IX. Add I.1. Introduction

Monitoring of databases of spontaneously reported suspected adverse reactions (in the format of individual case safety reports (ICSRs), see GVP Module VI) is an established method of signal detection. The monitoring process is facilitated by statistical summaries of the information received for each “drug-event” combination over defined time periods. To limit the chances of failing to detect a signal and to ensure that the processes in place are controlled and predictable in terms of resources required, it is recommended that these summaries are produced in a routine periodic fashion. For the same reasons, when possible, the criteria for selecting “drug-event” combinations (DECs) for further investigation should be objectively defined. The aim of this Addendum to GVP Module IX on signal management is to describe components of an effective system for routine scanning of accumulating data focusing on components that have been proved to be effective. It does not give details of particular implementations of such system because these may be influenced by a number of factors that differ between databases. For those interested in the specific implementation developed for use in EudraVigilance other guidance is available (see Screening for Adverse Drug Reactions in EudraVigilance (1) ). In common with other GVP documents, the information given herein is guidance on good practice to assist in ensuring compliance with Commission Implementing Regulation (EU) No 520/2012 (2) . Other methods may also satisfy this requirement.

This Addendum lists some of the methodological aspects that should be considered in detecting potential signals. The proposed approach complements the classical disproportionality analysis with additional data summaries, based on both statistical and clinical considerations. Although disproportionality methods have been demonstrated to detect many adverse reactions before other currently used methods of signal detection, this is not true for all types of adverse reactions. Hence a comprehensive and efficient routine signal detection system will seek to integrate a number of different methods to prioritise DECs for further evaluation.

The specific details of implementation of the methods proposed may vary depending on, for example, the nature of the medicinal products in the dataset or the rate at which new ICSRs are received. The approaches to signal detection discussed herein have been tested in a number of large and medium sized reporting databases (3) with some variations in performance (see IX. Add I.2.1.2.) noted between databases. Thus, a general principle is that any system of signal detection should be monitored not only for overall effectiveness but for the effectiveness of its components (e.g. statistical methods and specific group analyses).

The decision based on the assessment of the data summaries described herein is whether more detailed review of ICSRs should be undertaken. Such review may then prompt a search for additional data from other pharmacovigilance data sources. The decision process may rely on factors beyond the data summaries, for instance if the suspected adverse reaction is a specific incidence of a class of events already listed in the summary of product characteristics (SmPC). So far as possible the decision process should be formally pre-specified and validated. In each case it should be fully documented.

IX. Add I.1.1. Abbreviations