Key Elements in Adverse Drug Interaction Safety Signals

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.

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

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.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00939-y) contains supplementary material, which is available to authorized users.

Drug interactions with apixaban: A systematic review of the literature and an analysis of VigiBase, the World Health Organization database of spontaneous safety reports

Apixaban, a direct oral anticoagulant, has emerged over the past few years because it is considered to have a low risk of drug‐drug interactions compared to vitamin K antagonists. To better characterize these interactions, we systematically reviewed studies evaluating the drug‐drug interactions involving apixaban and analyzed the drug‐drug interactions resulting in an adverse drug reaction reported in case reports and VigiBase. We systematically searched Medline, Embase, and Google Scholar up to 20 August 2018 for articles that investigated the occurrence of an adverse drug reaction due to a potential drug interacting with apixaban. Data from VigiBase came from case reports retrieved up to the 2 January 2018, where identification of potential interactions is performed in terms of two drugs, one adverse drug reaction triplet and potential signal detection using Omega, a three‐way measure of disproportionality. We identified 15 studies and 10 case reports. Studies showed significant variations in the area under the curve for apixaban and case reports highlighted an increased risk of hemorrhage or thromboembolic events due to a drug‐drug interaction. From VigiBase, a total of 1617 two drugs and one adverse drug reaction triplet were analyzed. The most reported triplet were apixaban—aspirin—gastrointestinal hemorrhage. Sixty‐seven percent of the drug‐drug interactions reported in VigiBase were not described or understood. In the remaining 34%, the majority were pharmacodynamic drug‐drug interactions. These data suggest that apixaban has significant potential for drug‐drug interactions, either with CYP3A/P‐gp modulators or with drugs that may impair hemostasis. The most described adverse drug reactions were adverse drug reactions related to hemorrhage or thrombosis, mostly through pharmacodynamic interactions. Pharmacokinetic drug‐drug interactions seem to be poorly detected.

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

Rivaroxaban has become an alternative to vitamin K antagonists, which are considered to be at higher risk of drug-drug interactions (DDI) and more difficult to use. However, DDI do occur. We systematically reviewed studies that evaluated them and analysed DDI and subsequent adverse drug reactions (ADR) reported in spontaneous reports and VigiBase. We systematically searched articles that explored DDI with rivaroxaban up to 20 August 2018 via Medline, Embase and Google Scholar. Data from VigiBase came from spontaneous reports recovered up to 2 January 2018, where Omega was used to detect signals and identify potential interactions in terms of triplets with two drugs and one ADR. We identified 31 studies and 28 case reports. Studies showed significant variation in the pharmacokinetic for rivaroxaban, and an increased risk of haemorrhage or thromboembolic events due to DDI was highlighted in case reports. From VigiBase, a total of 21,261 triplets were analysed and the most reported was rivaroxaban–aspirin–gastrointestinal haemorrhage. In VigiBase, only 34.8% of the DDI reported were described or understood, and most were pharmacodynamic DDI. These data suggest that rivaroxaban should be considered to have significant potential for DDI, especially with CYP3A/P-gp modulators or with drugs that impair haemostasis.

Characteristics of drugs safety signals that predict safety related product information update

Purpose

Investigation of drug safety signals is one of the major tasks in pharmacovigilance. Among many potential signals identified, only a few reflect adverse drug reactions requiring regulatory actions, such as product information (PI) update. Limited information is available regarding the signal characteristics that might predict PI update following signal evaluation. The objective of this study was to identify signal characteristics associated with PI updates following signal evaluation by the European Medicines Agency Pharmacovigilance Risk Assessment Committee during 2012 to 2016.

Methods

A comparative study was performed based on data from 172 safety signals. Characteristics of signals were extracted from the European Pharmacovigilance Issues Tracking Tool database. Multivariable logistic regression analysis was used to assess the relationship between signal characteristics and the decision to update the PI.

Results

Multivariable logistic regression analysis showed that the presence of evidence in multiple types of data sources (adjusted odds ratio [OR] 7.8 95% CI [1.5, 40.1]); mechanistic plausibility of the drug‐event association (adjusted OR 3.9 95% CI [1.9, 8.0]); seriousness of the event (adjusted OR 4.2 95% CI [1.3, 13.9]); and age of drugs ≤5 years (adjusted OR 3.9 95% CI [1.2, 12.7]) were associated with the decision to change the PI (P < 0.05).

Conclusions

This study identified 4 characteristics of drug safety signals that have shown to be associated with PI changes as outcome of signal evaluation. These characteristics may be used as criteria for selection and prioritization of potential signals that are more likely to necessitate product information updates.

[Pristinamycin/Vitamin k antagonists drug interaction: a French pharmacovigilance database study]

OBJECTIVE

To analyse pristinamycin/vitamin K antagonists (VKA) drug interaction by using data recorded in the French pharmacovigilance database (FPVB).

METHODS

All cases with an increase effect of a VKA and an association with pristinamycin recorded in the FPVB between 1985 and 2013 were included. Data concerning patients, VKA treatments and side effects were recorded for a descriptive analysis.

RESULTS

During this period, 31 reports with a VKA overdose after an association with pristinamycin were included. Fluindione is the most often involved VKA (77% of cases). In 20 cases (65.4%), VKA overdose caused bleeding and 24 cases (77.4%) were serious.

CONCLUSION

Although mechanism is unknown, pristinamycine/AVK drug interaction is a reality that needs to be reported in the summary of product characteristics of these drugs and better known by practitioners to act in patients' interest.

Drug-induced liver injury: what was new in 2013?

INTRODUCTION

The year 2013 continued to highlight numerous aspects of drug-induced liver injury (DILI), with new information communicated via > 1500 publications. New reports of DILI were described and FDA warnings and alerts were issued for a number of products, emphasizing the risks related to hepatotoxicity.

AREAS COVERED

We provide a summary of the year's published reports of new causes of DILI, along with reviews and reports of established hepatotoxins, new and expanded DILI registries and the continuing emphasis placed on genetic and other risk factors. Several new analyses of data generated from the US DILI Network are included.

EXPERT OPINION

The clinical usefulness of pharmacogenetic testing remains to be determined; the number of patients who must be tested is large and the overall risk of DILI is quite small. The role that dose and hepatic metabolism play in causing idiosyncratic DILI was reviewed; daily doses > 50 - 100 mg of medications with high lipophilicity appear to be most predictive of severe DILI, but not in all cases. Restricting access to paracetamol in certain parts of the UK continues to demonstrate a successful reduction in the number of acute liver failure cases and patients listed for liver transplant.

Pharmacovigilance and drug safety in Calabria (Italy): 2012 adverse events analysis

INTRODUCTION

Pharmacovigilance (PV) is designed to monitor drugs continuously after their commercialization, assessing and improving their safety profile. The main objective is to increase the spontaneous reporting of adverse drug reactions (ADRs), in order to have a wide variety of information. The Italian Drug Agency (Agenzia Italiana del Farmaco [AIFA]) is financing several projects to increase reporting. In Calabria, a PV information center has been created in 2010.

MATERIALS AND METHODS

We obtained data using the database of the National Health Information System AIFA relatively to Italy and Calabria in the year 2012. Descriptive statistics were performed to analyze the ADRs.

RESULTS

A total number of 461 ADRs have been reported in the year 2012 with an increase of 234% compared with 2011 (138 reports). Hospital doctors are the main source of this reporting (51.62%). Sorafenib (Nexavar(®)), the combination of amoxicillin/clavulanic acid and ketoprofen represent the drugs most frequently reported causing adverse reactions. Adverse events in female patients (61.83%) were more frequently reported, whereas the age groups "41-65" (39.07%) and "over 65" (27.9%) were the most affected.

CONCLUSIONS

Calabria has had a positive increase in the number of ADRs reported, although it has not yet reached the gold standard set by World Health Organization (about 600 reports), the data have shown that PV culture is making inroads in this region and that PV projects stimulating and increasing PV knowledge are needed.