Federated analyses of multiple data sources in drug safety studies

Studies of rare side effects of new drugs with limited exposure may require pooling of multiple data sources. Federated Analyses (FA) allow real-time, interactive, centralized statistical processing of individual-level data from different data sets without transfer of sensitive personal data.

We review IT-architecture, legal considerations, and statistical methods in FA, based on a Swedish Medical Products Agency methodological development project.

In a review of all post-authorisation safety studies assessed by the EMA during 2019, 74% (20/27 studies) reported issues with lack of precision in spite of mean study periods of 9.3 years. FA could potentially improve precision in such studies. Depending on the statistical model, the federated approach can generate identical results to a standard analysis. FA may be particularly attractive for repeated collaborative projects where data is regularly updated. There are also important limitations. Detailed agreements between involved parties are strongly recommended to anticipate potential issues and conflicts, document a shared understanding of the project, and fully comply with legal obligations regarding ethics and data protection. FA do not remove the data harmonisation step, which remains essential and often cumbersome. Reliable support for technical integration with the local server architecture and security solutions is required. Common statistical methods are available, but adaptations may be required.

Federated Analyses require competent and active involvement of all collaborating parties but have the potential to facilitate collaboration across institutional and national borders and improve the precision of postmarketing drug safety studies.