ABSTRACT
Introduction
Drug-drug interactions (DDIs) are defined as the pharmacological effects produced by the concomitant administration of two or more drugs. To minimize false positive signals and ensure their validity when analyzing Spontaneous Reporting System (SRS) databases, it has been suggested to incorporate key pharmacological principles, such as temporal plausibility.
Areas covered
The scoping review of the literature was completed using MEDLINE from inception to March 2023. Included studies had to provide detailed methods for identifying DDIs in SRS databases. Any methodological approach and adverse event were accepted. Descriptive analyzes were excluded as we focused on automatic signal detection methods. The result is an overview of all the available methods for DDI signal detection in SRS databases, with a specific focus on the evaluation of the co-exposure time of the interacting drugs. It is worth noting that only a limited number of studies (n = 3) have attempted to address the issue of overlapping drug administration times.
Expert opinion
Current guidelines for signal validation focus on factors like the number of reports and temporal association, but they lack guidance on addressing overlapping drug administration times, highlighting a need for further research and method development.
Article highlights
When it comes to the analysis of drug-drug interactions (DDIs), the problem of false-positive signals is exacerbated by a lack of methodological control for important confounding factors, such as temporal plausibility.
Only a limited number of studies have attempted to address the issue of overlapping drug administration times, and there are currently no official guidelines provided by regulatory agencies to tackle this specific challenge.
This scoping review provides an overview of all the methodologies that have been used so far to detect drug-drug interactions and underscores the need to adopt enhanced methodologies that incorporate temporal considerations in DDI analysis.
Among the 82 studies identified in this scoping review, only 3 considered time in identifying DDIs when using spontaneous reporting system databases. These three studies have harnessed the concept of co-exposure time to evaluate signals arising from DDIs. The authors adeptly showcased that integrating these variables, notably the concurrent duration of both drugs involved in the suspected interaction, holds superior efficacy compared to relying solely on disproportionality analysis.
Declarations of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Acknowledgments
We want to acknowledge Niklas Norén for the comments he provided at a late stage in the project to help us understand better the methodological aspects that are described in our work. VB is enrolled in the PhD in Experimental and Clinical Pharmacological Sciences, Università degli Studi di Milano, which supports her fellowship.
Authors contributions
V Battini and M Sessa conceived and designed the study. V Battini and M Cocco performed the research and analyzed the data. M Cocco and V Battini wrote the original draft which was reviewed and edited by MA Barbieri, M Sessa, C Carnovale and E Clementi. MA Barbieri, C Carnovale and E Clementi participated in the interpretation of the data and revised and approved the final article as submitted.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/17512433.2024.2343875