Verification of the "Upward Variation in the Reporting Odds Ratio Scores" to Detect the Signals of Drug-Drug Interactions

Timing Matters: A Machine Learning Method for the Prioritization of Drug-Drug Interactions Through Signal Detection in the FDA Adverse Event Reporting System and Their Relationship with Time of Co-exposure

INTRODUCTION

Current drug-drug interaction (DDI) detection methods often miss the aspect of temporal plausibility, leading to false-positive disproportionality signals in spontaneous reporting system (SRS) databases.

OBJECTIVE

This study aims to develop a method for detecting and prioritizing temporally plausible disproportionality signals of DDIs in SRS databases by incorporating co-exposure time in disproportionality analysis.

METHODS

The method was tested in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The CRESCENDDI dataset of positive controls served as the primary source of true-positive DDIs. Disproportionality analysis was performed considering the time of co-exposure. Temporal plausibility was assessed using the flex point of cumulative reporting of disproportionality signals. Potential confounders were identified using a machine learning method (i.e. Lasso regression).

RESULTS

Disproportionality analysis was conducted on 122 triplets with more than three cases, resulting in the prioritization of 61 disproportionality signals (50.0%) involving 13 adverse events, with 61.5% of these included in the European Medicine Agency's (EMA's) Important Medical Event (IME) list. A total of 27 signals (44.3%) had at least ten cases reporting the triplet of interest, and most of them (n = 19; 70.4%) were temporally plausible. The retrieved confounders were mainly other concomitant drugs.

CONCLUSIONS

Our method was able to prioritize disproportionality signals with temporal plausibility. This finding suggests a potential for our method in pinpointing signals that are more likely to be furtherly validated.

Reply to: Peptic ulcers with ChEIs, NSAIDs

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Exploring the impact of co-exposure timing on drug-drug interactions in signal detection through spontaneous reporting system databases: a scoping review

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.

Contribution of aldehyde oxidase to methotrexate-induced hepatotoxicity: in vitro and pharmacoepidemiological approaches

BACKGROUND

Methotrexate (MTX) is partially metabolized by aldehyde oxidase (AOX) in the liver and its clinical impact remains unclear. In this study, we aimed to demonstrate how AOX contributes to MTX-induced hepatotoxicity in vitro and clarify the relationship between concomitant AOX inhibitor use and MTX-associated liver injury development using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS).

METHODS

We assessed intracellular MTX accumulation and cytotoxicity using HepG2 cells. We used the FAERS database to detect reporting odds ratio (ROR)-based MTX-related hepatotoxicity event signals.

RESULTS

AOX inhibition by AOX inhibitor raloxifene and siRNA increased the MTX accumulation in HepG2 cells and enhanced the MTX-induced cell viability reduction. In the FAERS analysis, the ROR for MTX-related hepatotoxicity increased with non-overlap of 95% confidence interval when co-administered with drugs with higher Imax, u (maximum unbound plasma concentration)/IC50 (half-maximal inhibitory concentration for inhibition of AOX) calculated based on reported pharmacokinetic data.

CONCLUSION

AOX inhibition contributed to MTX accumulation in the liver, resulting in increased hepatotoxicity. Our study raises concerns regarding MTX-related hepatotoxicity when co-administered with drugs that possibly inhibit AOX activity at clinical concentrations.

Examining the safety of mirabegron: an analysis of real-world pharmacovigilance data from the US FDA adverse event reporting system (FAERS) database

Background: Mirabegron, the first β-3 adrenergic receptor agonist, received approval from the Food and Drug Administration (FDA) in 2012 for the treatment of overactive bladder (OAB). This pharmacovigilance study investigated the safety profile of mirabegron treatment using the US FDA Adverse Event Reporting System (FAERS) database. Methods: This study employed disproportionality analyses, including the reporting odds ratio (ROR) and Bayesian Confidence Propagation Neural Network (BCPNN) algorithm, to quantify signals of adverse events associated with mirabegron. Results: From the first quarter of 2012 to the third quarter of 2023, a comprehensive total of 14,356,234 adverse event (AE) reports were submitted to the FDA Adverse Event Reporting System database. Within this dataset, encompassing 18,763 reports specifically associated with mirabegron, healthcare professionals notably contributed 2,902 of these reports. A total of 80 preferred terms (PTs) of interest were identified using both the ROR and information component algorithms. The most common AEs included blood pressure increased, urinary retention, atrial fibrillation, dry mouth, and tachycardia, which were consistent with the product instructions. Unexpected significant AEs, such as arrhythmia, palpitations, dementia, transient ischemic attack, Parkinson's disease, anti-neutrophil cytoplasmic antibody positive vasculitis, lip swelling, and swollen tongue, were also identified. The study findings indicated that the majority of onset time occurred within 30 days (n = 358, 55.68%). However, AEs were still possible after 1 year of mirabegron treatment. Conclusion: This study provided valuable evidence for the real-world safety of mirabegron, helping clinical professionals enhance their understanding of mirabegron's safety in clinical practice. It also contributed valuable evidence for further safety studies on mirabegron.

Comparative study on the occurrence of adverse effects in the concomitant use of azathioprine and aldehyde oxidase inhibitors

OBJECTIVES

Aldehyde oxidase (AO) is a molybdenum-containing redox enzyme similar to xanthine oxidase that is involved in the thiopurine metabolism. This study investigated the effects of drug-drug interactions (DDIs) between azathioprine (AZA) and AO inhibitors on hematologic and hepatic disorders using the U.S. Food and Drug Administration Adverse Event Reporting System and the Japanese Adverse Drug Event Report database.

METHODS

The presence of DDI was assessed using the interaction signal scores (ISSs) calculated via the reporting odds ratios and 95% confidence intervals. The study used reports of 'azathioprine' as a suspect drug for adverse effects. AO inhibitors were selected based on previous in vitro reports.

RESULTS

Some drugs tested positive for ISSs in each database and type of adverse effect (hematologic or hepatic disorder) analysis. Among these drugs, chlorpromazine, clozapine, hydralazine, and quetiapine could inhibit AZA metabolism via AO, given the previously reported clinical blood concentration and inhibitory effects of each drug.

CONCLUSION

Concomitant use of AO inhibitors increased the signals for AZA-induced adverse effects. To date, no studies have evaluated the clinical importance of AO as a drug-metabolizing enzyme, and further in vitro and clinical research is needed to clarify the contribution of AO to the pharmacokinetics of thiopurines.

Drug Repurposing Using FDA Adverse Event Reporting System (FAERS) Database

Drug repurposing is an emerging approach to reassigning existing pre-approved therapies for new indications. The FDA Adverse Event Reporting System (FAERS) is a large database of over 28 million adverse event reports submitted by medical providers, patients, and drug manufacturers and provides extensive drug safety signal data. In this review, four common drug repurposing strategies using FAERS are described, including inverse signal detection for a single disease, drug-drug interactions that mitigate a target ADE, identifying drug-ADE pairs with opposing gene perturbation signatures and identifying drug-drug pairs with congruent gene perturbation signatures. The purpose of this review is to provide an overview of these different approaches using existing successful applications in the literature. With the fast expansion of adverse drug event reports, FAERS-based drug repurposing represents a promising strategy for discovering new uses for existing therapies.

Association between road traffic accidents and drugs belonging to the antiseizure medications class: A pharmacovigilance analysis in VigiBase

AIMS

Due to their central mechanism of action, antiseizure medications (ASMs) could lead to adverse effects likely to impair driving skills. Their extended use to neuropsychiatric disorders makes it a class of drugs to monitor for their road traffic accidental (RTA) potential. We aimed to assess the reporting association between ASMs and RTAs using the World Health Organization pharmacovigilance database (VigiBase).

METHODS

We performed a disproportionality analysis to compute adjusted reporting odds ratios to evaluate the strength of reporting association between ASMs and RTAs. A univariate analysis using the reporting odds-ratio was used to assess drug-drug interactions between ASMs and RTAs.

RESULTS

There were 1 341 509 reports associated with at least 1 ASM in VigiBase of whom 2.91‰ were RTAs reports. Eight ASMs were associated with higher reporting of RTAs compared to others (ranging from 1.35 [95% confidence interval 1.11-1.64] for lamotrigine to 4.36 [95% confidence interval 3.56-5.32] for cannabis). Eight significant drug-drug interactions were found between ASMs and the onset of RTA, mainly involving CYP450 induction.

CONCLUSION

A significant safety signal between RTAs and some ASMs was identified. Association of several ASMs might further increase the occurrence of RTA. ASMs prescription in patients with identified risk factors of RTA should be considered with caution. Study number: ClinicalTrials.gov, NCT04480996.