EudraVigilance Medicines Safety Database: Publicly Accessible Data for Research and Public Health Protection

Analysis of Thrombotic Adverse Reactions of COVID-19 AstraZeneca Vaccine Reported to EudraVigilance Database

The development of safe, effective, affordable vaccines against COVID-19 remains the cornerstone to mitigating this pandemic. Early in December 2020, multiple research groups had designed potential vaccines. From 11 March 2021, several European countries temporarily suspended the use of the Oxford-AstraZeneca vaccine amid reports of blood clot events and the death of a vaccinated person, despite the European Medicines Agency (EMA) and the World Health Organization's assurance that there was no indication that vaccination was linked. This study aimed to identify and analyse the thrombotic adverse reactions associated with the Oxford-AstraZeneca vaccine. This was a retrospective descriptive study using spontaneous reports submitted to the EudraVigilance database in the period from 17 February to 12 March 2021. There were 54,571 adverse reaction reports, of which 28 were associated with thrombotic adverse reactions. Three fatalities were related to pulmonary embolism; one fatality to thrombosis. With 17 million people having had the AstraZeneca vaccine, these are extremely rare events The EMA's Pharmacovigilance Risk Assessment Committee (18 March 2021) concluded that the vaccine was safe, effective and the benefits outweighed the risks. Conducting further analyses based on more detailed thrombotic adverse event reports, including patients' characteristics and comorbidities, may enable assessment of the causality with higher specificity.

Automation in signal management in pharmacovigilance-an insight

Drugs are the imperial part of modern society, but along with their therapeutic effects, drugs can also cause adverse effects, which can be mild to morbid. Pharmacovigilance is the process of collection, detection, assessment, monitoring and prevention of adverse drug events in both clinical trials as well as in the post-marketing phase. The recent trends in increasing unknown adverse events, known as signals, have raised the need to develop an ideal system for monitoring and detecting the potential signals timely. The process of signal management comprises of techniques to identify individual case safety reports systematically. Automated signal detection is highly based upon the data mining of the spontaneous reporting system such as reports from health care professional, observational studies, medical literature or from social media. If a signal is not managed properly, it can become an identical risk associated with the drug which can be hazardous for the patient safety and may have fatal outcomes which may impact health care system adversely. Once a signal is detected quantitatively, it can be further processed by the signal management team for the qualitative analysis and further evaluations. The main components of automated signal detection are data extraction, data acquisition, data selection, and data analysis and data evaluation. This system must be developed in the correct format and context, which eventually emphasizes the quality of data collected and leads to the optimal decision-making based upon the scientific evaluation.

Does additional monitoring status increase the reporting of adverse drug reactions? An interrupted time series analysis of EudraVigilance data

Purpose

To evaluate the impact of including a medicine in the list of medicinal products subject to additional monitoring (AM) on the reporting of adverse drug reactions (ADRs) in the european economic area (EEA).

Methods

Interrupted time series using the monthly number of EEA ADR reports in EudraVigilance during 12 months before and after the addition to AM list. The main outcome was the change (%) in reporting of ADRs with step change as the a priori impact model. Further time series analysis was performed using Joinpoint Regression.

Results

The analysis included 11 active substances. No significant immediate (step change) increase of reporting was identified for any product at time of addition to AM list. We identified a significant gradual increase of ADR reporting after addition to AM list (slope change) for two out of five new products—boceprevir (10% per month, 95% confidence interval (CI) 3%–18%) and denosumab‐Xgeva (13% per month, 95% CI 4%–22%). No change was identified for Prolia, another denosumab‐containing product not subject to AM. No significant increase was identified for any product included in the AM list due to the requirement to conduct a PASS. Conversely, a gradual decrease in reporting was identified for natalizumab (−5% per month; 95% CI −10% to −1%), rivaroxaban (−5%; −8 to −3%), and varenicline (−16%; −21 to −10%). The results were corroborated by the Joinpoint analyses, which yielded similar results.

Conclusions

We identified limited evidence that reporting of ADRs increased modestly and gradually for some new products and not for products with PASS requirement.

Tisagenlecleucel in Children and Young Adults: Reverse Translational Research by Using Real-World Safety Data

Tisagenlecleucel has revolutionized the pharmacological approach of relapsed or refractory B-cell acute lymphoblastic leukaemialeukaemia in paediatrics. The safety profile of tisagenlecleucel still needs to be better defined. The aim of this study was a post-marketing evaluation of the safety of tisagenlecleucel through the analysis of the Eudravigilance database with focus on the paediatric population. From 2017 to 2020, one third of Individual Case Safety Reports referring to tisagenlecleucel (117/364) have been collected in paediatrics, on average nine year-old boys. Overall, 92% of the638 adverse events were serious and caused or prolonged hospitalisation. A total of 55 adverse events presented a fatal outcome, mainly due to progression of malignant neoplasm (N = 10; 18.2%), recurrence of acute lymphocytic leukaemia (N = 6; 10.9%) or occurrence of acute lymphocytic leukaemia (N = 5; 9.1%). Cytokine release syndrome was commonly reported after tisagenlecleucel infusion (54/638), followed by pyrexia (45/638) and hypotension (27/638). Only 18/638 events referred to neurotoxicity, none of them resulted in death. More than one third of cases (41/117) were suggestive of therapeutic failure. This first post-marketing analysis confirms pre-approval evidence of the safety profile of tisagenlecleucel in paediatrics. Since only a few years of marketing is available, further followed-up studies need to be performed to investigate longer-term safety of tisagenlecleucel.

Molecular basis of mood and cognitive adverse events elucidated via a combination of pharmacovigilance data mining and functional enrichment analysis

Drug-induced Mood- and Cognition-related adverse events (MCAEs) are often only detected during the clinical trial phases of drug development, or even after marketing, thus posing a major safety concern and a challenge for both pharmaceutical companies and clinicians. To fill some gaps in the understanding and elucidate potential biological mechanisms of action frequently associated with MCAEs, we present a unique workflow linking observational population data with the available knowledge at molecular, cellular, and psychopharmacology levels. It is based on statistical analysis of pharmacovigilance reports and subsequent signaling pathway analyses, followed by evidence-based expert manual curation of the outcomes. Our analysis: (a) ranked pharmaceuticals with high occurrence of such adverse events (AEs), based on disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) database, and (b) identified 120 associated genes and common pathway nodes possibly underlying MCAEs. Nearly two-thirds of the identified genes were related to immune modulation, which supports the critical involvement of immune cells and their responses in the regulation of the central nervous system function. This finding also means that pharmaceuticals with a negligible central nervous system exposure may induce MCAEs through dysregulation of the peripheral immune system. Knowledge gained through this workflow unravels putative hallmark biological targets and mediators of drug-induced mood and cognitive disorders that need to be further assessed and validated in experimental models. Thereafter, they can be used to substantially improve in silico/in vitro/in vivo tools for predicting these adversities at a preclinical stage.

Uses of pharmacovigilance databases: An overview

Over the past decades, assessment of drug safety and of their benefits harms balance has been profoundly modified by the availability of large databases and computerized automated statistical approaches. Improvement of digital data storage capacity has been applied to pharmacovigilance reports. VigiBase, the international pharmacovigilance database, is now aggregating over 21 million individual case safety reports in 2020. Identification and investigation of drug safety signals - concerning notably rare and unknown adverse drug reactions - is one of the major tasks in pharmacovigilance that can be amplified by automated signal detection. Several quantitative statistical methods exist, each with its own strengths and limits. Integrating signal detection, pharmacovigilance databases can be used for a wide variety of retrospective observational studies illustrated here by concrete examples. Confirming these signals by orthogonal validation using pre-clinical platforms and prospective trials is helpful. Pharmacovigilance databases represent a considerable source of information. However, the quality of signal detection and of pharmacoepidemiology studies in the field of adverse drug reaction closely depends on the quality of the individual data recorded.

An Application of Machine Learning in Pharmacovigilance: Estimating Likely Patient Genotype From Phenotypical Manifestations of Fluoropyrimidine Toxicity

Dihydropyrimidine dehydrogenase (DPD)‐deficient patients might only become aware of their genotype after exposure to dihydropyrimidines, if testing is performed. Case reports to pharmacovigilance databases might only contain phenotypical manifestations of DPD, without information on the genotype. This poses a difficulty in estimating the cases due to DPD. Auto machine learning models were developed to train patterns of phenotypical manifestations of toxicity, which were then used as a surrogate to estimate the number of cases of DPD‐related toxicity. Results indicate that between 8,878 (7.0%) and 16,549 (13.1%) patients have a profile similar to DPD deficient status. Results of the analysis of variable importance match the known end‐organ damage of DPD‐related toxicity, however, accuracies in the range of 90% suggest presence of overfitting, thus, results need to be interpreted carefully. This study shows the potential for use of machine learning in the regulatory context but additional studies are required to better understand regulatory applicability.

We Really Need Clear Guidelines and Recommendations for Safer and Proper Use of Aripiprazole and Risperidone in a Pediatric Population: Real-World Analysis of EudraVigilance Database

Background: Although aripiprazole and risperidone are used widespread in pediatrics, there are still limited pieces of evidence on their actual safety profile. By using the EudraVigilance database, we carried out an analysis to perform a comprehensive overview of reported adverse events among children and adolescents treated with aripiprazole and risperidone. Methods: Descriptive analysis was performed of all individual case safety reports (ISCRs) submitted to EudraVigilance associated with aripiprazole and risperidone and related to the pediatric population from 2016 to 2018. Results: A total of 855 and 2,242 ISCRs for aripiprazole and risperidone, respectively, were recorded for a total of 11,042 suspected adverse drug reactions (2,993 for aripiprazole and 8,049 for risperidone). Most ISCRs were related to male patients (65.0 and 86.3% for aripiprazole and risperidone, respectively) and were serious (81.0 and 94.1% for aripiprazole and risperidone, respectively). Schizophrenia spectrum and other psychotic disorders, such as disruptive, impulse-control, and conduct disorders, and autism spectrum disorder were the top three clinical indications for aripiprazole (19.0, 16.1, and 11.6%, respectively). For risperidone, attention-deficit/hyperactivity disorder (25.4%), disruptive, impulse-control, and conduct disorders (17.1%), and bipolar and related disorders (14.2%) were more commonly reported as clinical indications. Data also showed a high proportion of use for clinical conditions not authorized in children. Psychiatric disorders were the main related adverse events for aripiprazole (20.2%), and among these, suicidal behavior was one of the most reported (14.9%). Reproductive system and breast disorders were the main related adverse events for risperidone (19.8%), and gynecomastia was the most reported event; metabolism and nutrition disorders, mainly reported as weight gain disorders, were more reported in children (3-11 years) than in adolescents (12-17 years). Conclusions: Our results demonstrate that spontaneously reported adverse events associated with aripiprazole and risperidone reflect what is already known in terms of safety profile, although with about 90% of them being serious. This analysis stresses the need for further studies and effective training and information activities to better define the actual benefit/risk ratio of these drugs in pediatric patients.

Utilizing Advanced Technologies to Augment Pharmacovigilance Systems: Challenges and Opportunities

There are significant challenges and opportunities in deploying and utilizing advanced information technology (IT) within pharmacovigilance (PV) systems and across the pharmaceutical industry. Various aspects of PV will benefit from automation (e.g., by improving standardization or increasing data quality). Several themes are developed, highlighting the challenges faced, exploring solutions, and assessing the potential for further research. Automation of the workflow for processing of individual case safety reports (ICSRs) is adopted as a use case. This involves a logical progression through a series of steps that when linked together comprise the complete work process required for the effective management of ICSRs. We recognize that the rapid development of new technologies will invariably outpace the regulations applicable to PV systems. Nevertheless, we believe that such systems may be improved by intelligent automation. It is incumbent on the owners of these systems to explore opportunities presented by new technologies with regulators in order to evaluate the applicability, design, deployment, performance, validation and maintenance of advanced technologies to ensure that the PV system continues to be fit for purpose. Proposed approaches to the validation of automated PV systems are presented. A series of definitions and a critical appraisal of important considerations are provided in the form of use cases. We summarize progress made and opportunities for the development of automation of future systems. The overall goal of automation is to provide high quality safety data in the correct format, in context, more quickly, and with less manual effort. This will improve the evidence available for scientific assessment and helps to inform and expedite decisions about the minimization of risks associated with medicines.

Improving the Safety of Medicines in the European Union: From Signals to Action

Pharmacovigilance and risk minimization must be planned during drug development and forms a critical part of the regulator's decision on whether a medicinal product can be authorized. Pharmacovigilance systems should ensure proactive monitoring of all authorized medicines throughout their lifecycle in clinical use. Signal detection and management are core activities in pharmacovigilance, rapidly delivering new information on the safety of medicines in real-world use which helps to fill knowledge gaps. The first 6 years of the European Union (EU) signal management system resulted in 453 recommendations issued by the Pharmacovigilance Risk Assessment Committee (PRAC), of which more than half were for drug labeling changes. The EU pharmacovigilance network has demonstrated its ability to detect and evaluate new drug safety signals. This has resulted in new warnings to guide the safe and effective use of medicines in Europe.

In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR

A plethora of databases exist online that can assist in in silico chemical or drug safety assessment. However, a systematic review and grouping of databases, based on purpose and information content, consolidated in a single source, has been lacking. To resolve this issue, this review provides a comprehensive listing of the key in silico data resources relevant to: chemical identity and properties, drug action, toxicology (including nano-material toxicity), exposure, omics, pathways, Absorption, Distribution, Metabolism and Elimination (ADME) properties, clinical trials, pharmacovigilance, patents-related databases, biological (genes, enzymes, proteins, other macromolecules etc.) databases, protein-protein interactions (PPIs), environmental exposure related, and finally databases relating to animal alternatives in support of 3Rs policies. More than nine hundred databases were identified and reviewed against criteria relating to accessibility, data coverage, interoperability or application programming interface (API), appropriate identifiers, types of in vitro, in vivo,-clinical or other data recorded and suitability for modelling, read-across, or similarity searching. This review also specifically addresses the need for solutions for mapping and integration of databases into a common platform for better translatability of preclinical data to clinical data.

Pharmacovigilance in India in Comparison With the USA and European Union: Challenges and Perspectives

Pharmacovigilance (PV) is an integral part of the drug regulation system. PV plays an indispensable role in the identification, assessment, and publicizing of adverse drug reactions (ADRs) through various methods. ADRs account for serious harm to the patients and even lead to morbidity and mortality. The PV databases help in the promotion of safe drug use and protection of public health safety. This article compares the PV system in the USA, Europe, and India, highlighting the challenges and future perspectives to be adapted to widen the horizon of the existing PV structure in India. In India, PV programs are still at the dawning stage when paralleled to the other countries. The National Pharmacovigilance Program and the Pharmacovigilance Program of India are the most recent advancements in this field in the country. The USA and Europe have well-established PV systems in place thanks to technological progress and other resources. India is the largest producer of pharmaceuticals in the world and a major clinical research hub; hence, it requires a more stringent PV setup. With the increase in population and novel drugs in the market each day, there is a need for an effective PV system in India.