Nouvelles méthodes pour soutenir la Pharmacovigilance Active dans l'environnement clinique

La sécurité des médicaments (DS) est un problème de santé publique important, car les effets indésirables des médicaments (EIM) entraînent un fardeau de santé publique important. La pharmacovigilance (PV) est définie comme «la science et les activités liées à la détection, à l'évaluation, à la compréhension et à la prévention des effets indésirables ou de tout autre problème éventuel lié aux médicaments ». Les progrès des technologies de l'information et de la communication (TIC) permettent l'utilisation de nouvelles sources de données émergentes, généralement construites à d'autres fins principales, élargissant l'espace de preuves du monde réel utilisé pour rechercher de nouveaux signaux PV potentiels. Ces sources de données émergentes pourraient améliorer considérablement l'identification et l'élaboration de signaux PV potentiels, en complément des preuves produites par l'analyse des ICSR. Ainsi, la pharmacovigilance active (PA) va au-delà de l'utilisation des bases de données ICSR et peut être définie comme «un processus systématique qui cherche à identifier les problèmes de sécurité grâce à des analyses épidémiologiques des bases de données de soins de santé», faisant généralement référence à l'exploitation des dossiers patients (DP) dans les systèmes d’information hospitaliers ou des bases de données d'observation, s'étendant parfois également à d'autres types de sources de données. L'objectif principal de cette thèse est de définir clairement le concept de pharmacovigilance active et de le réviser, en mettant l'accent sur l'impact potentiel des approches d'ingénierie des connaissances et en identifiant les étapes nécessaires en termes de «feuille de route».Drug safety is a critical issue causing significant public health and financial burden. Pharmacovigilance (PV) is the science related with all aspects of drug safety, focusing on the post-marketing drug safety. Typically, PV activities are not supported by specific tools systematically developed to this purpose. Active Pharmacovigilance (AP) is a new paradigm aiming to increase the PV data space via the active pursue of data which could in principle be produced for another main purpose, but they could also potentially be useful for PV as a secondary use. Technically, the exploitation of these data sources requires the use of Knowledge Engineering (KE) computational approaches, aiming to integrate, mine and semantically align the respective data. The challenges of integrating the use of these KE and potentially other “intelligent” technical paradigms as well as data sources in the clinical environment and beyond that are evident. Revisiting the AP paradigm towards focusing on the exploitation of emerging data sources and technologies is necessary in order to improve medical practice, patient safety and clinical research. This thesis aims to redefine AP based on the opportunities provided by the potential of integrating emerging data sources and “intelligent” technologies. More specifically, it emphasizes on the legal and organizational aspects, elaborating the related “Business Processes” (BPs) and the respective “User Goals” (UGs) and their value in updating the AP paradigm. To this end, a systematic review of the research papers focusing on the use of KE for drug safety has been conducted, identifying the technical approaches and the data sources used, while also investigating potential technical and research gaps. Based on these findings a number of activities has been launched, aiming to support the integration of these data sources and technical approaches in the clinical context and beyond. The regulatory context has been analysed, the respective BPs were identified and elaborated and finally a well-defined set of “User-Goals” has been produced and the respective challenges on the integration of “intelligent” technologies were elaborated. Ultimately, based on these findings, the vision of integrating AP as part of a “Learning Healthcare System” is presented. Finally, a set of technical research lines were also elaborated, providing clear pathways for future research initiatives. More specifically, a Knowledge Graph using PV data is currently under construction, based on PV signal report information published by Uppsala Monitoring Centre, the World Health Organization reference centre for PV. Furthermore, emphasizing on the potential use of Systems Pharmacology oriented data, an ontology enabling the semantic modelling of biochemical pathway information aligned with Systems Theory concepts has also been designed