Personalized Medicine (PM) has shifted the traditional top-down approach to medicine based on the identification of single etiological factors to explain diseases, which was not suitable for explaining complex conditions. The concept of PM assumes several interpretations in the literature, with particular regards to Genetic and Genomic Medicine. Despite the fact that some disease-modifying genes affect disease expression and progression, many complex conditions cannot be understood through only this lens, especially when other lifestyle factors can play a crucial role (such as the environment, emotions, nutrition, etc.). Personalizing clinical phenotyping becomes a challenge when different pathophysiological mechanisms underlie the same manifestation. Brain disorders, cardiovascular and gastroentero-logical diseases can be paradigmatic examples. Experiences on the field of Fondazione Policlinico Gemelli in Rome (a research hospital recognized by the Italian Ministry of Health as national leader in “Personalized Medicine” and “Innovative Biomedical Technologies”) could help understanding which techniques and tools are the most performing to develop potential clinical phenotypes person-alization. The connection between practical experiences and scientific literature highlights how this potential can be reached towards Systems Medicine using Artificial Intelligence tools.

Cesario, A., D'Oria, M., Bove, F., Privitera, G., Boskoski, I., Pedicino, D., Boldrini, L., Erra, C., Loreti, C., Liuzzo, G., Crea, F., Armuzzi, A., Gasbarrini, A., Calabresi, P., Padua, L., Costamagna, G., Antonelli, M., Valentini, V., Auffray, C., Scambia, G., Personalized clinical phenotyping through systems medicine and artificial intelligence, <<JOURNAL OF PERSONALIZED MEDICINE>>, n/a; 11 (4): 265-N/A. [doi:10.3390/jpm11040265] [http://hdl.handle.net/10807/203807]

Personalized clinical phenotyping through systems medicine and artificial intelligence

Cesario, Alfredo;Boskoski, Ivo;Pedicino, Daniela;Boldrini, Luca;Erra, Carmen;Loreti, Claudia;Liuzzo, Giovanna;Crea, Filippo;Armuzzi, Alessandro;Gasbarrini, Antonio;Calabresi, Paolo;Padua, Luca;Costamagna, Guido;Antonelli, Massimo;Valentini, Vincenzo;Scambia, Giovanni
2021

Abstract

Personalized Medicine (PM) has shifted the traditional top-down approach to medicine based on the identification of single etiological factors to explain diseases, which was not suitable for explaining complex conditions. The concept of PM assumes several interpretations in the literature, with particular regards to Genetic and Genomic Medicine. Despite the fact that some disease-modifying genes affect disease expression and progression, many complex conditions cannot be understood through only this lens, especially when other lifestyle factors can play a crucial role (such as the environment, emotions, nutrition, etc.). Personalizing clinical phenotyping becomes a challenge when different pathophysiological mechanisms underlie the same manifestation. Brain disorders, cardiovascular and gastroentero-logical diseases can be paradigmatic examples. Experiences on the field of Fondazione Policlinico Gemelli in Rome (a research hospital recognized by the Italian Ministry of Health as national leader in “Personalized Medicine” and “Innovative Biomedical Technologies”) could help understanding which techniques and tools are the most performing to develop potential clinical phenotypes person-alization. The connection between practical experiences and scientific literature highlights how this potential can be reached towards Systems Medicine using Artificial Intelligence tools.
2021
Inglese
Cesario, A., D'Oria, M., Bove, F., Privitera, G., Boskoski, I., Pedicino, D., Boldrini, L., Erra, C., Loreti, C., Liuzzo, G., Crea, F., Armuzzi, A., Gasbarrini, A., Calabresi, P., Padua, L., Costamagna, G., Antonelli, M., Valentini, V., Auffray, C., Scambia, G., Personalized clinical phenotyping through systems medicine and artificial intelligence, <<JOURNAL OF PERSONALIZED MEDICINE>>, n/a; 11 (4): 265-N/A. [doi:10.3390/jpm11040265] [http://hdl.handle.net/10807/203807]
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