In designing signal detection systems, careful consideration should be given to the criteria that are used to define an SDR. The choice of disproportionality statistic does not appreciably affect the achievable range of signal detection performance and so this can primarily be based on ease of implementation, interpretation and minimisation of computing resources. The changes in sensitivity and precision obtainable by replacing one algorithm with another are predictable. However, the absolute performance of a method is specific to the database and is best assessed directly on that database. New methods may be required to gain appreciable improvements.

Over a period of 5 years, the Innovative Medicines Initiative PROTECT (Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium) project has addressed key research questions relevant to the science of safety signal detection. The results of studies conducted into quantitative signal detection in spontaneous reporting, clinical trial and electronic health records databases are summarised and 39 recommendations have been formulated, many based on comparative analyses across a range of databases (e.g. regulatory, pharmaceutical company). The recommendations point to pragmatic steps that those working in the pharmacovigilance community can take to improve signal detection practices, whether in a national or international agency or in a pharmaceutical company setting. PROTECT has also pointed to areas of potentially fruitful future research and some areas where further effort is likely to yield less.

The analysis of safety data from spontaneous reporting systems has a proven value for the detection and analysis of the risks of medicines following their placement on the market and use in medical practice. EudraVigilance is the pharmacovigilance database to manage the collection and analysis of suspected adverse reactions to medicines authorised in the European Economic Area. EudraVigilance first operated in December 2001, with access to the database being governed by the EudraVigilance access policy. We performed a literature search including data up to December 2016 to demonstrate how the data from EudraVigilance has been used in scientific publications. We describe the results, including by type of publication, research topics and drugs involved. In 50% of the publications, the data are used to describe safety issues, in 44% to analyse methodologies used in pharmacovigilance activities and in 6% to support clinical perspectives. We also outline a description of the use of the database by the European Union regulatory network. Driven by the full implementation of the 2010 pharmacovigilance legislation, EudraVigilance has undergone further enhancements together with a major revision of its access policy, taking into account the use of the new individual case safety report standard developed by the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use and the International Organization for Standardization. The aim of the broadened access is to facilitate more effective safety monitoring of authorised medicines, to make more data available for research and to provide better access to information on suspected adverse reactions for healthcare professionals and patients. In November 2017, the new full functionalities of EudraVigilance were launched, including the extensive web access to data on suspected adverse drug reactions and the possibilities for academic research institutions to request a more extensive dataset for the purposes of health research. The main objective of this article is to describe the new access to the database together with the opportunities that this new access can bring for research. It is intended to promote an appropriate use of the data to support the safe and effective use of medicines.Electronic supplementary materialThe online version of this article (10.1007/s40264-018-0647-1) contains supplementary material, which is available to authorized users.

Patient reporting complemented reporting by HCPs. Patients were motivated to report ADRs, especially those that affected their quality of life. Sharing these results with NCAs and patient associations can inform training and awareness on patient reporting.

Subgroup analyses perform better than stratified analyses and should be considered over the latter in routine first-pass signal detection. Subgroup analyses are also clearly beneficial over crude analyses for larger databases, but further validation is required for smaller databases.