Criteria and methods applied to decision-making to embark on late-stage clinical trials with a multi-stakeholder perspective
Event: ISPOR Europe 2023, Copenhagen, Denmark Authors: C. Jiang, J. Tanniou, B. Amzal View Poster Objectives The More-EUROPA project aims at establishing the value of registry-based RWD in enhancing RCT data and enabling a more effective and ethical use of registry data to support patient-centred regulatory and HTA decision-making. Work package 1 (WP1) is specifically […]
Existing automated tools to assist evidence generation and better qualification of registries and real-world data. A systematic review from the More-EUROPA project
Event: ISPOR Europe 2023, Copenhagen, Denmark Authors: P. Godbillot, P. Tang, J. Moreira, J. Tanniou S. Zebachi, B. Amzal View Poster Objectives The More-EUROPA project consortium brings together 14 public and private entities from 7 countries with the aim of enhancing the ethical and effective utilization of registry data to facilitate patient-centered decision-making by drug regulators and Health Technology Assessment […]
AliBERT: A pretrained Language Model for French Biomedical Text
Event : BioNLP 2023 Workshop at ACL (Association for Computational Linguistics)Authors: A. Berhe, G. Draznieks, V. Martenot, V. Masdeu, L. Davy, J-D. Zucker View publication Background Over the past few years, domain specific pretrained language models have been investigated and have shown remarkable achievements in different downstream tasks, especially in biomedical domain. These achievements stem on the well known BERT […]
L’intelligence artificielle au service de la modélisation de maladies en vie réelle : vision, exemples et impact sur l’évaluation des médicaments
Event: Colloque de Données de Santé en vie réelle, AFCROs 2023, Boulogne-Billancourt, France Authors: M. Génin, M. Rollot, A. Movschin, B. Amzal, J. Tanniou View Poster Introduction Le rôle des données de vie réelle (RWD) devient de plus en plus important dans les évaluations réglementaires et HTA, en compléments des essais randomisés (RCT), notamment pour anticiper […]
AI/ML in Precision Medicine: A Look Beyond the Hype
Publisher: Therapeutic Innovation & Regulatory Science (Springer Nature Link)Authors: Z. Xu, B. Biswas, L. Li, B. Amzal View publication Background Artificial Intelligence (AI) and Machine Learning (ML) are making headlines in medical research, especially in drug discovery, digital imaging, disease diagnostics, genetic testing, and optimal care pathway (personalized care). Patients and methods However, the potential uses and […]
AI-Powered Pre-Competitive Disease and Care Modeling: Building a Reference Disease-Centric Framework for Value-Based Decision Making
Event: ISPOR 2023, Boston, MA, USA Authors: B. Amzal, A. Movschin, A. Chiorean,J. Tanniou, M. Rollot, M. Génin View Poster Objectives Drugs evaluation has been undergoing a transformational shift from the classical sequence of randomized control trials (RCT) and Real-World (RW) studies towards a more agile process, capitalizing better and faster from retrospective data. The purpose of this […]
Qluster: An easy-to-implement generic workflow for robust clustering of health data
Publisher: Frontiers in Artificial IntelligenceAuthors: C. Esnault, M. Rollot, P. Guilmin, J-D. Zucker View publication Background The exploration of heath data by clustering algorithms allows to better describe the populations of interest by seeking the sub-profiles that compose it. This therefore reinforces medical knowledge, whether it is about a disease or a targeted population in real life. Nevertheless, […]
LiSA : an assisted literature search pipeline for detecting serious adverse drug events with deep learning
Publisher: BMC Medical Informatics and Decision MakingAuthors: V. Martenot, V. Masdeu, J. Cupe, F. Gehin, M. Blanchon, J. Dauriat, A. Horst, M. Renaudin, P. Girard, J-D. Zucker View publication Introduction Detecting safety signals attributed to a drug in scientific literature is a fundamental issue in pharmacovigilance. The constant increase in the volume of publications requires the automation of this tedious task, […]
A Natural Language Processing (NLP) Approach to Automate Patients’ Testimonials Analysis
Event: ISPOR Europe 2022, Vienna, Austria Authors: P. Hayat, C. Clémente, V. Martenot, M. Rollot View Poster Objectives: Patients’ testimonials (e.g. posts on forums or responses to questionnaires) provide valuable insights to define and characterize patient-reported outcomes (PRO), quality of life and patients’ perspective of disease symptoms. However, traditional NLP methods used for automated analysis of patients’ […]
Q-Finder: An Algorithm for Credible Subgroup Discovery in Clinical Data Analysis — An Application to the International Diabetes Management Practice Study
Publisher: Frontiers Artificial IntelligenceAuthors: C. Esnault, M-L. Gadonna, M. Queyrel, A. Templier, J-D. Zucker View publication Background Addressing the heterogeneity of both the outcome of a disease and the treatment response to an intervention is a mandatory pathway for regulatory approval of medicines. In randomized clinical trials (RCTs), confirmatory subgroup analyses focus on the assessment of drugs in […]
