- Preventive: able to keep the patient healthy or to prevent the disease before reaching an acute treatment, through the use of genomics, the use of targeted screening and check-up activities and the adoption of proper lifestyles.
- Predictive: able to make predictions for each patient on the risk factors of chronic diseases that may occur in the future, and to predict individual drug reactions, levels of effectiveness and toxicity, through molecular biology, Big Data analysis and management.
- Participatory: which provides for the patient’s empowement, which evolves from “passive” to active and aware. A patient now able to gather information, to use new technologies to improve his lifestyle and to make informed choices of care and prevention in health, under the guidance of his doctor.
- Personalized and precision: modulating screening and diagnosis, therapies and treatment models on the individual characteristics, clinical data and biomarkers of the patient, also taking into account the environmental and cultural context in which the person lives and operates. Biomarker is in fact any information – physiological and behavioral – detectable in an individual and able to provide in an objective, measurable and reproducible, details on the state of health of that person and condition – or predict the incidence of an outcome or disease. Biomarkers are subject to approval procedures, validation processes and regulatory bodies different from country to country.
4P medicine, progress and “omics” sciences
Formulated for the first time in 2013 by the Institute for System Biology in Seattle, under the guidance of Leroy Hood, the “4P Medicine” is the result of the convergence of three factors:
- The progress of biomolecular disciplines at the service of clinical practice, or the most recent “omics” sciences, such as genomics, which start from the identification of genes and proteins present in an organism and evaluate anomalies, effects and evolution over time, and use biomarkers as a tool to prevent the onset of genetic, degenerative, tumor, infectious diseases.
- The explosion of big data and the interoperability of devices (with the dissemination of electronic health files, computerized health records, new diagnostic and bioinformatics programs); telemedicine and Iot (with medical devices equipped with sensors able to detect and share via web in real time the patient’s vital and physiological parameters); even “unstructured” data, shared by users on social networks;
- The digital revolution, with the digitization of processes that is having its peak acceleration in the last two years, under pandemic by COVID-19.
Disease prevention and targeting of medicines and therapies
- Reduce the incidence of acuity and chronic disease based on data associated with the disease and able to detect susceptibility/ risk, diagnosis, prognosis, monitoring
- Identify the most effective therapies for the individual case with the advent of advanced therapies (gene therapy products, somatic cell therapy and tissue engineering) and biomarkers able to predict pharmacodynamics/ response, safety and efficacy of a given drug.
- Contributing to the growth of an innovative health care system, in continuous learning, prepared to do active biosorveglianza for the entire population, increase the degree of relationship with the citizen, provide personalized health care.
- SG Alonso, de la Torre Díez, BG Zapiraín. Predictive, Personalized, Preventive and Participatory (4P) Medicine Applied to Telemedicine and eHealth in the Literature – Journal of medical systems, Springer, 2019
- Collecchia G., Artificial intelligence systems and precision medicine: Hopes and realities, Recent Prog Med (111), 2020.
- Wilkinson J.W. et al., Time to reality check the promise of machine-learning powered precision medicine, Lancet Digital Health, 2020.
- Hood L. Systems Biology and P4 Medicine: Past, Present, and Future, Rambam Maimonides Med J (203), 2013.
- Jameson J.L. et al., Precision medicine. Personalized, problematic, and promising, NEJM(372)