. With the advent of this program, it is imperative to incorporate data-driven strategies as innovative approaches to improve and enhance the current state of operations in community health programs. Discussion: A medical practice that addresses the well-being of people within a particular geographical location is referred to as community health. This technical review paper discusses the concepts, roles and mode of operations of community health workers and the programs that are embedded. The attributes of a robust well-functioning health system as stated by World Health Organisation (WHO) were discussed alongside program components that are often executed by village workers. Value-based care, patient-centered care and P4 medicine were identified as the major ideologies behind data-driven strategies and the characteristic features of each were adequately discussed. Conclusion: A data-driven healthcare innovative approach must put into consideration the real definition of data management policies, organize training for health care workers who are handling health data and also support the implementation in order to secure the designed information systems.

Transforming Ontology Web Language Elements into Common Terminology Service 2 Terminology Resources.

Communication and cooperation are fundamental for the correct deployment of P5 medicine, and this can be achieved only by correct comprehension of semantics so that it can aspire to medical knowledge sharing. There is a hierarchy in the operations that need to be performed to achieve this goal that brings to the forefront the complete understanding of the real-world business system by domain experts using Domain Ontologies, and only in the last instance acknowledges the specific transformation at the pure information and communication technology level. A specific feature that should be maintained during such types of transformations is versioning that aims to record the evolution of meanings in time as well as the management of their historical evolution. The main tool used to represent ontology in computing environments is the Ontology Web Language (OWL), but it was not created for managing the evolution of meanings in time. Therefore, we tried, in this paper, to find a way to use the specific features of Common Terminology Service-Release 2 (CTS2) to perform consistent and validated transformations of ontologies written in OWL. The specific use case managed in the paper is the Alzheimer's Disease Ontology (ADO). We were able to consider all of the elements of ADO and map them with CTS2 terminological resources, except for a subset of elements such as the equivalent class derived from restrictions on other classes.

Total blastocyst usable rate is a predictor of cumulative live birth rate in IVF cycles

PurposeDespite advances in IVF techniques, determining the prognostic factors influencing cumulative live birth rate (CLBR) remains crucial for optimizing outcomes. Among the various key performance indicators in the lab, blastulation rate, and more specifically Total Blastocyst Usable Rate (TBUR), has gained particular interest. In this study we aimed at determining if TBUR was significantly associated with CLBR. Basic proceduresThis monocentric retrospective case-control study was conducted in 317 consecutive IVF/ICSI cycles in 2014–2020 and leading to the formation of 3 usable blastocysts, including freeze all cycles. TBUR (usable blastocysts / 2PNs) was calculated and CLBR after 2-year follow up was recorded, including both fresh and frozen embyro transfers. CLBR was then compared between 2 groups according to TBUR (group 1: TBUR ≥50 % vs group 2: TBUR ≤30 %). Main findingsCLBR was significantly higher in group 1 than in group 2 (57 vs. 41 %, p = 0.02). Adjusted logistic regression showed a statistically significant relationship between CLBR and TBUR, with a significantly lower chance of achieving a live birth in group 2 than in group 1 (OR = 0.408 [0.17–0.96]; p = 0.04). Principal conclusionsAlthough the monocentric design and the arbitrary choice of thresholds for TBUR and number of blastocysts call for caution when generalizing the findings and advocates for external validation, our results illustrate that TBUR is a valuable prognostic factor of CLBR in IVF cycles which might serve as a tool for lab monitoring, cycle analysis by medical staff and patients’ counselling. These results fit well within the P4 medicine concept (Predictive, Preventive, Personalized, and Participatory), and advocate for further research in order to improve embryo culture conditions.

The Importance of Nutrigenetics and Microbiota in Personalized Medicine: From Phenotype to Genotype.

Background After the completion of the Human Genome Project in 2003, the impact of genetic variations among people on human health was better understood. Precision medicine, also called 4P (Predictive, Preventive, Personalized, Participatory) medicine, is used to determine personal health risks, prevent, diagnose, and treat chronic diseases, and aims to identify the phenotypic, genotypic, and environmental factors that affect individual health risks instead of applying the same approach to everyone. Methods The study was conducted with 24 patients aged between 7 and 57. The patient group was selected from individuals who had undergone genetic and microbiota testing at Epigenetic Coaching Company. The patients' age, gender, and health status were documented. Genomic analysis of buccal samples was subsequently conducted using a custom Infinium HTS iSelect microarray on an Illumina iScan instrument, and microbiota metagenome analysis was performed using an Illumina NextSeq 500 platform. This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Biruni University Molecular Biology and Genetics Ethics Committee, with the decision number 2023/78-03. Results The genotypes of 19 cases carrying genetic variants involved in the metabolism of Vitamin D, Folate, B12, and Choline were analyzed. Eight of the cases were included in our study as autism patients, eight as allergy patients, and three as autoimmune thyroiditis patients. The Vitamin D receptor (VDR) genetic variants and microbiota diversity (using the Firmicutes/Bacteroides ratio, an indicator of dysbiosis) of 11 cases (9 allergy and two autism patients) participating in the study were evaluated together. Conclusions Translating nutrigenetic and nutrigenomic research into multidisciplinary clinical practice is the most challenging aspect. It is now evident that integrating data regarding phenotype and genotype, and using nutrition, lifestyle, and supplements tailored to an individual's genetics can increase clinical success. Importantly, if we wish to adopt an epigenomic approach, we must incorporate analyses of nutrigenetics, microbiota, and personalized risk based on test results.

Towards an Electronic Health Prevention Record Based on HL7 FHIR and the OMOP Common Data Model.

Approximately 40% of all recorded deaths in Austria are due to behavioral risks. These risks could be avoided with appropriate measures. Extension of the concept of EHR and EMR to an electronic prevention record, focusing on primary and secondary prevention. The concept of a structured prevention pathway, based on the principles of P4 Medicine, was developed for a multidisciplinary prevention network. An IT infrastructure based on HL7 FHIR and the OHDSI OMOP common data model was designed. An IT solution supporting a structured and modular prevention pathway was conceptualized. It contained a personalized management of prevention, risk assessment, diagnostic and preventive measures supported by a modular, interoperable IT infrastructure including a health app, prevention record web-service, decision support modules and a smart prevention registry, separating primary and secondary use of data. A concept was created on how an electronic health prevention record based on HL7 FHIR and the OMOP common data model can be implemented.

A Proactive Intervention Study in Metabolic Syndrome High-Risk Populations Using Phenome-Based Actionable P4 Medicine Strategy.

The online version contains supplementary material available at 10.1007/s43657-023-00115-z.

The preventive direction of modern theories of health and health-saving in public health and education

Background. The modern understanding of health is related to the need to prevent diseases caused by infections, lifestyle, environmental and genetic factors. Ukrainian legislation guarantees health care, but the practice of implementing laws is imperfect. The teaching of valeological disciplines in educational institutions is of great importance for the prevention of diseases. But the content of these disciplines requires constant revision from the point of view of evidence-based medicine, and the creation of new preventive programs requires theoretical justification. Aim. To determine the content and practical significance of the modern understanding of health care in public health care and education. Materials and Methods. Methods of bibliosemantic and system analysis were used. Results. The theory of health and health-saving is considered using cross-cultural, discursive, norm-centric, phenomenological, holistic, axiological and integral approaches, from the perspective of evidence-based and "4P" medicine. Health-saving is shown as derived from a healthy lifestyle and valeological competence formed in the population. The best environment for the formation of a healthy lifestyle is shown to be an educational environment, the tools of formation are valeological disciplines and education of medical and social non-government organizations. The need for joint efforts of the population and medical workers to achieve better results in the prevention of socially significant diseases is determined. Conclusions. Improvement of the preventive direction of valeological education is closely related to the competence approach, in particular, with the formation of valeological competence. The public health system should use the potential of educational valeological programs to form a healthy lifestyle in new generations during their studies at higher education institutions. For the formation of high-quality valeological programs, a permanent partnership of educators and medical professionals is necessary. Keywords: valeological competence, evidence-based medicine, 4P medicine, Health Pedagogy.

Pharmacomicrobiomics-Guided Precision Oncology: A New Frontier of P4 (Predictive, Personalized, Preventive, and Participatory) Medicine and Microbiome-Based Therapeutics.

Pharmacomicrobiomics is a rapidly developing field that promises to make significant contributions to predictive, personalized, preventive, and participatory (P4) medicine. This is becoming evident particularly in the field of precision (P4) oncology by taking seriously the crucial role microbiome plays in health and disease. Several studies have already shown that clinicians can harness insights from the microbiome to better predict treatment response, reduce side effects, and improve overall outcomes for cancer patients. Furthermore, pharmacomicrobiomics will undoubtedly play a crucial role in shaping the future of cancer treatment in the era of P4 oncology as we continue to unravel the intricate relationships between the microbiome and cancer. This perspective and innovation analysis discusses the emerging intersection of P4 medicine and P4 oncology, as seen through a lens of pharmacomicrobiomics. A key promise of pharmacomicrobiomics is the development of personalized microbiome-based therapeutics. In all, we suggest that optimizing cancer treatment and prevention by harnessing pharmacomicrobiomics has vast potentials for precision oncology, and personalized medicine using the right drug, at the right dose, for the right patient, and at the right time.

Taking Political Determinants of Planetary Health Seriously: Expanding from P4 to P5 Medicine.

Predictive, Personalized, Preventive, and Participatory (P4) Medicine is embedded in the precision medicine conceptual framework to achieve the overarching goal of "the right drug, for the right patient, at the right dose, and at the right time." Science cultures and political determinants of health have normative and instrumental impacts on P4 medicine. Yet, since the age of Enlightenment in the 17th century, science and economics have been disarticulated from politics along the lines of classical liberalism, and with an ahistorical approach that continues into the 21st century. The consequence of this liberal disarticulation is that science is falsely and narrowly understood as an invariably technocratic and objective field. In the aftermath of the Covid-19 pandemic, it is clearer that political determinants of health are the causes-of-causes for disease and health. I propose that we need P5 medicine with a fifth P, political determinants of planetary health. The new "P" can engage not only with instrumental aspects of P4 medicine research and clinical implementation but also with the structural factors that are an integral part of the politics of the P4 medicine. For example, the living legacies of colonialism contribute to the unequal relationships in trade, labor, provision, and production of materials among nation-states and between the Global South and the Global North and shape the class struggles in contemporary society, science, and medicine. A decolonial politics of care in which the political determinants of planetary health are taken seriously is therefore crucial and relevant to building a robust, ethical, responsible, and just P5 medicine in the 21st century.

High residual cardiovascular risk after lipid-lowering: prime time for Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive medicine.

As time has come to translate trial results into individualized medical diagnosis and therapy, we analyzed how to minimize residual risk of cardiovascular disease (CVD) by reviewing papers on "residual cardiovascular disease risk". During this review process we found 989 papers that started off with residual CVD risk after initiating statin therapy, continued with papers on residual CVD risk after initiating therapy to increase high-density lipoprotein-cholesterol (HDL-C), followed by papers on residual CVD risk after initiating therapy to decrease triglyceride (TG) levels. Later on, papers dealing with elevated levels of lipoprotein remnants and lipoprotein(a) [Lp(a)] reported new risk factors of residual CVD risk. And as new risk factors are being discovered and new therapies are being tested, residual CVD risk will be reduced further. As we move from CVD risk reduction to improvement of patient management, a paradigm shift from a reductionistic approach towards a holistic approach is required. To that purpose, a personalized treatment dependent on the individual's CVD risk factors including lipid profile abnormalities should be configured, along the line of P5 medicine for each individual patient, i.e., with Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive approaches.

Toward Personalized Medicine Approaches for Parkinson Disease Using Digital Technologies.

Parkinson disease (PD) is a complex neurodegenerative disorder that afflicts over 10 million people worldwide, resulting in debilitating motor and cognitive impairment. In the United States alone (with approximately 1 million cases), the economic burden for treating and caring for persons with PD exceeds US $50 billion and myriad therapeutic approaches are under development, including both symptomatic- and disease-modifying agents. The challenges presented in addressing PD are compounded by observations that numerous, statistically distinct patient phenotypes present with a wide variety of motor and nonmotor symptomatic profiles, varying responses to current standard-of-care symptom-alleviating medications (L-DOPA and dopaminergic agonists), and different disease trajectories. The existence of these differing phenotypes highlights the opportunities in personalized approaches to symptom management and disease control. The prodromal period of PD can span across several decades, allowing the potential to leverage the unique array of composite symptoms presented to trigger early interventions. This may be especially beneficial as disease progression in PD (alongside Alzheimer disease and Huntington disease) may be influenced by biological processes such as oxidative stress, offering the potential for individual lifestyle factors to be tailored to delay disease onset. In this viewpoint, we offer potential scenarios where emerging diagnostic and monitoring strategies might be tailored to the individual patient under the tenets of P4 medicine (predict, prevent, personalize, and participate). These approaches may be especially relevant as the causative factors and biochemical pathways responsible for the observed neurodegeneration in patients with PD remain areas of fluid debate. The numerous observational patient cohorts established globally offer an excellent opportunity to test and refine approaches to detect, characterize, control, modify the course, and ultimately stop progression of this debilitating disease. Such approaches may also help development of parallel interventive strategies in other diseases such as Alzheimer disease and Huntington disease, which share common traits and etiologies with PD. In this overview, we highlight near-term opportunities to apply P4 medicine principles for patients with PD and introduce the concept of composite orthogonal patient monitoring.

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues

BackgroundP4 medicine (predict, prevent, personalize, and participate) is a new approach to diagnosing and predicting diseases on a patient-by-patient basis. For the prevention and treatment of diseases, prediction plays a fundamental role. One of the intelligent strategies is the design of deep learning models that can predict the state of the disease using gene expression data.ResultsWe create an autoencoder deep learning model called DeeP4med, including a Classifier and a Transferor that predicts cancer's gene expression (mRNA) matrix from its matched normal sample and vice versa. The range of the F1 score of the model, depending on tissue type in the Classifier, is from 0.935 to 0.999 and in Transferor from 0.944 to 0.999. The accuracy of DeeP4med for tissue and disease classification was 0.986 and 0.992, respectively, which performed better compared to seven classic machine learning models (Support Vector Classifier, Logistic Regression, Linear Discriminant Analysis, Naive Bayes, Decision Tree, Random Forest, K Nearest Neighbors).ConclusionsBased on the idea of DeeP4med, by having the gene expression matrix of a normal tissue, we can predict its tumor gene expression matrix and, in this way, find effective genes in transforming a normal tissue into a tumor tissue. Results of Differentially Expressed Genes (DEGs) and enrichment analysis on the predicted matrices for 13 types of cancer showed a good correlation with the literature and biological databases. This led that by using the gene expression matrix, to train the model with features of each person in a normal and cancer state, this model could predict diagnosis based on gene expression data from healthy tissue and be used to identify possible therapeutic interventions for those patients.

Severe Asthma Phenotypes: Challenges and Options for Control

The practice of medicine has evolved from “arm-chair medicine” through “evidence-based medicine” to “precision medicine”. Medical literature has seen a proliferation of the use of the phrases “precision medicine” and “personalized medicine,” with little distinction made between the two. While both strategies promote individualizing patient care, precision medicine is guided by information based on the genes, proteins, metabolites, and other biomarkers in the human body. In addition to these biological markers, personalized medicine would consider various social, economic, behavioural, and environmental factors that might be specific to a particular individual in planning a treatment strategy unique to that individual. The term P4 Medicine (Predictive, Preventive, Personalized and Participatory) has also been proposed to reflect the increased understanding and implications of the pathobiology of disease on management strategies.1 The use of biologics and cell-based therapies, particularly in cancer therapeutics, has demonstrated the power of these strategies.2 This brief review will focus on how this strategy is currently being applied in the management of severe asthma.

Personalize, participate, predict, and prevent: 4Ps in inflammatory bowel disease.

Inflammatory bowel disease (IBD), which includes Crohn's disease (CD) and ulcerative colitis (UC), is a complex, immune-mediated, disorder which leads to several gastrointestinal and systemic manifestations determining a poor quality of life, disability, and other negative health outcomes. Our knowledge of this condition has greatly improved over the last few decades, and a comprehensive management should take into account both biological (i.e., disease-related, patient-related) and non-biological (i.e., socioeconomic, cultural, environmental, behavioral) factors which contribute to the disease phenotype. From this point of view, the so called 4P medicine framework, including personalization, prediction, prevention, and participation could be useful for tailoring ad hoc interventions in IBD patients. In this review, we discuss the cutting-edge issues regarding personalization in special settings (i.e., pregnancy, oncology, infectious diseases), patient participation (i.e., how to communicate, disability, tackling stigma and resilience, quality of care), disease prediction (i.e., faecal markers, response to treatments), and prevention (i.e., dysplasia through endoscopy, infections through vaccinations, and post-surgical recurrence). Finally, we provide an outlook discussing the unmet needs for implementing this conceptual framework in clinical practice.

РАЗРАБОТКА ПРОСТОГО ОПРОСНИКА ДЛЯ РАННЕГО ВЫЯВЛЕНИЯ ДОНОЗОЛОГИЧЕСКИХ ФУНКЦИОНАЛЬНЫХ НАРУШЕНИЙ ЗДОРОВЬЯ

Introduction. Health systems and health status in developed economies demonstrate failure of chronic disease prevention, in part due to too late health interventions postponed until the patient has a medical diagnosis. Healthcare system can benefit from P4 medicine, which needs special questionnaires to collect person-centered data. The available questionnaires do not match the practical tasks of the P4-medicine paradigm. Aim. The aim is to develop a simple questionnaire for mass early screening of health status in the adults within the P4-medicine paradigm. Material and Methods. We transformed and adapted the Suboptimal health status questionnaire (SHSQ-25) to meet the requirements of mass screening in the P4 medicine paradigm. Information value, sensitivity and specificity of the new questionnaire were tested in several focus groups of respondents through matching with detailed clinical interview aimed at prevention of chronic health conditions. Results and discussion. The Functional impairment questionnaire “FIQ-15” includes 15 questions covering the most common warning symptoms seen in respondents of various health states. Two alternative scales, 5-point and 3-point, are proposed to rate the symptoms. Based on the rate of functional impairments, their impact on everyday functioning, and the need in detailed examination and/or help, respondents are divided into 4 risk groups. More than 400 respondents filled the FIQ-15 over 2 years, 300 of them underwent detailed clinical interviews for questionnaire development and validation. The system of data acquisition and interpretation based on FIQ-15 allows automated mass screening for early functional impairments, fast primary sorting into risk groups (‘traffic light’ system), semi-quantify the severity of functional impairments and their impact on life quality, propose effective routing of patients to further examination and diagnosing, and involve the respondent in active management of one’s health. Conclusion. The proposed FIQ-15 questionnaire can become a simple, affordable and informative tool in early mass screening for functional impairments in the P4-medicine paradigm, in sorting the respondents based on their need in detailed examination, and in real life decision support, including the respondent’s participatory decisions regarding one’s health management.

Predictive, preventive, personalized and participatory medicine (4P): narrative review

4 P medicine is a concept used in healthcare and biomedical research that is based on the principles of prediction, personalization, prevention, and participation. It is increasingly used which has enabled the rapid development of medicine: several forms/types of pathologies have been discovered, for which specific treatments and appropriate prevention strategies have been developed, it has become possible to predict the evolution of health and disease, all these would be useless without the participation of the patient, family, and decision makers.The purpose of this article is to provide an overview of the 4 P medicine and its preventive, predictive, personalized, and participatory principles through the lens of clinical practice.Materials and Methods: The database was searched for the keywords “4P medicine”, “personalized medicine”, “participatory medicine”, “systems medicine”. For the term “systems medicine” we obtained 5,257,904 results, in the last 10 years - there were 2,396,921 publications, journal articles - 2.4 million citations, book chapters - 11 thousand, related to medicine - 1.6 million of the references. For the term “precision medicine” 158,239 references appeared, for “personalized medicine” - 91,883 citations and for “participatory medicine” - 17,579 references. Most references were published in English. For the search for “personalized medicine oncology” - 18,209 references appeared, for “personalized medicine neurology” 4,751 references were discovered, in the last 10 years 4,336 of them were published, being journal articles4,300 and 16 book chapters. Most publications talk about the use of the principles of personalized medicine (4P) in demyelinating pathologies, epilepsy, dementia, neuro-oncology, stroke, migraine, neuroimaging, and neurorehabilitation. Results and discussions: 4P medicine is at the intersection of three major trends: the growing ability of systems biology and medicine to decipher the biological complexity of pathologies, the digital revolution that has increased theability to collect, integrate, store, analyze and communicate data and information, and consumer access to information.Conclusion: 4P medicine is a concept used in biomedical research and human health care that was taken from systems biology and systems medicine. It is a form of approach that uses the principles of prevention, prediction, personalization, and participation to transform healthcare from a reactive to a proactive one. The use of the principles of 4P medicine in clinical practice allows the deciphering of forms of the disease, the stratification according to pathophysiological mechanisms, the application of personalized treatment to the patient, respectively more efficiently and with fewer adverse reactions.

НОВЫЙ ИНСТРУМЕНТ ДЛЯ 4П-МЕДИЦИНЫ: ОЦЕНКА ВОЗМОЖНОСТЕЙ КРАТКОГО ОПРОСНИКА ФУНКЦИОНАЛЬНЫХ НАРУШЕНИЙ ОФН-15

Background: 4P medicine is the most promising approach towards age-related diseases, since it can overcome the limitations of the prevalent diagnosis-centered healthcare model. To implement 4P medicine in Russia on a large scale, new instruments are needed to identify early signs of ill-being. A short functional impairment questionnaire FIQ-15 is proposed as such a tool. The purpose of the study was to evaluate strengths and limitations of FIQ-15 in identifying signs of age-related functional disorders in working-age individuals with different health status. Material and methods. Responses to FIQ-15 were compared with the results of an extended (45-60 minutes) medical consultation on healthy lifestyle. Results: The study involved 147 individuals aged 19-64, including 102 women. Major reasons for consultation included: "overweight" (37.4%), sleep problems (19.7%), low energy levels (18.4%), digestive problems (17.7%). In all cases, FIQ-15 has accurately identified or clarified the leading symptoms of the biological, psychological and social ill-being and their context. The most common pronounced subjective symptoms of ill-being included: low energy level (40.1%); restlessness/anxiety (37.4%); back/neck pain (37.4%); sleep problems (28.6%); depressed mood (27.9%); mood swings (21.8%). Distribution of the participants by "subjective risk zone" of health deterioration was as follows: high risk – 70.1%, average risk – 24.5%, relatively low risk – 5.4%. In 95.2% of the participants, the identified symptoms fit into one or more patterns of age-related functional disorders: chronic distress – 83%, chronic systemic inflammation – 52,4%, insulin resistance – 42,9%. Age-related evolution of the patterns and interrelations between them have been identified. Conclusion: FIQ-15 is informative in identifying early signs of biopsychosocial ill-being in working age people. It makes it possible to identify symptom patterns characteristic of age-related diseases. FIQ-15 implements the principles of predictivity and participation, and can be considered as a promising tool for a large-scale implementation of the 4P medicine and prevention of age-related diseases.

P4 Medicine for Heterogeneity of Dry Eye: A Mobile Health-based Digital Cohort Study

During the 5th Science, Technology, and Innovation Basic Plan, the Japanese government proposed a novel societal concept -Society 5.0- that promoted a healthcare system characterized by its capability to provide unintrusive, predictive, longitudinal care through the integration of cyber and physical space. The role of Society 5.0 in managing our quality of vision will become more important in the modern digitalized and aging society, both of which are known risk factors for developing dry eye. Dry eye is the most common ocular surface disease encountered in Japan with symptoms including increased dryness, eye discomfort, and decreased visual acuity. Owing to its complexity, implementation of P4 (predictive, preventive, personalized, participatory) medicine in managing dry eye requires a comprehensive understanding of its pathology, as well as a strategy to visualize and stratify its risk factors. Using DryEyeRhythm®, a mobile health (mHealth) smartphone software (app), we established a route to collect holistic medical big data on dry eye, such as the subjective symptoms and lifestyle data for each individual. The studies to date aided in determining the risk factors for severe dry eye, the association between major depressive disorder and dry eye exacerbation, eye drop treatment adherence, app-based stratification algorithms based on symptomology, blink detection biosensoring as a dry eye-related digital phenotype, and effectiveness of app-based dry eye diagnosis support compared to traditional methods. These results contribute to elucidating disease pathophysiology and promoting preventive and effective measures to counteract dry eye through mHealth.