Discovering Composite Lifestyle Biomarkers With Artificial Intelligence From Clinical Studies to Enable Smart eHealth and Digital Therapeutic Services - Kyriazakos, Sofoklis; Pnevmatikakis, Aristodemos; Cesario, Alfredo; Kostopoulou, Konstantina; Boldrini, Luca; Valentini, Vincenzo; Scambia, Giovanni (Frontiers in Digital Health, 2021)
Discovery of biomarkers is a continuous activity of the research community in the clinical domain that recently shifted its focus towards digital, non-traditional biomarkers that often use physiological, psychological, social and environmental data to derive an intermediate biomarker. Such biomarkers, by triggering smart services, can be used in a clinical trial framework, as well as eHealth or digital therapeutic services. In this paper, we discuss the APACHE trial for determining the quality of life of cervical cancer patients and demonstrate how we are discovering a biomarker for this therapeutic area that to predicts significant quality of life variations. To this extent we present how Real-World Data can unfold a big potential for detecting the cervical cancer quality of life biomarker and how it can be used for novel treatments. The presented methodology, derived in APACHE, is introduced by Healthentia eClinical solution and is beginning to be used in several clinical studies.