Post marketing surveillance of suspected adverse drug reactions through spontaneous reporting: current status, challenges and the future

Unveiling the future: precision pharmacovigilance in the era of personalized medicine

In the era of personalized medicine, pharmacovigilance faces new challenges and opportunities, demanding a shift from traditional approaches. This article delves into the evolving landscape of drug safety monitoring in the context of personalized treatments. We aim to provide a succinct reflection on the intersection of tailored therapeutic strategies and vigilant pharmacovigilance practices. We discuss the integration of pharmacogenetics in enhancing drug safety, illustrating how genetic profiling aids in predicting drug responses and adverse reactions. Emphasizing the importance of phase IV-post-marketing surveillance, we explore the limitations of pre-marketing trials and the necessity for a comprehensive approach to drug safety. The article discusses the pivotal role of pharmacogenetics in pre-exposure risk management and the redefinition of pharmacoepidemiological methods for post-exposure surveillance. We highlight the significance of integrating patient-specific genetic profiles in creating personalized medication leaflets and the use of advanced computational methods in data analysis. Additionally, we examine the ethical, privacy, and data security challenges inherent in precision medicine, emphasizing their implications for patient consent and data management.

Evaluation of the knowledge of and attitudes towards pharmacovigilance among healthcare students in China: a cross-sectional study

BACKGROUND

Knowledge of pharmacovigilance (PV) and adverse drug reactions (ADRs) are the core competencies that healthcare students should acquire during their studies. The objective of this study was to assess attitudes towards and knowledge of PV and ADRs among healthcare students in China.

METHODS

An online, cross-sectional survey was conducted nationally among healthcare students in China from April through October 2023. Knowledge of PV and ADRs was assessed using a questionnaire based on current PV guidelines. We performed logistic regression analysis to determine the potential factors related to knowledge of and attitudes towards PV and ADRs.

RESULTS

A total of 345 students were included in the analysis. Among the healthcare students who participated in the survey, 225 (65.22%) students correctly defined PV, while only 68 (19.71%) had a correct understanding of ADRs. Among all respondents included in the analysis, only 71 (20.58%) reported having taken a PV course. Pharmacy students were more likely to have taken PV courses at a university and to demonstrate superior knowledge compared to other healthcare students. The logistic regression model revealed that the significant predictors of a higher level of PV knowledge were being female (odds ratio [OR]: 1.76; 95% confidence interval (CI): 1.06-2.92; P value: 0.028) and having previously taken PV-related courses (OR: 2.00; 95% CI: 1.06-3.80; P value: 0.034).

CONCLUSIONS

This study revealed that healthcare students' knowledge of PV and ADRs is unsatisfactory. However, there were a limited number of universities providing PV education. Given the vital role of healthcare professionals in identifying and reporting ADRs, our findings raise significant concerns. Hence, more efforts should be made to enhance PV education for future healthcare professionals.

Comparative analysis of adverse drug reactions associated with new antiseizure medications from the Korea Adverse Event Reporting System database

OBJECTIVE

This study aimed to compare and characterize the safety profiles of new antiseizure medications (ASMs) using a nationwide pharmacovigilance database from a long-term perspective in Korea.

METHODS

We reviewed adverse event reports from the Korea Adverse Event Reporting System database between January 2013 and December 2022 for descriptive analysis of six new ASMs (lacosamide, levetiracetam, lamotrigine, oxcarbazepine, topiramate, and zonisamide). We investigated the frequency and characteristics of adverse drug reactions (ADRs) based on the MedDRA terminology, system organ classes, and modified WHO classification.

RESULTS

We identified 5,733 reported cases of ADRs. The commonly reported ADRs associated with total ASMs were rash/urticaria (1,822, 31.8 %), dizziness (409, 7.1 %), somnolence/drowsiness (311, 5.4 %), and hepatotoxic effects (273, 4.8 %). Type B (idiosyncratic) effects (2,932; 51.1 %) were more commonly reported than Type A (related to known drug mechanisms) effects (2,613; 45.6 %). Skin and subcutaneous tissue disorders and type B effects were most commonly reported for lamotrigine and oxcarbazepine, whereas nervous system disorders and type A effects were most commonly reported for lacosamide, topiramate, and zonisamide. The pediatric group (<18 years) exhibited skin and subcutaneous tissue disorders and type B effects relatively more frequently than the adult and older adult groups.

CONCLUSION

Hypersensitivity skin reactions and type B effects remained significant ADRs in the new ASMs; however, type A effects were more commonly reported in some ASMs. The pediatric group showed a higher rate of type B effects. Overall, new ASMs should also be used with caution.

Advancing Adverse Drug Reaction Prediction with Deep Chemical Language Model for Drug Safety Evaluation

The accurate prediction of adverse drug reactions (ADRs) is essential for comprehensive drug safety evaluation. Pre-trained deep chemical language models have emerged as powerful tools capable of automatically learning molecular structural features from large-scale datasets, showing promising capabilities for the downstream prediction of molecular properties. However, the performance of pre-trained chemical language models in predicting ADRs, especially idiosyncratic ADRs induced by marketed drugs, remains largely unexplored. In this study, we propose MoLFormer-XL, a pre-trained model for encoding molecular features from canonical SMILES, in conjunction with a CNN-based model to predict drug-induced QT interval prolongation (DIQT), drug-induced teratogenicity (DIT), and drug-induced rhabdomyolysis (DIR). Our results demonstrate that the proposed model outperforms conventional models applied in previous studies for predicting DIQT, DIT, and DIR. Notably, an analysis of the learned linear attention maps highlights amines, alcohol, ethers, and aromatic halogen compounds as strongly associated with the three types of ADRs. These findings hold promise for enhancing drug discovery pipelines and reducing the drug attrition rate due to safety concerns.

Development, assessment and educational impact of a blended e-learning training program on pharmacovigilance implemented in four African countries

Introduction

Efforts to improve medication access in low-and middle-income countries, particularly in Sub-Saharan Africa, have made progress, especially in the fight against infectious diseases such as tuberculosis. However, challenges exist in establishing effective pharmacovigilance systems. The PhArmacoVIgilance Africa (PAVIA) project was committed to enhancing pharmacovigilance in Tanzania, Eswatini, Nigeria, and Ethiopia, with an emphasis on anti-tuberculosis drugs, utilizing various methods, including training. This study evaluates the PAVIA training program's effectiveness and its adaptation during the COVID-19 pandemic.

Methods

A blended e-learning program, incorporating two courses and a platform for educational materials, was developed. This program, designed to train healthcare professionals in pharmacovigilance, was incorporated into a Training of Trainers model. To evaluate the program effectiveness, we used multiple measures such as assessing knowledge gain through pre-and post-test scores, assessing learners' satisfaction and attitudes via questionnaires, and analyzing Individual Case Safety Reports (ICSRs) in VigiBase to determine the impact on spontaneous reporting systems in the PAVIA countries.

Results

121 learners enrolled in the pilot trainings, including 36 from Tanzania, 34 from Eswatini, 25 from Nigeria, and 26 from Ethiopia. Notably, post-test scores were significantly higher than pre-test scores in all four countries. Following the pilot trainings, multiple step-down training sessions were held in Tanzania, Eswatini, and Nigeria, with a total of 827 learners registering and 421 successfully completing the program. Learners' scores on the post-tests were significantly higher than on the pre-tests for both courses in all three countries. Learners' feedback on the training was overwhelmingly positive. Additionally, a qualitative analysis of ICSRs revealed a substantial increase in reports after the training in Tanzania, Eswatini, and Nigeria.

Discussion

An innovative e-learning program trained healthcare professionals in pharmacovigilance and anti-tuberculosis drug safety over 3 years in four PAVIA countries. The program effectively improved participants' knowledge, received positive feedback, and likely had an impact on reporting rates in Tanzania, Eswatini, and Nigeria, although a direct causal link could not be definitively established due to data limitations and other factors, such as the heightened reporting rates associated with COVID-19 vaccines, that could have contributed to the notable increase in ICSRs.

Applications of Blockchain-Based Technology for Healthcare Devices Post-market Surveillance

The volume of data analysis for medical device post-market surveillance (PMS) has increased dramatically in recent years. It is the more stringent and intricate regulatory criteria of the health authorities that are meant to improve the medical device safety review. As regulators scrutinize device safety more closely, proactive approaches to PMS processes are becoming crucial. To solve some of the issues brought on by this shifting regulatory landscape, new technologies have been investigated. This study envisages the technical features of blockchain technology (BCT) and its role in enhancing the PMS for medical devices. To address the aforementioned challenges, our model involves the establishment of a secure, permissioned blockchain for PMS data management, utilizing a proof-of-authority consensus mechanism. This blockchain framework will exclusively permit a carefully vetted and designated set of participants to validate transactions and record them in the PMS data ledger. The utilization of BCT holds the potential to introduce enhanced efficiency and provide several advantages to the various stakeholders involved in the PMS procedure, including its potential to support emerging regulatory efforts.

Predictive Modeling of Drug-Related Adverse Events with Real-World Data: A Case Study of Linezolid Hematologic Outcomes

Electronic health records (EHRs) provide meaningful knowledge of drug-related adverse events (AEs) that are not captured in standard drug development and postmarketing surveillance. Using variables obtained from EHR data in the University of California San Francisco de-identified Clinical Data Warehouse, we aimed to evaluate the potential of machine learning to predict two hematological AEs, thrombocytopenia and anemia, in a cohort of patients treated with linezolid for 3 or more days. Features for model input were extracted at linezolid initiation (index), and outcomes were characterized from index to 14 days post-treatment. Random forest classification (RFC) was used for AE prediction, and reduced feature models were evaluated using cumulative importance (cImp) for feature selection. Grade 3+ thrombocytopenia and anemia occurred in 31% of 2,171 and 56% of 2,170 evaluable patients, respectively. Of the total 53 features, as few as 7 contributed at least 50% cImp, resulting in prediction accuracies of 70% or higher and area under the receiver operating characteristic curves of 0.886 for grade 3+ thrombocytopenia and 0.759 for grade 3+ anemia. Sensitivity analyses in strictly defined patient subgroups revealed similarly high predictive performance in full and reduced feature models. A logistic regression model with the same 50% cImp features showed similar predictive performance as RFC and good concordance with RFC probability predictions after isotonic calibration, adding interpretability. Collectively, this work demonstrates potential for machine learning prediction of AE risk in real-world patients using few variables regularly available in EHRs, which may aid in clinical decision making and/or monitoring.

Commercialization potential of PET (polyethylene terephthalate) recycled nanomaterials: A review on validation parameters

Polyethylene Terephthalate (PET) is a polymer which is considered as one of the major contaminants to the environment. The PET waste materials can be recycled to produce value-added products. PET can be converted to nanoparticles, nanofibers, nanocomposites, and nano coatings. To extend the applications of PET nanomaterials, understanding its commercialization potential is important. In addition, knowledge about the factors affecting recycling of PET based nanomaterials is essential. The presented review is focused on understanding the PET commercialization aspects, keeping in mind market analysis, growth drivers, regulatory affairs, safety considerations, issues associated with scale-up, manufacturing challenges, economic viability, and cost-effectiveness. In addition, the paper elaborates the challenges associated with the use of PET based nanomaterials. These challenges include PET contamination to water, soil, sediments, and human exposure to PET nanomaterials. Moreover, the paper discusses in detail about the factors affecting PET recycling, commercialization, and circular economy with specific emphasis on life cycle assessment (LCA) of PET recycled nanomaterials.

Harmonization of individual case safety reports transmission requirements among PAHO reference authorities: a review of their current regulation

To perform optimal monitoring of the safety profile in the postmarketing phase, Marketing Authorization Holders and National Regulatory Authorities (NRAs) must evaluate the adverse drug reactions (ADRs) that occurred and characterize their nature, frequency, and severity. Management is possible through Individual Case Safety Reports (ICSRs), which are the reports of organized and processed data. Globally, the International Council for Harmonisation (ICH) E2B guideline suggests harmonized activities for the ICSR electronic content and transmission. In America, the Pan American Health Organization (PAHO) is the agency responsible to implement cooperation among its members, which are recognized as National Regulatory Authorities of Reference (NRARs) such as Argentina, Brazil, Canada, Chile, Colombia, Cuba, Mexico, and the United States. PAHO published the 'Good Pharmacovigilance Practices for the Americas' suggesting improvement and harmonization in the region. After reviewing the regulatory framework, it is assumed that all NRARs have a regulated ICSR transmission system (i.e. a systematic vigilance system for collecting, analyzing, and disseminating information from ADRs). However, significant differences exist, such as the requirement for social media vigilance, expedited and non-expedited ICSRs, coding, severity, and transmission. The volume of ICSRs has significantly increased, due to using electronic standards managed by the NRAs, which facilitates early identification of new ADRs, allowing the implementation of novel minimization activities, contributing to the continuous assessment of the benefit-risk balance of medicines. Nevertheless, there is still area for improvement, especially in Latin America.

Detection of potential safety signals related to the use of remdesivir and tocilizumab in the COVID era during pregnancy, resorting to open data from the FDA adverse event reporting system (FAERS)

Background: The in-hospital treatment for COVID-19 may include medicines from various therapeutic classes, such as antiviral remdesivir and immunosuppressant tocilizumab. Safety data for these medicines are based on controlled clinical trials and case reports, limiting the knowledge about less frequent, rare or unique population adverse events excluded from clinical trials. Objective: This study aims at analyzing the reports of Adverse Drug Events (ADEs) related to these two medicines, focusing on events in pregnant women and foetuses. Methods: Data from the open-access FDA Adverse Event Reporting System (FAERS) from 2020 to 2022 were used to create a dashboard on the Grafana platform to ease querying and analyzing report events. Potential safety signals were generated using the ROR disproportionality measure. Results: Remdesivir was notified as the primary suspect in 7,147 reports and tocilizumab in 19,602. Three hundred and three potential safety signals were identified for remdesivir, of which six were related to pregnant women and foetuses (including abortion and foetal deaths). Tocilizumab accumulated 578 potential safety signals, and three of them were associated with this population (including neonatal death). Discussion: None of the possible signals generated for this population were found in the product labels. According to the NIH and the WHO protocols, both medicines are recommended for pregnant women hospitalized with COVID-19. Conclusion: Despite the known limitations of working with open data from spontaneous reporting systems (e.g., absence of certain clinical data, underreporting, a tendency to report severe events and recent medicines) and disproportionality analysis, the findings suggest concerning associations that need to be confirmed or rejected in subsequent clinical studies.

Utilizing temporal pattern of adverse event reports to identify potential late-onset adverse events

OBJECTIVES

Through the use of FDA adverse event reporting system (FAERS) dataset, this study analyzes the pattern of time-to-event (TTE) for drugs and adverse events, and suggest ways to identify candidate late-onset events for monitoring.

METHODS

The duration between administration date of the drug and the onset of adverse events was explored with using FAERS data from 2012-2021. The fold change of proportional reporting ratios or reporting odds ratios were calculated to identify enriched events in the later period and to suggest the late-onset events for further monitoring. To compare the findings, we used the claims database of the Korean National Health Insurance Service (NHIS).

RESULTS

A total of 1,426,781 reports were included. The median TTE was 10 days (interquartile range [IQR]: 0-98 days), with 11.5% (n = 164,093) reporting events that occurred at least one year after administration. TTE and fold change analysis captured historical cases of late-onset events, while generating an additional less-explored list of events. The results for tumor necrosis factor (TNF) inhibitors were compared using the NHIS dataset.

CONCLUSION

Our study provides a comprehensive analysis of the FAERS dataset, focusing on TTE data. Periodic summarization of reports would be helpful in monitoring the late-onset events.

Characterizing and Comparing Adverse Drug Events Documented in 2 Spontaneous Reporting Systems in the Lower Mainland of British Columbia, Canada: Retrospective Observational Study

BACKGROUND

Robust adverse drug event (ADE) reporting systems are crucial to monitor and identify drug safety signals, but the quantity and type of ADEs captured may vary by system characteristics.

OBJECTIVE

We compared ADEs reported in 2 different reporting systems in the same jurisdictions, the Patient Safety and Learning System-Adverse Drug Reaction (PSLS-ADR) and ActionADE, to understand report variation.

METHODS

This retrospective observational study analyzed reports entered into PSLS-ADR and ActionADE systems between December 1, 2019, and December 31, 2022. We conducted a comprehensive analysis including all events from both reporting systems to examine coverage and usage and understand the types of events captured in both systems. We calculated descriptive statistics for reporting facility type, patient demographics, serious events, and most reported drugs. We conducted a subanalysis focused on adverse drug reactions to enable direct comparisons between systems in terms of the volume and events reported. We stratified results by reporting system.

RESULTS

We performed the comprehensive analysis on 3248 ADE reports, of which 12.4% (375/3035) were reported in PSLS-ADR and 87.6% (2660/3035) were reported in ActionADE. Distribution of all events and serious events varied slightly between the 2 systems. Iohexol, gadobutrol, and empagliflozin were the most common culprit drugs (173/375, 46.2%) in PSLS-ADR, while hydrochlorothiazide, apixaban, and ramipril (308/2660, 11.6%) were common in ActionADE. We included 2728 reports in the subanalysis of adverse drug reactions, of which 12.9% (353/2728) were reported in PSLS-ADR and 86.4% (2357/2728) were reported in ActionADE. ActionADE captured 4- to 6-fold more comparable events than PSLS-ADR over this study's period.

CONCLUSIONS

User-friendly and robust reporting systems are vital for pharmacovigilance and patient safety. This study highlights substantial differences in ADE data that were generated by different reporting systems. Understanding system factors that lead to varying reporting patterns can enhance ADE monitoring and should be taken into account when evaluating drug safety signals.

Drug Repositioning: A Monetary Stratagem to Discover a New Application of Drugs

Drug repurposing, also referred to as drug repositioning or drug reprofiling, is a scientific approach to the detection of any new application for an already approved or investigational drug. It is a useful policy for the invention and development of new pharmacological or therapeutic applications of different drugs. The strategy has been known to offer numerous advantages over developing a completely novel drug for certain problems. Drug repurposing has numerous methodologies that can be categorized as target-oriented, drug-oriented, and problem-oriented. The choice of the methodology of drug repurposing relies on the accessible information about the drug molecule and like pharmacokinetic, pharmacological, physicochemical, and toxicological profile of the drug. In addition, molecular docking studies and other computer-aided methods have been known to show application in drug repurposing. The variation in dosage for original target diseases and novel diseases presents a challenge for researchers of drug repurposing in present times. The present review critically discusses the drugs repurposed for cancer, covid-19, Alzheimer's, and other diseases, strategies, and challenges of drug repurposing. Moreover, regulatory perspectives related to different countries like the United States (US), Europe, and India have been delineated in the present review.

Adverse drug reactions and hospital admissions: Large case-control study of patients aged 65-100 years using linked English primary care and hospital data

BACKGROUND

Adverse drug reactions (ADRs) are common and a leading cause of injury. However, information on ADR risks of individual medicines is often limited. The aim of this hypothesis-generating study was to assess the relative importance of ADR-related and emergency hospital admission for large group of medication classes.

METHODS

This study was a propensity-matched case-control study in English primary care. Data sources were Clinical Practice Research Databank and Aurum with longitudinal, anonymized, patient level electronic health records (EHRs) from English general practices linked to hospital records. Cases aged 65-100 with ADR-related or emergency hospital admission were matched to up to six controls by age, sex, morbidity and propensity scores for hospital admission risk. Medication groups with systemic administration as listed in the British National Formulary (used by prescribers for medication advice). Prescribing in the 84 days before the index date was assessed. Only medication groups with 50+ cases exposed were analysed. The outcomes of interest were ADR-related and emergency hospital admissions. Conditional logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CI).

RESULTS

The overall population included 121 546 cases with an ADR-related and 849 769 cases with emergency hospital admission. The percentage of hospitalizations with an ADR-related code for admission diagnosis was 1.83% and 6.58% with an ADR-related code at any time during hospitalization. A total of 137 medication groups was included in the main ADR analyses. Of these, 13 (9.5%) had statistically non-significant adjusted ORs, 58 (42.3%) statistically significant ORs between 1.0 and 1.5, 37 (27.0%) between 1.5-2.0, 18 (13.1%) between 2.0-3.0 and 11 (8.0%) 3.0 or higher. Several classes of antibiotics (including penicillins) were among medicines with largest ORs. Evaluating the 14 medications most often associated with ADRs, a strong association was found between the number of these medicines and the risk of ADR-related hospital admission (adjusted OR of 7.53 (95% CI 7.15-7.93) for those exposed to 6+ of these medicines).

CONCLUSIONS AND RELEVANCE

There is a need for a regular systematic assessment of the harm-benefit ratio of medicines, harvesting the information in large healthcare databases and combining it with causality assessment of individual case histories.

A real-world pharmacovigilance study of mepolizumab in the FDA adverse event reporting system (FAERS) database

Mepolizumab is primarily used in the treatment of asthma, eosinophilic granulomatosis with polyangiitis, eosinophilia syndrome, and chronic rhinitis with nasal polyps. The information about its adverse drug reactions is mainly derived from clinical trials, and there is a shortage of real-world studies with extensive sample sizes. In this study, the U.S. FDA's Adverse Event Reporting System (FAERS) database was analyzed to evaluate the side effects of mepolizumab. A total of 18,040 reports of mepolizumab-associated adverse events were identified from the FDA Adverse Event Reporting System database. Multiple disproportionality analysis algorithms were used to determine the significance of these AEs. The study identified 198 instances of mepolizumab-induced AEs, including some important AEs not mentioned in the product labeling. The time to onset of adverse reactions was also analyzed, with a median time of 109 days. Most AEs occurred within the first month of mepolizumab use, but some may still occur after 1 year of treatment. Gender-specific analysis showed different high-risk AEs for females (digestive and neurological side effects) and males (serious adverse effects leading to hospitalization and death). The findings mentioned provide valuable insights on optimizing the use of mepolizumab, enhancing its effectiveness, and minimizing potential side effects. This information will greatly contribute to the practical implementation of the drug in clinical settings.

Nurses as adverse drug reaction reporting advocates

Adverse drug reactions (ADRs) is a challenge in modern healthcare, particularly given the increasing complexity of drug therapy, an ageing population, rising multimorbidity, and a high patient turnover. The core activity of detecting potential ADRs over the last half century has been spontaneous reporting systems. A recent Norwegian regulation commits healthcare professionals other than physicians and dentists to report serious ADRs. In this discussion paper, we share our preliminary experience with a training programme using nurses as ADR advocates to stimulate ADR reporting among the clinical staff in a hospital department.

Thirteen years of experience with eslicarbazepine acetate in the United Kingdom and Republic of Ireland: A safety perspective

OBJECTIVE

Eslicarbazepine acetate (ESL) is a once-daily oral antiseizure medication. Its safety and tolerability from clinical trials have been mostly confirmed by real-world data. The main purpose of this report is to provide an overview of the safety profile of ESL in the United Kingdom (UK) and Republic of Ireland (ROI).

METHODS

Safety data were obtained from the UK and ROI post-marketing sources (October 2009-April 2022) by the marketing authorization holder. All individual reports were included in the Argus Safety™ database. All adverse events (AEs) were coded using MedDRA® version 24.1. Only valid cases (meeting the minimum pharmacovigilance reporting requirements) were included.

RESULTS

During 13 years of ESL marketing, with cumulative estimated exposure of 2 210 395 patients-years, 183 reports were received. A total of 402 AEs were reported for the 155 valid reports. The most common reported AEs (≥6% of total reported), per system organ class (SOC), were: nervous system disorders (23.4%), injury, poisoning, and procedural complications (18.9%), general disorders and administration site conditions (12.9%), psychiatric disorders (12.7%) and gastrointestinal disorders (6.7%). The most frequently reported (≥2% of total reported) AEs were: seizure (4.5%), hyponatremia (4.2%), dizziness (2.7%), rash, fatigue (2.5% each), and somnolence (2.0%). Twenty-six percent of events were classified as serious (including six fatal cases).

SIGNIFICANCE

The current analysis supports the known safety profile of ESL, as generally well-tolerated with most AEs being non-serious. The most common AEs were considered either expected according to the disease itself or to the reference safety information. ESL continues to be a relevant medication in the treatment of partial (focal-onset) epilepsy, as also confirmed by the 2022 NICE guidelines.

Comparative Analysis of Information Provided in German Adverse Drug Reaction Reports Sent by Physicians, Pharmacists and Consumers

INTRODUCTION

Adverse drug reactions (ADRs) can be reported by Health Care Professionals (HCPs; e.g., physicians, pharmacists) and non-Health Care Professionals (non-HCPs; e.g., consumers). Previous studies investigating differences between reports from HCPs and non-HCPs rarely considered the completeness of information provided. In addition, they mostly did not distinguish between physicians and pharmacists or were performed years ago. The aim of our study was to analyse and compare the completeness of information provided in reports from physicians, pharmacists and consumers from Germany in a more recent dataset.

MATERIALS AND METHODS

We analysed all spontaneous reports from Germany received between 2018 and 2021 in the ADR database EudraVigilance exclusively reported by physicians (n = 69,976), pharmacists (n = 42,396) or consumers (n = 121,144). Demographical parameters of the patients were analysed descriptively. Completeness of reports was evaluated applying an established score (vigiGrade). Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using logistic regression analysis in order to identify report, patient, drug or ADR-specific information provided more often in reports from physicians, pharmacists or consumers.

RESULTS

Within the study period the number of reports per year by physicians and pharmacists decreased steadily, while an opposite trend was observed for consumer reports. The proportion of female patients was higher in reports from pharmacists (64.4%) and consumers (64.8%) compared to those from physicians (55.3%). On average, patients in reports from pharmacists (58.7) were older compared to those from physicians (53.5) and consumers (52.6). As an example for the presence of specific information, the time to onset of the ADR could be calculated more often in consumer compared to physician (OR 1.9 [1.8-1.9]) and pharmacist reports (OR 1.7 [1.6-1.7]). In contrast, pharmacist (OR 0.5 [0.4-0.5]) and consumer (OR 0.5 [0.5-0.5]) reports included the indication of the suspected drug less often than physician reports. Physician reports on average (mean = 0.5) were slightly more complete according to the vigiGrade score compared to reports from consumers (mean = 0.4) and pharmacists (mean = 0.4).

CONCLUSION

The ADR reports from consumers were comparable with regard to the completeness score with those from physicians and pharmacists underlining their value. Differences in completeness of specific information between the reporter types were found, suggesting that a common reporting of interactions between the three reporters may further improve the completeness of ADR reports. Furthermore, stratified analysis of ADR reports per reporter type may be helpful for certain objectives in scientific research.

Sharing Adverse Drug Event Reports Between Hospitals and Community Pharmacists to Inform Re-dispensing: An Analysis of Reports and Process Outcomes

INTRODUCTION

Adverse drug events (ADEs) are a leading cause of unplanned hospital visits. We designed ActionADE, an online ADE reporting platform, and integrated it with PharmaNet, British Columbia's (BC's) provincial medication dispensing system, to overcome identified barriers in ADE reporting and communicate ADEs to community pharmacies. Our objectives were to characterise ADEs reported in ActionADE, explore associations between patients' age, sex and ADE characteristics, and estimate the re-dispensation rate of culprit medications in community pharmacies.

METHODS

We conducted a prospective observational study of ADE reporting in four BC hospitals between April 1, 2020 and October 31, 2022. We described the characteristics of ADEs reported into ActionADE, used logistic regression modelling to examine associations between age and sex and ADE characteristics, and calculated rates of avoided culprit drug re-dispensations using community pharmacists' responses to ActionADE alerts.

RESULTS

In total, 3591 ADE reports were initiated by hospital clinicians, 3174 of which were included in this analysis. Serious or life-threatening ADEs resulting in permanent disability, hospitalisation, extended hospitalisation, and/or death accounted for 28.5% (906/3174; 95% CI 27.0-30.1%) of reports. Males were more likely to have non-adherence reported compared to females and experienced life threatening ADEs at a younger age than females. Of 592 patients who had ≥ 1 adverse drug reaction or allergy report (a subset of ADEs) transmitted to community pharmacies, 200 subsequently attempted to re-fill the culprit or a same class drug. Community pharmacists responded to preventative alerts by avoiding re-dispensation in 33.0% (66/200; 95% CI 26.5-39.5%).

INTERPRETATION

ActionADE is the first interoperable system that communicates ADEs via a central medication database to community pharmacies. Every 10th ADE reported in ActionADE and shared to PharmaNet resulted in community pharmacists' avoiding one culprit or same class drug re-exposure. Further research is needed to understand ActionADE's impact on patient and health system outcomes.

Global Postmarket Pharmacovigilance: A Generic Drug Perspective

Despite the recognized need for generic drug pharmacovigilance harmonization efforts, only a few studies compared generic drug postmarket safety and surveillance methods adopted by regulatory agencies in different countries. The purpose of this research is to collect available information from a sample of international regulators with the overall goal of providing a general overview of each agency's decision-making processes for postmarket generic drug safety and surveillance. A structured four-part questionnaire of open-ended and multiple-choice questions along with a semi-structured interview were designed to elicit detailed information. Swissmedic, Medicines and Healthcare products Regulatory Agency (MHRA), Health Canada, and the U.S. Food and Drug Administration (FDA) provided information. Detailed information from participating regulatory agencies demonstrated some similarities and differences in their postmarket generic drug pharmacovigilance approaches. This study examines each agency's scientific perspective to address generic drug safety issues, as well as to identify common barriers within decision-making processes, such as legislative restrictions and limited resources. Most agencies do not have specific processes that are unique to generic drug products. This exploratory study, through documenting common and unique approaches intends to create a greater awareness and to promote cross-collaboration between global regulatory agencies.

Drug-induced hypoglycemia: a disproportionality analysis of the FAERS database

BACKGROUND

Hypoglycemia is an adverse event (AE) that cannot be ignored in clinical practice. This study aimed to identify the most common and top drugs associated with the risk of hypoglycemia based on the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database.

RESEARCH DESIGN AND METHODS

We used OpenVigil 2.1 pharmacovigilance analytics platform to query FAERS database and data from 2004 to 2023 were retrieved. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify hypoglycemia cases, and DrugBank database was used to determine drug generic names.

RESULTS

A total of 11,155,106 AEs reports were identified, of which 28,443 (0.25%) were related to hypoglycemia. Metformin (6926 cases) was associated with most cases of hypoglycemia. According to the disproportionality analysis, the top five drugs with the highest ROR and PRR were penamecillin, nikethamide, sotagliflozin, norethandrolone, glimepiride/pioglitazone. Nineteen of the top 50 drugs did not have hypoglycemia indicated in the package insert.

CONCLUSIONS

By analyzing the FAERS database, we listed drugs with a strong hypoglycemic signal for which the label does not provide a reminder. Notably, the potential hypoglycemia risks are of great importance and should be closely monitored in medical practice.

Comprehensive Study of Drug-Induced Pruritus Based on Adverse Drug Reaction Report Database

Drug-induced pruritus triggers a desire to scratch, thereby diminishing one's quality of life. Certain instances of this phenomenon follow complex mechanisms of action that diverge from histamine-mediated pathways, known contributors to pruritus. However, investigations into the relationship between drugs and pruritus are limited. In this study, data mining techniques were employed to comprehensively analyze the characteristics of drugs linked to pruritus, using the FDA's Adverse Event Reporting System (FAERS) data. Reports linked to pruritus demonstrated noteworthy differences in gender, age, and weight when compared with non-pruritus cases. Among the leading candidates for drugs prompting pruritus were ophthalmic drugs, systemic antibacterials, contrast media, dermatological antifungals, and dermatological preparations. A principal component analysis showed that the second principal component served as an indicator for distinguishing between onsets at mucous membranes or the skin's surface. Additionally, the third principal component functioned as an indicator for categorizing administration methods as either invasive or noninvasive. Furthermore, a hierarchical cluster analysis conducted on these obtained principal components revealed the potential for classifying drugs based on the site of pruritus onset and the method of drug administration. These findings contribute to the development of targeted prevention and treatment strategies for avoiding pruritus in clinical practice.

Finding Needles in the Haystack: Clinical Utility Score for Prioritisation (CUSP), an Automated Approach for Identifying Spontaneous Reports with the Highest Clinical Utility

INTRODUCTION

Spontaneous reporting of adverse events has increased steadily over the past decades, and although this trend has contributed to improving post-marketing surveillance pharmacovigilance activities, the consequent amount of data generated is challenging to manually review during assessment, with each individual report requiring review by pharmacovigilance experts. This highlights a clear need for alternative or complementary methodologies to help prioritise review.

OBJECTIVE

Here, we aimed to develop and test an automated methodology, the Clinical Utility Score for Prioritisation (CUSP), to assist pharmacovigilance experts in prioritising clinical assessment of safety data to improve the rapidity of case series review when case volumes are large.

METHODS

The CUSP method was tested on a reference dataset of individual case safety reports (ICSRs) associated to five drug-event pairs that led to labelling changes. The selected drug-event pairs were of varying characteristics across the portfolio of GSK's products.

RESULTS

The mean CUSP score for 'key cases' and 'cases of low utility' was 19.7 (median: 21; range: 7-27) and 17.3 (median: 19; range: 4-27), respectively. CUSP distribution for 'key cases' were skewed toward the higher range of scores compared with 'all cases'. The overall performance across each individual drug-event pair varied considerably, showing higher predictive power for 'key cases' for three of the drug-event pairs (average CUSP between these three: 22.8; range: 22.5-23.0) and lesser power for the remaining two (average CUSP between these two: 17.6; range: 14.5-20.7).

CONCLUSION

Although several tools have been developed to assess ICSR completeness and regulatory utility, this is the first attempt to successfully develop an automated clinical utility scoring system that can support the prioritisation of ICSRs for clinical review.

Profiles and Outcomes of Skin Injuries Caused by Injectable Drug Extravasation: An Analysis of the Japanese Adverse Drug Event Report Database

Extravasation occurs when injectable drugs leak out of the blood vessels, damaging the surrounding tissues and causing a variety of skin injuries. This study aimed to comprehensively analyze extravasation risk, skin injury profiles, and outcomes for suspect drugs from the Japanese Adverse Drug Event Report (JADER) database. Adverse events were defined according to the Medical Dictionary for Regulatory Activities/Japanese version; the term extravasation (Standardized MedDRA Query Code: 20000136) was used in this analysis. The names of adverse events were entered as unified preferred terms and redefined to evaluate skin injury profiles. In addition, skin injury outcomes were divided into 2 broad categories: "improvement" and "no improvement." Reporting odds ratios were used to detect signals for adverse events. A total of 656 cases of extravasation-related adverse events were reported between April 2004 and January 2022. Signals for extravasation-related adverse events were detected from 11 drugs. Then, their respective skin injury profiles and outcomes were determined. These results suggest a relationship between adverse events associated with extravasation and 11 drugs and identify the characteristics of each skin injury and their outcomes. These findings will contribute to improving the quality of infusion management in clinical practice.

Adverse Events Following the BNT162b2 mRNA COVID-19 Vaccine (Pfizer-BioNTech) in Aotearoa New Zealand

INTRODUCTION

In February 2021, New Zealand began its largest ever immunisation programme with the BNT162b2 mRNA coronavirus disease 2019 (COVID-19) vaccine.

OBJECTIVE

We aimed to understand the association between 12 adverse events of special interest (AESIs) and a primary dose of BNT162b2 in the New Zealand population aged ≥5 years from 19 February 2021 through 10 February 2022.

METHODS

Using national electronic health records, the observed rates of AESIs within a risk period (1-21 days) following vaccination were compared with the expected rates based on background data (2014-2019). Standardised incidence ratios (SIRs) were estimated for each AESI with 95% confidence intervals (CIs) using age group-specific background rates. The risk difference was calculated to estimate the excess or reduced number of events per 100,000 persons vaccinated in the risk period.

RESULTS

As of 10 February 2022, 4,277,163 first doses and 4,114,364 second doses of BNT162b2 had been administered to the eligible New Zealand population aged ≥5 years. The SIRs for 11 of the 12 selected AESIs were not statistically significantly increased post vaccination. The SIR (95% CI) for myo/pericarditis following the first dose was 2.3 (1.8-2.7), with a risk difference (95% CI) of 1.3 (0.9-1.8), per 100,000 persons vaccinated, and 4.0 (3.4-4.6), with a risk difference of 3.1 (2.5-3.7), per 100,000 persons vaccinated following the second dose. The highest SIR was 25.6 (15.5-37.5) in the 5-19 years age group, following the second dose of the vaccine, with an estimated five additional myo/pericarditis cases per 100,000 persons vaccinated. A statistically significant increased SIR of single organ cutaneous vasculitis (SOCV) was also observed following the first dose of BNT162b2 in the 20-39 years age group only.

CONCLUSIONS

A statistically significant association between BNT162b2 vaccination and myo/pericarditis was observed. This association has been confirmed internationally. BNT162b2 was not found to be associated with the other AESIs investigated, except for SOCV following the first dose of BNT162b2 in the 20-39 years age group only, providing reassurances around the safety of the vaccine.

The Adverse Effects and Nonmedical Use of Methylphenidate Before and After the Outbreak of COVID-19: Machine Learning Analysis

BACKGROUND

Methylphenidate is an effective first-line treatment for attention-deficit/hyperactivity disorder (ADHD). However, many adverse effects of methylphenidate have been recorded from randomized clinical trials and patient-reported outcomes, but it is difficult to determine abuse from them. In the context of COVID-19, it is important to determine how drug use evaluation, as well as misuse of drugs, have been affected by the pandemic. As people share their reasons for using medication, patient sentiments, and the effects of medicine on social networking services (SNSs), the application of machine learning and SNS data can be a method to overcome the limitations. Proper machine learning models could be evaluated to validate the effects of the COVID-19 pandemic on drug use.

OBJECTIVE

To analyze the effect of the COVID-19 pandemic on the use of methylphenidate, this study analyzed the adverse effects and nonmedical use of methylphenidate and evaluated the change in frequency of nonmedical use based on SNS data before and after the outbreak of COVID-19. Moreover, the performance of 4 machine learning models for classifying methylphenidate use based on SNS data was compared.

METHODS

In this cross-sectional study, SNS data on methylphenidate from Twitter, Facebook, and Instagram from January 2019 to December 2020 were collected. The frequency of adverse effects, nonmedical use, and drug use before and after the COVID-19 pandemic were compared and analyzed. Interrupted time series analysis about the frequency and trends of nonmedical use of methylphenidate was conducted for 24 months from January 2019 to December 2020. Using the labeled training data set and features, the following 4 machine learning models were built using the data, and their performance was evaluated using F-1 scores: naïve Bayes classifier, random forest, support vector machine, and long short-term memory.

RESULTS

This study collected 146,352 data points and detected that 4.3% (6340/146,352) were firsthand experience data. Psychiatric problems (521/1683, 31%) had the highest frequency among the adverse effects. The highest frequency of nonmedical use was for studies or work (741/2016, 36.8%). While the frequency of nonmedical use before and after the outbreak of COVID-19 has been similar (odds ratio [OR] 1.02 95% CI 0.91-1.15), its trend has changed significantly due to the pandemic (95% CI 2.36-22.20). Among the machine learning models, RF had the highest performance of 0.75.

CONCLUSIONS

The trend of nonmedical use of methylphenidate has changed significantly due to the COVID-19 pandemic. Among the machine learning models using SNS data to analyze the adverse effects and nonmedical use of methylphenidate, the random forest model had the highest performance.

Automatic Extraction of Comprehensive Drug Safety Information from Adverse Drug Event Narratives in the Korea Adverse Event Reporting System Using Natural Language Processing Techniques

INTRODUCTION

Concerns have been raised over the quality of drug safety information, particularly data completeness, collected through spontaneous reporting systems (SRS), although regulatory agencies routinely use SRS data to guide their pharmacovigilance programs. We expected that collecting additional drug safety information from adverse event (ADE) narratives and incorporating it into the SRS database would improve data completeness.

OBJECTIVE

The aims of this study were to define the extraction of comprehensive drug safety information from ADE narratives reported through the Korea Adverse Event Reporting System (KAERS) as natural language processing (NLP) tasks and to provide baseline models for the defined tasks.

METHODS

This study used ADE narratives and structured drug safety information from individual case safety reports (ICSRs) reported through KAERS between 1 January 2015 and 31 December 2019. We developed the annotation guideline for the extraction of comprehensive drug safety information from ADE narratives based on the International Conference on Harmonisation (ICH) E2B(R3) guideline and manually annotated 3723 ADE narratives. Then, we developed a domain-specific Korean Bidirectional Encoder Representations from Transformers (KAERS-BERT) model using 1.2 million ADE narratives in KAERS and provided baseline models for the task we defined. In addition, we performed an ablation experiment to investigate whether named entity recognition (NER) models were improved when a training dataset contained more diverse ADE narratives.

RESULTS

We defined 21 types of word entities, six types of entity labels, and 49 types of relations to formulate the extraction of comprehensive drug safety information as NLP tasks. We obtained a total of 86,750 entities, 81,828 entity labels, and 45,107 relations from manually annotated ADE narratives. The KAERS-BERT model achieved F1-scores of 83.81 and 76.62% on the NER and sentence extraction tasks, respectively, while outperforming other baseline models on all the NLP tasks we defined except the sentence extraction task. Finally, utilizing the NER model for extracting drug safety information from ADE narratives resulted in an average increase of 3.24% in data completeness for KAERS structured data fields.

CONCLUSIONS

We formulated the extraction of comprehensive drug safety information from ADE narratives as NLP tasks and developed the annotated corpus and strong baseline models for the tasks. The annotated corpus and models for extracting comprehensive drug safety information can improve the data quality of an SRS database.

Comparative Safety Profiles of Oncology Biosimilars vs. Originators in Europe: An Analysis of the EudraVigilance Database

In the last decades, the clinical management of oncology patients has been transformed by the introduction of biologics. The high costs associated with the development and production of biologics limit patient access to these therapies. The expiration of exclusive patents for biologics has led to the development and market introduction of biosimilars, offering the reduction of costs for cancer treatments. Biosimilars are highly similar to the reference products in terms of structure, biological activity, efficacy, safety, and immunogenicity. Therefore, the monitoring of biosimilars' safety in real-world clinical practice though pharmacovigilance is essential. This study aimed to analyze the post-marketing pharmacovigilance data of biosimilar monoclonal antibodies used in oncology and compare them with respective reference products. Data of a 2-year period (1 January 2021-31 December 2022) were retrieved from EudraVigilance, and descriptive and comparative analysis were performed using the Reporting Odds Ratio to evaluate the distribution of medicine-reaction pairs related to biosimilars of three antitumor biological products and their corresponding reference products: bevacizumab, rituximab, and trastuzumab. The results showed that most frequently reported ADRs for biosimilars were non-serious and consistent with the safety profiles of reference products. These findings provide reassurance regarding safety equivalence of biosimilars and support their use as valid alternatives to originator biologics.

Safety Profile of Vitamin D in Italy: An Analysis of Spontaneous Reports of Adverse Reactions Related to Drugs and Food Supplements

Vitamin D (VitD) is largely used in Italy, often inappropriately; thus, an evaluation of its safety is a crucial issue. This study analyses the adverse reactions (ARs) associated with the use of products containing VitD (VitDps) reported to the Italian National Pharmacovigilance and Phytovigilance networks. From March 2002 to August 2022, a total of 643 and 127 reports concerning 903 and 215 ARs were retrieved from Pharmacovigilance and Phytovigilance networks, respectively. Overall, 332 (29.6%) ARs were classified as serious, and the most described ones were hypercalcaemia, renal failure and tachycardia. Serious AR risk was significantly higher for subjects using more than four concomitant products (OR 2.44 [95% CI 1.30-4.60]) and VitD doses higher than 1000 IU/day (OR 2.70 [95% CI 1.30-5.64]). In Italy, there was a modest decrease in AR reporting, despite the slightly increased use of VitD during the COVID-19 pandemic. To the best of our knowledge, this is the first study describing all VitDps-related ARs observed in the Italian general population. Since underreporting is the main limitation of the safety reporting systems, the necessity to continue ARs monitoring, also using real-world data on VitDps prescription, use and outcome patterns is highlighted.

Causal Evaluation of Post-Marketing Drugs for Drug-induced Liver Injury from Electronic Health Records

Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactions that can lead to acute liver failure and death. Detection of DILI and causal estimation of drug-hepatotoxicity association are of great importance for patient safety. This paper proposes a framework for causal estimation of post-marketing drugs for DILI from real-world electronic health record (EHR) data. Randomized clinical trials were replicated at scale by automatically generating different user and non-user cohorts for each potential drug, and average treatment effects (ATEs) of drugs were estimated using targeted maximum likelihood estimation. Ten years of real-world EHRs were used to validate the framework. Of all 1199 single-ingredient drugs analyzed, 7 novel and 7 known drug-hepatotoxicity associations were found to be causal.

Patterns of adverse drug reactions in Jordan: a retrospective analysis of the National Pharmacovigilance Data Registry (2015-2021)

BACKGROUND

Post-marketing surveillance of drugs is a cornerstone of pharmacovigilance. This study was conducted to characterize patterns of adverse drug reactions (ADRs) reported in Jordan.

RESEARCH DESIGN AND METHODS

ADR reports submitted to the pharmacovigilance database of the Jordan Food and Drug Administration during 2015-2021 were retrospectively analyzed. The most commonly reported drugs, drug classes, ADRs, and ADRs consequences were explored. Logistic regression identified possible predictors of reporting serious ADRs.

RESULTS

A total of 2744 ADR reports were included, among which 28.4% were classified as serious. An annual increase in ADR reporting was observed. The most commonly implicated drug classes were antineoplastic and immunomodulating agents (24.0%), anti-infectives for systemic use (14.2%), and alimentary tract and metabolism (12.1%). Covid-19 vaccination was the most reported drug (22.8%). Fatigue (6.3%), injection site pain (6.1%), and headache (6.0%) were the top three common ADRs. Among ADRs with outcome information, 4.7% were fatal. Patient's age and intravenous medication use largely predicted reporting serious ADRs.

CONCLUSIONS

This study provides contemporary insights into the post-marketing surveillance of drugs in Jordan. The findings are foundational for future studies exploring drug-ADRs causality relationships. Efforts that promote pharmacovigilance concepts should be sustained and enhanced at the national level.

Characteristics of Phase IV Clinical Trials in Oncology: An Analysis Using the ClinicalTrials.gov Registry Data

The present study analyzed the characteristics of phase IV clinical trials in oncology using data from the ClinicalTrials.gov registry. The included trials were conducted between January 2013 and December 2022 and were examined for key characteristics, including outcome measures, interventions, sample sizes, and study design, different cancer types, and geographic regions. The analysis included 368 phase IV oncology studies. An amount of 50% of these studies examined both safety and efficacy, while 43.5% only reported efficacy outcome measures, and 6.5% only described safety outcome measures. Only 16.9% of studies were powered to detect adverse events with a frequency of 1 in 100. Targeted therapies accounted for the majority of included studies (53.5%), with breast (32.91%) and hematological cancers (25.82%) being the most frequently investigated malignancies. Most phase IV oncology studies lacked sufficient power to detect rare adverse events due to their small sample sizes and instead focused on effectiveness. To ensure that there is no gap in drug safety data collection and detection of rare adverse events due to limited phase IV clinical trials, there is a significant need for additional education and participation by both health care providers and patients in spontaneous reporting processes.

Adverse drug reactions and their fatal outcomes in clozapine patients in VigiBase: Comparing the top four reporting countries (US, UK, Canada and Australia)

BACKGROUND

Pharmacovigilance findings and box warnings in the clozapine package inserts have marked the history of clozapine.

OBJECTIVE

This is the largest review of clozapine adverse drug reactions (ADRs) and their associated fatal outcomes. Reports to the World Health Organization's global pharmacovigilance database, VigiBase™, were analyzed, extending from clozapine's introduction to December 31, 2022.

METHODS

The analysis focused on the top four reporting countries: United States (US), United Kingdom (UK), Canada and Australia (83 % of fatal outcomes worldwide). Attempts were made to control for population and clozapine prescription in each country.

RESULTS

Clozapine ADRs worldwide accounted for 191,557 reports, with the highest number (53,505) in "blood and lymphatic system disorder". Of the 22,596 fatal outcomes reported in clozapine patients, 9587 were from the US, 6567 from the UK, 3623 from Canada and 1484 from Australia. The top category worldwide in fatal outcomes was nonspecifically labeled "death" with 46 % (range 22-62 %). "Pneumonia" was second with 30 % (range 17-45 %). Agranulocytosis was numerically only the 35th top clozapine ADR associated with fatal outcomes. On average, 2.3 clozapine ADRs were reported per fatal outcome. Infections were associated with 24.2 % of the UK fatal outcomes (9.4 %-11.9 % in the 3 other countries).

CONCLUSIONS

The four countries appeared to report clozapine ADRs in different ways, making comparisons difficult. We estimated higher fatal outcomes in the UK and Canada after controlling for cross-sectional estimations of population and published clozapine use. This last hypothesis is limited by the lack of precise estimation of accumulated clozapine use in each country.

Spontaneously reported adverse events following COVID-19 basic and booster immunizations in the Netherlands

INTRODUCTION

The rapid roll-out of novel COVID-19 vaccines made near real-time post-marketing safety surveillance essential to identify rare and long-term adverse events following immunization (AEFIs). In light of the ongoing booster vaccination campaigns, it is key to monitor changes in observed safety patterns post-vaccination. The effect of sequential COVID-19 vaccinations, as well as heterologous vaccination sequences, on the observed post-vaccination safety pattern, remains largely unknown.

METHODS

The primary objective of this study was to describe the profile of spontaneously reported AEFIs following COVID-19 vaccination in the Netherlands, including the primary and booster series. Reports from consumers and healthcare professionals were collected via a COVID-19 vaccine-tailored online reporting form by the National Pharmacovigilance Centre Lareb (Lareb) between 6 January 2021 and 31 August 2022. The data were used to describe the most frequently reported AEFIs per vaccination moment, the consumer experienced burden per AEFI, and differences in AEFIs reported for homologous and heterologous vaccination sequences.

RESULTS

Lareb received 227,884 spontaneous reports over a period of twenty months. Overall, a high degree of similarity in local and systemic AEFIs per vaccination moment was observed, with no apparent change in the number of reports of serious adverse events after multiple COVID-19 vaccinations. No differences in the pattern of reported AEFIs per vaccination sequence was observed.

CONCLUSION

Spontaneous reported AEFIs demonstrated a similar reporting pattern for homologous and heterologous primary and booster series of COVID-19 vaccination in the Netherlands.

Calcium, magnesium, potassium, and sodium oxybates oral solution for cataplexy or excessive daytime sleepiness associated with narcolepsy

INTRODUCTION

Lower-sodium oxybate (LXB) is a novel formulation that is approved by the US Food and Drug Administration (FDA) to treat cataplexy and excessive daytime sleepiness (EDS) in adult patients and children ≥ 7 years with narcolepsy. LXB contains 92 percent less sodium than sodium oxybate (SXB), which adds 550-1640 mg of sodium/day at usual doses of 3-9 grams per day. The FDA has declared LXB to be clinically superior to SXB due to greater safety by reducing the chronic sodium load. Narcolepsy patients have high comorbidities for hypertension and cardiovascular disease, conditions which can be adversely affected by high sodium intake.

AREAS COVERED

This drug review discusses narcolepsy, current and upcoming pharmacotherapy, and LXB chemistry, pharmacodynamics, pharmacokinetics, and metabolism. Published results from LXB's phase 1 studies, a phase 3 study, and 2 post-marketing studies are reviewed. Databases searched included Pubmed, Google Scholar, Lexi-Comp, Scopus, Science, and Ovid.

EXPERT OPINION

LXB is efficacious in treating daytime sleepiness and cataplexy in adults and children ≥ 7 years with narcolepsy. Using LXB instead of SXB formulations may benefit narcolepsy patients with cardiovascular comorbidities and hypertension, but long-term studies are needed to prove it.

Risk management of medication errors: a novel conceptual framework

BACKGROUND

Medication error is a common cause of patient harm. The study aims to propose a way to manage the risk of medication errors in a novel way, by identifying practice areas where mitigating patient harm should be prioritized using a risk management approach.

METHODS

Suspected Adverse Drug Reactions (sADRs) in Eudravigilance database over three years were reviewed to identify preventable medication errors. These were classified using a new method based upon the root cause underlying pharmacotherapeutic failure. The correlation between severity of harm and type of medication error, and other clinical parameters was investigated.

RESULTS

Overall, 2294 medication errors were identified from Eudravigilance, of which 1300 (57%) were due to pharmacotherapeutic failure. Most cases of preventable medication error involved prescribing (41%) and administration (39%). The variables which significantly predicted severity of medication errors were pharmacological group, patient age, number of drugs prescribed, and route of administration. The drug classes most strongly associated with harm included cardiac drugs, opioids, hypoglycaemics, antipsychotics, sedatives, and antithrombotic agents.

CONCLUSION

The findings of this study highlight the feasibility of using a novel conceptual framework to identify areas of practice at risk of pharmacotherapeutic failure where Interventions by healthcare professionals in these areas are most likely to improve medication safety.

Trends in Adverse Drug Reactions Among Children: Evidence from Jiangsu Province of China, 2010-2019

BACKGROUND

Medication safety among children represents an underrecognized public health concern worldwide, yet little evidence was found in China. This study aimed to examine trends in rates of pediatric adverse drug reaction (ADR) reports in Jiangsu Province of China with a catchment population of more than 11 million children.

METHODS

Data for children aged under 15 years were extracted from the spontaneous reporting system of ADR surveillance in Jiangsu Province. Suspected therapeutic agents for ADRs were coded using the Anatomical Therapeutic Chemical classification system. We used the Chinese modification of the International Classification of Diseases, Tenth Revision, to group primary diseases, and the Medical Dictionary for Regulatory Activities to classify the manifestation of ADRs. We used Joinpoint to estimate age-adjusted ADR rates stratified by sex from July 2010 to June 2019, and further by specific features, including patient characteristics, main suspected therapeutic medications, primary diseases, and ADRs. We used the percentage change annualized estimator to evaluate trends over time.

RESULTS

A total of 79,903 ADR reports were identified among children aged under 15 years, which accounted for 11.4% of all ADRs reported in Jiangsu Province during the same period. The age-adjusted ADR report rates increased significantly from 66.20 to 96.76 per 100,000 children during the period July 2010-June 2019, with an annual increase of 4.9% (95% confidence interval 1.3-8.5%; p value 0.014). Of all ADR reports, there were 47,774 (59.8%) boys and 32,129 (40.2%) girls. Children aged 0-4 years accounted for more than half of the ADR reports (n = 47,680, 59.7%). Skin and subcutaneous tissue disorders were the most frequently reported ADRs (45,773, 57.3%). Respiratory diseases were the most commonly observed medical conditions in relation to pediatric ADRs, accounting for 68.8% (n = 54,940) of all ADR reports, and anti-infectives for systemic use consistently represented over time the most common medication group, contributing to 69.8% of all reports. A reduction in ADR report rates was observed for vaccines, with an annual decrease of 19% in children.

CONCLUSIONS

ADRs remain a public health challenge among the vulnerable pediatric populations. Findings from the present study call for continuing efforts in ADR prevention and medication safety improvement in children.

Drug Safety Monitoring in Health Programs of Cameroon

BACKGROUND

Data are needed to serve as evidence in planning the strengthening of pharmacovigilance in health programs administering drugs to populations. The present study was proposed to map the distribution of pharmacovigilance units in health programs, assess the availability of key resources, the implementation of key pharmacovigilance activities and identify needs of involved actors.

METHODS

It was a cross sectional descriptive study targeting all health programs of the Cameroon Ministry of Public Health administering drugs/vaccines to the population. Data were collected using semi structured questionnaire administered face to face to key persons in charge of drug safety monitoring or drug management in health programs.

RESULTS

Out of the 09 health programs involved in drug distribution, 07 consented to participate. Five out of them (71.4%) claimed to have existing pharmacovigilance units. Office space, computers, operating budget, data analysis software and a trained staff were available in 28.6%, 42.9%, 42.9%, 14.3%, 00.0%, and 42.9% of the health programs respectively. One of the 7 health programs (14.3%) declared conducting detection/notification of adverse events following exposure drugs, 2 (28.6%) conduct causality assessment and 3 (42.8%) conduct analysis of pharmacovigilance data. All health programs proposed to prioritize the allocation of budget and qualified personnel and the training of existing personnel as key interventions to improve drugs/vaccines safety monitoring in health programs.

CONCLUSION

The study reports limited coverage of Cameroon health programs with activities leading to drugs and vaccine safety monitoring. Suggested actions have to be taken into account when attempting to improve the situation.

A Narrative Review of Adverse Event Detection, Monitoring, and Prevention in Indian Hospitals

An adverse event is any abnormal clinical finding associated with the use of a therapy. Adverse events are classified by reporting an event's seriousness, expectedness, and relatedness. Monitoring patient safety is of utmost importance as more and more data becomes available. In reality, very low numbers of adverse events are reported via the official path. Chart review, voluntary reporting, computerized surveillance, and direct observation can detect adverse drug events. Medication errors are commonly seen in hospitals and need provider and system-based interventions to prevent them. The need of the hour in India is to develop and implement medication safety best practices to avoid adverse events. The utility of artificial intelligence techniques in adverse event detection remains unexplored, and their accuracy and precision need to be studied in a controlled setting. There is a need to develop predictive models to assess the likelihood of adverse reactions while testing novel pharmaceutical drugs.

Rituximab and Pyoderma Gangrenosum: An Investigation of Disproportionality Using a Systems Biology-Informed Approach in the FAERS Database

BACKGROUND

Studies have found an increased risk of pyoderma gangrenosum associated with rituximab. The structural properties and pharmacological action of rituximab may affect the risk of pyoderma gangrenosum. Additionally, pyoderma gangrenosum is associated with autoimmune disorders for which rituximab is indicated.

OBJECTIVE

We aimed to determine whether rituximab is disproportionally associated with pyoderma gangrenosum using a systems biology-informed approach.

METHODS

Adverse event reports were extracted from the US Food and Drug Administration Adverse Event Reporting System (FAERS, 2013-20). The Bayesian Confidence Propagation Neural Network Information Component was used to test for disproportionality. Comparators used to determine potential causal pathways included all other medicines, all medicines with a similar structure (monoclonal antibodies), all medicines with the same pharmacological target (CD20 antagonists) and all medicines used for the same indication(s) as rituximab.

RESULTS

Thirty-two pyoderma gangrenosum cases were identified, 62.5% were female, with a median age of 48 years. There was an increased association of pyoderma gangrenosum with rituximab compared with all other medicines (exponentiated Information Component 6.75, 95% confidence interval (CI) 4.66-9.23). No association was observed when the comparator was either monoclonal antibodies or CD20 antagonists. Conditions for which an association of pyoderma gangrenosum with rituximab was observed were multiple sclerosis (6.68, 95% CI 1.63-15.15), rheumatoid arthritis (2.67, 95% CI 1.14-4.80) and non-Hodgkin's lymphoma (2.94, 95% CI 1.80-3.73).

CONCLUSIONS

Pyoderma gangrenosum was reported more frequently with rituximab compared with all other medicines. The varying results when restricting medicines for the same condition suggest the potential for confounding by indication. Post-market surveillance of biologic medicines in  FAERS should consider a multi-faceted approach, particularly when the outcome of interest is associated with the underlying immune condition being treated by the medicine of interest.

Screening the European pharmacovigilance database for reports of clozapine-related DRESS syndrome: 47 novel cases

Clozapine-related drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare adverse reaction. We aimed to screen a large pharmacovigilance database to identify clozapine-related DRESS cases, even if otherwise reported and provide a clinical overview. We screened spontaneous reports of clozapine-related DRESS syndrome in EudraVigilance database applying the European Registry on Severe Cutaneous Adverse Drug Reactions (RegiSCAR) criteria and scores to identify probable/definite DRESS syndrome cases. Clinical and demographic characteristics of included cases were provided and associations between RegiSCAR scores, and time to develop/recover DRESS were assessed. In a total of 262,146 adverse drug reactions reports for 75,190 clozapine-treated patients, 596 cases fulfilled RegiSCAR criteria; ultimately, 51 cases were rated as probable/definite DRESS according to RegiSCAR scores, of which 4 were previously published as case reports. The mean age of patients was 41.06 years (43.1% females), with 13 patients (25.5%) receiving reported co-medication with other DRESS culprit drugs. Median time between clozapine initiation and DRESS symptoms was 25 days. Clozapine dose was associated with days to develop symptoms (Spearman's ρ 0.40, p = 0.03). Organ involvement was reported in all cases followed by fever (n = 49; 96.1%) and eosinophilia (n = 47; 92.2%). Treatment involved clozapine discontinuation for 37 patients (72.5%), while 3.9% (n = 2) of cases ended fatally. Clozapine rechallenge was undertaken in 25 patients (49.0%). The screening of the EudraVigilance database revealed 47 novel clozapine-related DRESS cases, and only one was originally reported as DRESS. Clozapine-related DRESS may occur with clozapine monotherapy not only during dose titration, but also during maintenance treatment.

Analyzing adverse drug reaction using statistical and machine learning methods: A systematic review

BACKGROUND

Adverse drug reactions (ADRs) are unintended negative drug-induced responses. Determining the association between drugs and ADRs is crucial, and several methods have been proposed to demonstrate this association. This systematic review aimed to examine the analytical tools by considering original articles that utilized statistical and machine learning methods for detecting ADRs.

METHODS

A systematic literature review was conducted based on articles published between 2015 and 2020. The keywords used were statistical, machine learning, and deep learning methods for detecting ADR signals. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) guidelines.

RESULTS

We reviewed 72 articles, of which 51 and 21 addressed statistical and machine learning methods, respectively. Electronic medical record (EMR) data were exclusively analyzed using the regression method. For FDA Adverse Event Reporting System (FAERS) data, components of the disproportionality method were preferable. DrugBank was the most used database for machine learning. Other methods accounted for the highest and supervised methods accounted for the second highest.

CONCLUSIONS

Using the 72 main articles, this review provides guidelines on which databases are frequently utilized and which analysis methods can be connected. For statistical analysis, >90% of the cases were analyzed by disproportionate or regression analysis with each spontaneous reporting system (SRS) data or electronic medical record (EMR) data; for machine learning research, however, there was a strong tendency to analyze various data combinations. Only half of the DrugBank database was occupied, and the k-nearest neighbor method accounted for the greatest proportion.

Comparative Safety Signal Assessment of Hospitalization Associated With the Use of Atypical Antipsychotics

Background

Persons with symptoms of psychosis receiving treatment with atypical antipsychotics (AAPs) can experience serious adverse events (AEs) requiring admission to the hospital. The comparative likelihood of AE-related hospitalization following the use of all AAPs has not been fully characterized. Therefore, we evaluated the safety signals of hospitalizations associated with the use of AAPs.

Methods

We conducted a cross-sectional analysis using the FDA Adverse Event Reporting System (FAERS) database (from January 1, 2004, to December 31, 2021) to examine disproportionality in reporting hospitalizations suspected to be associated with 12 AAPs (aripiprazole, asenapine, brexpiprazole, clozapine, iloperidone, lurasidone, olanzapine, paliperidone, and pimavanserin, quetiapine, risperidone, and ziprasidone). Hospitalization in the FAERs database is an outcome that is recorded as a result of an AE occurring at any drug dose. We estimated reporting odds ratios (RORs) by comparing the odds of hospitalization occurring with a particular AAP to the odds of its occurrence with other drugs. In addition, we considered the presence of a significant safety signal when the lower limit of the 95% confidence interval (CI) of the ROR is >1.

Results

A total of 204,287 cases of hospitalizations were reported to the FDA for individuals treated with AAPs. There were significant safety signals of hospitalization associated with using clozapine (ROR, 2.88; 95% CI, 2.84-2.92), olanzapine (ROR, 2.61; 95% CI, 2.57-2.64), quetiapine (ROR, 1.87; 95% CI, 1.85-1.89), risperidone (ROR, 1.41; 95% CI, 1.39-1.43), aripiprazole (ROR, 1.34; 95% CI, 1.32-1.35), and ziprasidone (ROR, 1.14; 95% CI, 1.10-1.18). However, no hospitalization-related safety signals were observed with the use of paliperidone, pimavanserin, iloperidone, asenapine, lurasidone, and brexpiprazole. The ROR estimates were numerically higher among older adults than younger adults.

Conclusions

This cross-sectional assessment of data from FAERs (2004-2021) suggested that users of clozapine, olanzapine, quetiapine, risperidone, aripiprazole, and ziprasidone were more likely to report being hospitalized than users of other AAPs. Given that the FAERs database only contains spontaneous reports of AEs experienced by persons exposed to a drug but without information on exposed persons who did not have an event, a cohort study comparing hospitalizations among new users of individual AAPs against each other is needed to delineate these safety signals further.

Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)

In the past twenty years, the consumption of opioid medications has reached significant proportions, leading to a rise in drug misuse and abuse and increased opioid dependence and related fatalities. Thus, the purpose of this study was to determine whether there are pharmacovigilance signals of abuse, misuse, and dependence and their nature for the following prescription opioids: codeine, dihydrocodeine, fentanyl, oxycodone, pentazocine, and tramadol. Both the pharmacovigilance datasets EudraVigilance (EV) and the FDA Adverse Events Reporting System (FAERS) were analyzed to identify and describe possible misuse-/abuse-/dependence-related issues. A descriptive analysis of the selected Adverse Drug Reactions (ADRs) was performed, and pharmacovigilance signal measures (i.e., reporting odds ratio, proportional reporting ratio, information component, and empirical Bayesian geometric mean) were computed for preferred terms (PTs) of abuse, misuse, dependence, and withdrawal, as well as PTs eventually related to them (e.g., aggression). From 2003 to 2018, there was an increase in ADR reports for the selected opioids in both datasets. Overall, 16,506 and 130,293 individual ADRs for the selected opioids were submitted to EV and FAERS, respectively. Compared with other opioids, abuse concerns were mostly recorded in relation to fentanyl and oxycodone, while tramadol and oxycodone were more strongly associated with drug dependence and withdrawal. Benzodiazepines, antidepressants, other opioids, antihistamines, recreational drugs (e.g., cocaine and alcohol), and several new psychoactive substances, including mitragynine and cathinones, were the most commonly reported concomitant drugs. ADRs reports in pharmacovigilance databases confirmed the availability of data on the abuse and dependence of prescription opioids and should be considered a resource for monitoring and preventing such issues. Psychiatrists and clinicians prescribing opioids should be aware of their misuse and dependence liability and effects that may accompany their use, especially together with concomitant drugs.

A Proposal to Increase Value and Equity in the Development and Distribution of New Pharmaceuticals

The process of developing and marketing new pharmaceuticals in the United States is driven by a need to maximize returns to shareholders. This results all too often in the production of new medications that are expensive and of marginal value to patients and society. In line with our heightened awareness of the importance of social justice and public health—and in light of our government‘s alliance with private companies in bringing us COVID-19 vaccines—we need to reconsider how new pharmaceuticals are developed and distributed. Accordingly, we propose the creation of a new agency of the Food and Drug Administration (FDA) that would direct the whole process. This agency would fund the research and development of high-value medications, closely monitor the clinical studies of these new drugs, and manage their distribution at prices that are value-based, fair, and equitable.

A Focus on Abuse/Misuse and Withdrawal Issues with Selective Serotonin Reuptake Inhibitors (SSRIs): Analysis of Both the European EMA and the US FAERS Pharmacovigilance Databases

Despite increasing reports, antidepressant (AD) misuse and dependence remain underestimated issues, possibly due to limited epidemiological and pharmacovigilance evidence. Thus, here we aimed to determine available pharmacovigilance misuse/abuse/dependence/withdrawal signals relating to the Selective Serotonin Reuptake Inhibitors (SSRI) citalopram, escitalopram, paroxetine, fluoxetine, and sertraline. Both EudraVigilance (EV) and Food and Drug Administration-FDA Adverse Events Reporting System (FAERS) datasets were analysed to identify AD misuse/abuse/dependence/withdrawal issues. A descriptive analysis was performed; moreover, pharmacovigilance measures, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the information component (IC), and the empirical Bayesian geometric mean (EBGM) were calculated. Both datasets showed increasing trends of yearly reporting and similar signals regarding abuse and dependence. From the EV, a total of 5335 individual ADR reports were analysed, of which 30% corresponded to paroxetine (n = 1592), 27% citalopram (n = 1419), 22% sertraline (n = 1149), 14% fluoxetine (n = 771), and 8% escitalopram (n = 404). From FAERS, a total of 144,395 individual ADR reports were analysed, of which 27% were related to paroxetine, 27% sertraline, 18% citalopram, 16% fluoxetine, and 13% escitalopram. Comparing SSRIs, the EV misuse/abuse-related ADRs were mostly recorded for citalopram, fluoxetine, and sertraline; conversely, dependence was mostly associated with paroxetine, and withdrawal to escitalopram. Similarly, in the FAERS dataset, dependence/withdrawal-related signals were more frequently reported for paroxetine. Although SSRIs are considered non-addictive pharmacological agents, a range of proper withdrawal symptoms can occur well after discontinuation, especially with paroxetine. Prescribers should be aware of the potential for dependence and withdrawal associated with SSRIs.

Gabapentinoid-induced peripheral edema and acute heart failure: A translational study combining pharmacovigilance data and in vitro animal experiments

INTRODUCTION

Gabapentinoids are ligands of the α2-δ subunit of voltage-gated calcium channels (Cav) that have been associated with a risk of peripheral edema and acute heart failure in connection with a potentially dual mechanism, vascular and cardiac.

OBJECTIVES & METHODS

All cases of peripheral edema or heart failure involving gabapentin or pregabalin reported to the French Pharmacovigilance Centers between January 1, 1994 and April 30, 2020 were included to describe their onset patterns (e.g., time to onset). Based on these data, we investigated the impact of gabapentinoids on the myogenic tone of rat third-order mesenteric arteries and on the electrophysiological properties of rat ventricular cardiomyocytes.

RESULTS

A total of 58 reports were included (gabapentin n = 5, pregabalin n = 53). The female-to-male ratio was 4:1 and the median age was 77 years (IQR 57-85, range 32-95). The median time to onset were 23 days (IQR 10-54) and 17 days (IQR 3-30) for non-cardiogenic edema and acute heart failure, respectively. Cardiogenic and non-cardiogenic peripheral edema occurred frequently after a dose escalation (27/45, 60%), and the course was rapidly favorable after discontinuation of gabapentinoid (median 7 days, IQR 5-13). On rat mesenteric arteries, gabapentinoids significantly decreased the myogenic tone to the same extent as verapamil and nifedipine. Acute application of gabapentinoids had no significant effect on Ca_v1.2 currents of ventricular cardiomyocytes.

CONCLUSION

Gabapentinoids can cause concentration-dependent peripheral edema of early onset. The primary mechanism of non-cardiogenic peripheral edema is vasodilatory edema secondary to altered myogenic tone, independent of Ca_v1.2 blockade under the experimental conditions tested.

Descriptive Analysis of Adverse Drug Reactions Reports of the Most Consumed Antibiotics in Portugal, Prescribed for Upper Airway Infections

Adverse drug reactions (ADR) significantly impact mortality and morbidity and lead to high healthcare costs. Reporting ADR to regulatory authorities allows for monitoring the safety and efficacy profile of medicines on the market and for assessing the benefit–risk ratio. This retrospective study aims to characterize the ADR profile of the most consumed antibiotics in Portugal that are prescribed for upper airway infections and submitted to the EudraVigilance database. The variables were analyzed in an exploratory perspective, through absolute and relative frequencies, with emphasis on serious ADR. A total of 59,022 reports were analyzed of which 64.4% were classified as suspected serious ADR. According to serious ADR, the female sex (52.2%) and 18–64 age group (47.5%) prevail. Health professionals reported 87.8% of suspected serious ADR and European Economic Area (EEA) countries represented 50.8% of the reports. “Skin and subcutaneous tissue connections” (15.9%), “general disorders and administrations site conditions” (12%), and “gastrointestinal disorders” (9.8%) are the prevalent system organ classes. In 4.5% of the reports, patients had a fatal outcome. A periodic evaluation of the safety of the antibiotic should be performed to facilitate the development of guidelines and policies to reduce the frequency of serious ADR.

COVID-19 Outcomes and Vaccination in People with Relapsing Multiple Sclerosis Treated with Ofatumumab

Introduction

The SARS-CoV-2 pandemic necessitated better understanding of the impact of disease-modifying therapies on COVID-19 outcomes and vaccination. We report characteristics of COVID-19 cases and vaccination status in ofatumumab-treated relapsing multiple sclerosis (RMS) patients.

Methods

COVID-19 data analyzed were from the ongoing, open-label, long-term extension phase 3b ALITHIOS study from December 2019 (pandemic start) and post-marketing cases from August 2020 (ofatumumab first approval) up to 25 September 2021. COVID-19 cases, severity, seriousness, outcomes, vaccination status, and breakthrough infection were evaluated.

Results

As of 25 September 2021, 245 of 1703 patients (14.4%) enrolled in ALITHIOS receiving ofatumumab (median exposure: 2.45 years) reported COVID-19 (confirmed: 210; suspected: 35). Most COVID-19 was of mild (44.1%) or moderate (46.5%) severity, but 9% had severe/life-threatening COVID-19. There were 24 serious cases (9.8%) with 23 patients hospitalized; 22 recovered and 2 died. At study cut-off, 241 patients (98.4%) had recovered or were recovering or had recovered with sequelae and 2 (0.8%) had not recovered. Ofatumumab was temporarily interrupted in 39 (15.9%) patients. Before COVID-19 onset, IgG levels were within the normal range in all COVID-19–affected patients, while IgM was < 0.4 g/l in 23 (9.4%) patients. No patient had a reinfection. Overall, 559 patients were vaccinated (full, 476; partial, 74; unspecified, 9). Breakthrough infection was reported in 1.5% (7/476) patients, and 11 reported COVID-19 after partial vaccination. As of 25 September 2021, the Novartis Safety Database (~ 4713 patient-treatment years) recorded 90 confirmed COVID-19 cases receiving ofatumumab. Most cases were non-serious (n = 80), and ten were serious (1 medically significant, 9 hospitalized, 0 deaths). Among 36 of 90 cases with outcomes reported, 30 recovered and 6 did not recover.

Conclusion

COVID-19 in RMS patients on ofatumumab was primarily of mild/moderate severity and non-serious in these observational data. Most recovered from COVID-19 without treatment interruption. Two people died with COVID-19. Breakthrough COVID-19 despite being fully/partially vaccinated was uncommon.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00341-z.

A Standardized Dataset of a Spontaneous Adverse Event Reporting System

One of the largest spontaneous adverse events reporting databases in the world is the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Unfortunately, researchers face many obstacles in analyzing data from the FAERS database. One of the major obstacles is the unstructured entry of drug names into the FAERS, as reporters might use generic names or trade names with different naming structures from all over the world and, in some cases, with typographical errors. Moreover, report duplication is a known problem in spontaneous adverse event-reporting systems, including the FAERS database. Hence, thorough text processing for database entries, especially drug name entries, coupled with a practical case-deduplication logic, is a prerequisite to analyze the database, which is a time- and resource-consuming procedure. In this study, we provide a clean, deduplicated, and ready-to-import dataset into any relational database management software of the FAERS database up to September 2021. Drug names are standardized to the RxNorm vocabulary and normalized to the single active ingredient level. Moreover, a pre-calculated disproportionate analysis is provided, which includes the reporting odds ratio (ROR), proportional reporting ratio (PRR), Chi-squared analysis with Yates correction (x2), and information component (IC) for each drug-adverse event pair in the database.