The enhanced national pharmacovigilance system implemented for COVID-19 vaccines in France: A 2-year experience report.

In March 2020, World Health Organization recognized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emergence as a public health emergency of international concern. One of the major preventative measures developed against coronavirus disease 2019 (COVID-19) was vaccines. To monitor their use and safety of vaccines from the first utilization in humans during clinical development phases to implementation for the general population, an enhanced national pharmacovigilance system was enabled by the French National Agency for Medicines and Health Products Safety in collaboration with the 30 Regional Pharmacovigilance Centres.

Validation of Artificial Intelligence to Support the Automatic Coding of Patient Adverse Drug Reaction Reports, Using Nationwide Pharmacovigilance Data.

Introduction: Adverse drug reaction reports are usually manually assessed by pharmacovigilance experts to detect safety signals associated with drugs. With the recent extension of reporting to patients and the emergence of mass media-related sanitary crises, adverse drug reaction reports currently frequently overwhelm pharmacovigilance networks. Artificial intelligence could help support the work of pharmacovigilance experts during such crises, by automatically coding reports, allowing them to prioritise or accelerate their manual assessment.

French organization for the pharmacovigilance of COVID-19 vaccines: A major challenge.

In this special issue, we present the main highlights of the first weeks of pharmacovigilance monitoring of coronavirus disease 2019 (COVID-19) vaccines in this unprecedented situation in France: the deployment of a vaccination during an epidemic period with the aim of vaccinating the entire population and the intense pharmacovigilance and surveillance of these vaccines still under conditional marketing authorizations. In this unprecedented situation, the cross approach and interaction between the French pharmacovigilance network and French National Agency for the Safety of Medicines and Health Products (ANSM) has been optimized to provide a real-time safety related to COVID-19 vaccines. Every week, pair of regional pharmacovigilance centers gathered safety data from the French pharmacovigilance network, to acutely expertise all the adverse drug reactions (ADRs) reported with each COVID-19 vaccine within a direct circuit with ANSM.

Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.

Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage to deal with its tremendous flow of information, based primarily on unstructured text fields. The aim of this study was to develop an automated system allowing to code ADRs from patient reports. Our system was based on a knowledge base about drugs, enriched by supervised machine learning (ML) models trained on patients reporting data.

Contribution of Causality Assessment for an Automated Detection of Safety Signals: An Example Using the French Pharmacovigilance Database.

Introduction: Qualitative approaches based on drug causality assessment estimate the causal link between a drug and the occurrence of an adverse event from individual case safety reports. Quantitative approaches based on disproportionality analyses were developed subsequently to allow automated statistical signal detection from pharmacovigilance databases. This study assessed the potential value of causality assessment for automated safety signal detection.

Benefits of combining change-point analysis with disproportionality analysis in pharmacovigilance signal detection.

Background: Change-point analysis (CPA) is a powerful method to analyse pharmacovigilance data but it has never been used on the disproportionality metric.

Objectives: To optimize signal detection investigating the interest of time-series analysis in pharmacovigilance and the benefits of combining CPA with the proportional reporting ratio (PRR).

Methods: We investigated the couple benfluorex and aortic valve incompetence (AVI) using the French National Pharmacovigilance and EudraVigilance databases: CPA was applied on monthly counts of reports and the lower bound of monthly computed PRR (PRR-).

A pre-clinical assessment of an atlas-based automatic segmentation tool for the head and neck.

Background And Purpose: Accurate conformal radiotherapy treatment requires manual delineation of target volumes and organs at risk (OAR) that is both time-consuming and subject to large inter-user variability. One solution is atlas-based automatic segmentation (ABAS) where a priori information is used to delineate various organs of interest. The aim of the present study is to establish the accuracy of one such tool for the head and neck (H&N) using two different evaluation methods.