A Feasibility Study of Drug–Drug Interaction Signal Detection in Regular Pharmacovigilance

Abstract

Introduction Adverse drug reactions related to drug-drug interactions cause harm to patients. There is a body of research on signal detection for drug interactions in collections of individual case reports, but limited use in regular pharmacovigilance. Objective The aim of this study was to evaluate the feasibility of signal detection of drug-drug interactions in collections of individual case reports of suspected adverse drug reactions. Methods This study was conducted in VigiBase, the WHO global database of individual case safety reports. The data lock point was 31 August 2016, which provided 13.6 million reports for analysis after deduplication. Statistical signal detection was performed using a previously developed predictive model for possible drug interactions. The model accounts for an interaction disproportionality measure, expressed suspicion of an interaction by the reporter, potential for interaction through cytochrome P450 activity of drugs, and reported information indicative of unexpected therapeutic response or altered therapeutic effect. Triage filters focused the preliminary signal assessment on combinations relating to serious adverse events with case series of no more than 30 reports from at least two countries, with at least one report during the previous 2 years. Additional filters sought to eliminate already known drug interactions through text mining of standard literature sources. Preliminary signal assessment was performed by a multidisciplinary group of pharmacovigilance professionals from Uppsala Monitoring Centre and collaborating organizations, whereas in-depth signal assessment was performed by experienced pharmacovigilance assessors. Results We performed preliminary signal assessment for 407 unique drug pairs. Of these, 157 drug pairs were considered already known to interact, whereas 232 were closed after preliminary assessment for other reasons. Ten drug pairs were subjected to in-depth signal assessment and an additional eight were decided to be kept under review awaiting additional reports. The triage filters had a major impact in focusing our preliminary signal assessment on just 14% of the statistical signals generated by the predictive model for drug interactions. In-depth assessment led to three signals communicated with the broader pharmacovigilance community, six closed signals and one to be kept under review. Conclusion This study shows that signals of adverse drug interactions can be detected through broad statistical screening of individual case reports. It further shows that signal assessment related to possible drug interactions requires more detailed information on the temporal relationship between different drugs and the adverse event. Future research may consider whether interaction signal detection should be performed not for individual adverse event terms but for pairs of drugs across a spectrum of adverse events.

Adverse drug reactions in SARS-CoV-2 hospitalised patients: a case-series with a focus on drug–drug interactions

“…Off-label drug utilisation and DDIs are well known causes of ADRs in the general population [ 25 ], and the risk of DDI-related ADRs typically increases in patients exposed to c drugs, such as those aged ≥ 65 years [ 24 ]. In the case of COVID-19 pandemic, lacking of specific pharmacological treatments forced clinicians and regulatory agencies to resort to currently available drugs.…”

Identifying and Characterizing Serious Adverse Drug Reactions Associated With Drug-Drug Interactions in a Spontaneous Reporting Database

“…Up to 14% of ADRs in the hospital setting have been caused by DDIs ( Sánchez Muñoz-Torrero et al, 2010 ), although the clinical relevance of multiple DDIs and their actual clinical importance may be underestimated. A spontaneous reporting database could be an appropriate and valid source to identify, characterize and to quantify the suspected ADRs resulting from DDIs ( Van Puijenbroek et al, 2000 ; Thakrar et al, 2007 ; Hult et al, 2020 ). This was the starting point for a previous article in which we described the percentage and characteristics of patients exposed to a potential DDI who experienced a related ADR by analyzing an Italian spontaneous reporting database ( Leone et al, 2010 ), though without focusing on the seriousness of DDI.…”

Drug-Drug Interactions Leading to Adverse Drug Reactions with Rivaroxaban: A Systematic Review of the Literature and Analysis of VigiBase

“…VigiBase has inherent limitations, as all ADR reporting databases [ 99 ]. Underreporting and selective reporting are the two first limitations worth mentioning.…”