Patient-reported outcomes and treatment adherence in type 2 diabetes using natural language processing: Wave 8 of the Observational International Diabetes Management Practices Study
Publisher: Journal of Diabetes Investigation Authors: Juliana CN Chan, Jean Claude Mbanya, Jean-Marc Chantelot, Marina Shestakova, Ambady Ramachandran, Hasan Ilkova, Lucille Deplante, Melissa Rollot, Lydie Melas-Melt, Juan Jose Gagliardino, Pablo Aschner View Publication Aims/Introduction We analyzed patient-reported outcomes of people with type 2 diabetes to better understand perceptions and experiences contributing to treatment adherence. Materials and […]
An AI powered tool to identify and assess fit-for use registries for real-world evidence
Event: EuroDURG 2025, Uppsala, Sweden Authors: Ghinwa Y. Hayek, Pascal Godbillot, Coriande Clemente, Sonia Zebachi, Gaëtan Pinon, Boris Kopin, Elisabeth Bakker, Sieta T. de Vries, Peter G.M. Mol, Billy Amzal View publication Abstract The selection of appropriate real-world data (RWD) sources, particularly registries, is of primary concern for academia, industry, regulators, and health technology assessment […]
Clustering des trajectoires thérapeutiques pour la bronchopneumopathie chronique obstructive (BPCO) : comparaison des méthodes d’encodage de séquences
Event: 17ème Colloque Données de Santé en Vie Réelle de l’AFCROs, Paris, France Authors: Romane Pean, Nina Temam, Diane Vincent, Marie Génin, Pauline Guilmin View Presentation Introduction L’analyse des séquences thérapeutiques et évènements médicauxest essentielle pour optimiser la prise en charge des patients. Cependant, lacomplexité et variabilité de ces séquences posent un défi méthodologique. Leclustering […]
Navigating the Real World: A Scoping Review of Structured Frameworks to Effectively Identify, Evaluate, and Select Real-World Data Sources for Fit-for-Purpose Studies
Publisher: Clinical Pharmacology and Therapeutics Authors: Sonia Zebachi, Julien Tanniou, Elisabeth Bakker, Sieta T. de Vries, Rossella Di Bidino, Entela Xoxi, Anna Glaser, Gianluigi Savarese, Jan Hillert, Peter G.M. Mol, Kelly Plueschke, Billy Amzal, Ghinwa Y. Hayek, Jeverson Moreira View publication Abstract The potential of real-world data (RWD), particularly from patient registries, has been increasingly recognized […]
Navigating the Real World: A Scoping Review of Structured Frameworks to Effectively Identify, Evaluate, and Select Real-World Data Sources for Fit-for-Purpose Studies
Event: EuroDURG 2025, Uppsala, Sweden Authors: Sonia Zebachi, Julien Tanniou, Elisabeth Bakker, Sieta T. de Vries, Rossella di Bidino, Entela Xoxi, Anna Glaser, Gianluigi Savarese, Jan Hillert, Peter G.M. Mol, Kelly Plueschke, Ghinwa Hayek, Billy Amzal, Jeverson Moreira View Poster The potential of real-world data (RWD), particularly from patient registries, has been increasingly recognised over […]
Policy makers must adopt agile signal detection tools to strengthen epidemiological surveillance and improve pandemic preparedness
Publisher: Health Policy Authors: Cédric Mahé, Aimo Kannt, AIOLOS Consortium View publication Abstract The SARS-COV2 pandemic has highlighted the urgent need for agile and responsive disease surveillance systems. To strengthen epidemiological surveillance and improve pandemic preparedness, policymakers must adopt real-time signal detection tools that integrate multisource data, including non-traditional health data, advanced analytics, and artificial […]
A text-to-tabular approach to generate synthetic patient data using LLMs
Publisher: IEEE XploreAuthors: Margaux Tornqvist, Jean-Daniel Zucker, Tristan Fauvel, Nicolas Lambert, Mathilde Berthelot, Antoine Movschin View publication Abstract Access to large-scale high-quality healthcare databases is key to accelerate medical research and make insightful discoveries about diseases. However, access to such data is often limited by patient privacy concerns, data sharing restrictions and high costs. To […]
A text-to-tabular approach to generate synthetic patient data using LLMs
Event: IEEE ICHI 2025, Rende, ItalyAuthors:Margaux Tornqvist, Jean-Daniel Zucker, Tristan Fauvel, Nicolas Lambert, Mathilde Berthelot, Antoine Movschin View Conference Proceeding Abstract Access to large-scale high-quality healthcare databases is key to accelerate medical research and make insightful discoveries about diseases. However, access to such data is often limited by patient privacy concerns, data sharing restrictions and […]
Decision-Making Criteria and Methods for Initiating Late-Stage Clinical Trials in Drug Development from a Multi-Stakeholder Perspective: A Scoping Review
Event: PSI 2025, Verona, Italy Authors: Ce Jiang, Céline Beji, Sonia Zebachi, Ghinwa Y. Hayek, Aysun Cetinyurek-Yavuz, Muhammad Bergas N. Fayyad, Laura Rodwell, Kit C. B. Roes, Billy Amzal, Christoph Gerlinger, Raphaël Porcher, Julien Tanniou View Abstract The decision-making process in drug development involves “go/no-go” decisions, particularly at the transition from early to late-stages trials. While the decisions are solely made by drug developers, they must […]
Federated Learning: A Privacy-Preserving Approach to Data-Centric Regulatory Cooperation
Publisher: Frontiers in Drug Safety and RegulationAuthors: Alexander Horst, Paul Loustalot, Sanjeev Yoganathan, Ting Li, Joshua Xu, Weida Tong, David Schneider, Nicolas Löffler-Perez, Erminio Di Renzo, Michael Renaudin View Publication Abstract Regulatory agencies aim to ensure the safety and efficacy of medical products but often face legal and privacy concerns that hinder collaboration at the […]
