Pharmacovigilance: An Overview

A retrospective analysis of the pharmacovigilance data registry in a tertiary teaching hospital in Jordan

Objectives

The study aims to analyse adverse drug reaction (ADR) reporting patterns at Jordan University Hospital to enhance pharmacovigilance practices.

Methods

Retrospective analysis of ADR data from February to August 2023 was conducted. Data included patient demographics, drugs implicated, seriousness criteria, and system organ classes affected.

Results

Among 1340 ADR reports analysed, females accounted for 67.4% of cases, with adults aged 18 to less than 65 years comprising 95.3% of reports. The majority of ADRs were non-serious, with only 2.1% resulting in hospitalisation or prolonged hospital stay. The most frequently reported ADRs included abdominal pain (8.3%), nausea (6.9%), headache (4.7%), and dizziness (4.7%). Notably, cardiovascular system drugs (16.4%) and alimentary tract and metabolism drugs (16.2%) were commonly associated with ADRs, followed by musculoskeletal system drugs (9.0%). Additionally, among all reported drugs, 99.9% were considered suspects, (suspected ADR cases include patient treatment cases for which a likelihood of being related to a drug therapy was scored as 'possible', 'probable', or 'certain' after causality assessment (by the WHO-UMC system in 2017), with oral administration being the predominant route (89.5%).

Conclusion

The study highlights a notable increase in ADR reporting during the study period compared to historical data, indicating heightened awareness and understanding among healthcare providers. Enhanced pharmacovigilance practices, particularly involving pharmacists, are essential for detecting and reporting ADRs effectively. Further investigation into factors contributing to prevalent serious ADRs is warranted to improve patient safety and health outcomes.

Moderate and serious adverse reactions to antimicrobials among hospitalized children: A systematic review

AIMS

This systematic review aimed to investigate the occurrence of moderate and severe adverse drug reactions (ADRs) to antimicrobials among hospitalized children.

METHODS

The PubMed/Medline, Cochrane Library, Embase, Web of Science, Scopus, Lilacs and CINAHL databases were searched in April 2023 to systematically review the published data describing the characteristics of moderate and severe ADRs to antimicrobials among hospitalized children. The search was carried out without date restrictions, up to the search date (April, 2023).

RESULTS

At the end of the selection process, 30 articles met the inclusion criteria. Cutaneous reactions were the primary serious clinical manifestations in most articles (19/30), followed by erythema multiforme (71 cases), Stevens-Johnson syndrome (72 cases), and toxic epidermal necrolysis (22 cases). The main antimicrobials involved in moderate and severe ADRs were penicillins, cephalosporins and sulfonamides. Regarding the primary outcomes, 30% (9/30) of the articles reported deaths, and 46.7% (14/30) of studies reported increased lengths of hospital stay, need for intensive care, and transfer to another hospital. Regarding the main interventions, 10% (3/30) of the articles mentioned greater monitoring, suspension, medication substitution or prescription of specific medications for the symptomatology.

CONCLUSIONS

The findings of this review could be used to identify areas for improvement and help health professionals and policymakers develop strategies. In addition, we emphasize the importance of knowing about ADRs so that there is adequate management to avoid undesirable consequences.

Strategic Partnerships in Pharmacovigilance: Business, Legal, and Regulatory Domains

Pharmaceutical development is a highly regulated industry through numerous worldwide guidance, laws, and regulations. Issues related to the safety of pharmaceutical products have been the most common cause of withdrawals from the market, as well as restrictions on distribution and limitations on labeling. Collaboration (hereafter referred to as partnership) between pharmaceutical companies in drug development has been recognized as critically significant to maximize the efficiency of drug development. In general, pharmaceutical companies might benefit from partnering in conducting pharmacovigilance (PV) activities, resulting in enhanced safety monitoring, improved clinical outcomes, and support of optimal benefit-risk assessment. However, some challenges exist. Differences between partners in strategy, culture, and processes can impact the harmonization of safety practices and decision-making processes, necessitating open communications and consensus-building to effectively address safety concerns. Both successful and unsuccessful partnership attempts within the pharmaceutical industry provide valuable business cases and lessons for the future. This paper sheds light on some of the critical aspects of PV in partnerships within the pharmaceutical industry. It addresses issues of the benefits and risks of partnerships, regulatory/legal expectations, and best practices for safety teams' integration.

Development of a Safety Surveillance Plan for the Academic Medicine Sponsor Performing First-in-Human Cellular Therapy Clinical Trials: A Report from the Consortium for Pediatric Cellular Immunotherapy

Pharmacovigilance (PV), also known as drug safety, is the science of risk management involving the detection, assessment, understanding, and prevention of adverse effects related to a medication. This discipline has traditionally focused on the postmarketing period, with less attention to early-phase clinical trials. However, during the immunotherapy and cellular therapy investigational stage, regulatory agencies are increasingly emphasizing the need to identify and characterize safety signals earlier in clinical development as part of a comprehensive safety surveillance plan. Compliance with PV and safety regulations are further heightened as cell and gene therapy (CGT) trials grow in complexity and scope owing to ever-changing and increasingly rigorous regulatory mandates. Based on this changing landscape, a critical aspect of early-phase trials of cellular products where significant safety events are anticipated is to ensure that every effort is made to protect clinical trial participants by maximizing attention to the risk-versus-benefit profile. This includes the development of robust plans for safety surveillance that provide a continual assessment of safety signals to enable safety reporting to regulatory bodies and the Food and Drug Administration, a regular analysis of aggregate safety data, and a plan to communicate safety findings. This report focuses on PV in early-phase clinical trials of first-in-human investigational products sponsored by academic centers in which the availability of PV resources and subject matter experts is limited. To more fully understand the challenges of CGT PV oversight within pediatric academic medical centers conducting early-phase clinical trials, a working group from institutions participating in the Consortium for Pediatric Cellular Immunotherapy composed of faculty and regulatory professionals was convened to compare experiences, identify best practices, and review published literature to identify commonalities and opportunities for alignment. Here we present guidelines on PV planning in early-phase CGT clinical trials occurring in academic medical centers and offer strategies to mitigate risk to trial participants. Standards to address regulatory requirements and governance for safety signal identification and risk assessment are discussed.

Drug-Induced Acute Pancreatitis: A Real-World Pharmacovigilance Study Using the FDA Adverse Event Reporting System Database

Timely identification and discontinuation of culprit-drug is the cornerstone of clinical management of drug-induced acute pancreatitis (AP), but the comprehensive landscape of AP culprit-drugs is still lacking. To provide the current overview of AP culprit-drugs to guide clinical practice, we reviewed the adverse event (AE) reports associated with AP in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database from 2004 to 2022, and summarized a potential AP culprit-drug list and its corresponding AE report quantity proportion. The disproportionality analysis was used to detect adverse drug reaction (ADR) signals for each drug in the drug list, and the ADR signal distribution was integrated to show the risk characteristic of drugs according to the ADR signal detection results. In the FAERS database, a total of 62,206 AE reports were AP-related, in which 1,175 drugs were reported as culprit-drug. On the whole, metformin was the drug with the greatest number of AE reports, followed by quetiapine, liraglutide, exenatide, and sitagliptin. Drugs used in diabetes was the drug class with the greatest number of AE reports, followed by immunosuppressants, psycholeptics, drugs for acid-related disorders, and analgesics. In disproportionality analysis, 595 drugs showed potential AP risk, whereas 580 drugs did not show any positive ADR signal. According to the positive-negative distribution of the ADR signal for drug classes, the drug class with the greatest number of positive drugs was antineoplastic agents. In this study, we provided the current comprehensive landscape of AP culprit-drugs from the pharmacovigilance perspective, which can provide reference information for clinical practice.

Why Oncology Global Safety Teams Should Develop the Safety Section of the Study's Target Product Profile (TPP)

Oncology Global Safety Teams (GSTs) are not universally tasked with the development of the risk section of the products target product profile (TPP). This fact makes little sense since the GST is tasked by the company to identify, analyze, and mitigate a product's risks. The TPP, in essence, establishes boundaries for go/no-go decisions around a product or products in combination treatment. Involvement of the Oncology GST in producing a well-researched and evidenced based TPP safety section allows the team to develop knowledge around the drug(s) studied or added to a study arm. The increased use of umbrella and platform studies for early-phase oncology trials allows an excellent resource for the use of clinical data to estimate the risk of developmental drugs combined to treat a given oncology indication. To shorten time to marketing, companies are including developmental products with novel mechanisms early within their development cycles. Antibody drug conjugates (ADCs) and bi-directional antibodies are a few examples of products combined in arms of a platform or umbrella study early and with only immature clinical data available. This article will share a novel analytical approach for safety teams to develop a well thought-out and defendable safety section to the TPP. Strategies to estimate the risks associated with combination therapies will be brought forward. The advantages of having the safety team involved early in the benefit/risk, go/no-go decisions for a study or the addition of a study arm will be detailed. The early development of a well-documented TPP will enhance chances of a successful product submission.

An Overview of Biosimilars-Development, Quality, Regulatory Issues, and Management in Healthcare

Biological therapies have transformed high-burden treatments. As the patent and exclusivity period for biological medicines draws to a close, there is a possibility for the development and authorization of biosimilars. These products boast comparable levels of safety, quality, and effectiveness to their precursor reference products. Biosimilars, although similar to reference products, are not identical copies and should not be considered generic substitutes for the original. Their development and evaluation involve a rigorous step-by-step process that includes analytical, functional, and nonclinical evaluations and clinical trials. Clinical studies conducted for biosimilars aim to establish similar efficacy, safety, and immunogenicity, rather than demonstrating a clinical benefit, as with the reference product. However, although the current knowledge regarding biosimilars has significantly increased, several controversies and misconceptions still exist regarding their immunogenicity, extrapolation, interchangeability, substitution, and nomenclature. The development of biosimilars stimulates market competition, contributes toward healthcare sustainability, and allows for greater patient access. However, maximizing the benefits of biosimilars requires cooperation between regulators and developers to ensure that patients can benefit quickly from access to these new therapeutic alternatives while maintaining high standards of quality, safety, and efficacy. Recognizing the inherent complexities of comprehending biosimilars fully, it is essential to focus on realistic approaches, such as fostering open communication between healthcare providers and patients, encouraging informed decision-making, and minimizing risks. This review addresses the regulatory and manufacturing requirements for biosimilars and provides clinicians with relevant insights for informed prescribing.

Understanding factors influencing the implementation of medicine risk communications by healthcare professionals in clinical practice: a systematic review using the Theoretical Domains Framework

BACKGROUND

Adverse drug reactions (ADRs) are known to cause hospitalisation, longer hospital stays, as well as higher healthcare costs and mortality. Unrecognised ADRs are anticipated throughout the medicine lifecycle as, before the medicine reaches the market, clinical trials are conducted for a short period on a limited number of people, who might underrepresent the actual population. After the medicine reaches the market, emergent information that could affect its benefit-to-risk balance is usually shared by regulatory agencies and pharmaceutical companies through medicine risk communications. Medicines risk communications aim to prevent harm to patients by targeting their behaviour, knowledge, and attitudes, as well as those of health care professionals (HCPs). Despite their important role in translating these communications into their clinical practice, HCPs do not always adhere to the recommendations provided in risk communications. Measurement of medicine risk communications' effectiveness does not necessarily guarantee their implementation, cost-effectiveness, or transferability in real-world situations. To enhance the impact of drug regulatory interventions, implementation science has been encouraged. However, implementation science was not previously used to identify factors affecting HCPs' implementation of medicines risk communications. A recently widely used framework is the Theoretical Domain Framework (TDF). In this systematic review, the TDF was employed to categorise a range of different factors that could affect HCPs' implementation of medicine risk communications within their clinical contexts.

METHODS

The search strategy involved a set of predefined search terms and fifteen databases, such as EMBASE, PubMed, Web of Science and CINAHL PLUS. Searches were conducted from April to May 2018 and updated in June 2021 using PubMed, Scopus, and CINAHL PLUS. A second reviewer independently conducted the screening process of the initial search. The total number of records screened was 10,475. A study was included if it reported any factors influencing HCPs' uptake of medicine risk communications. Only studies with English or Arabic abstracts were included. Those studies that did not include pharmacovigilance-related medicine risk communications were excluded. Additionally, studies only assessing HCPs' practice or evaluating the effectiveness of risk minimisation measures were excluded. Likewise, studies related to occupational hazards, case reports, interventional studies, and studies not involving HCPs were excluded. In case the published information was insufficient to decide whether to include or exclude a study, the authors were contacted. Furthermore, the authors of seven eligible abstracts were contacted for full-text articles. The mixed method appraisal tool (MMAT) was used to evaluate the quality of the included studies. All included studies were assessed by one reviewer, and a total of 16 studies were assessed by two reviewers independently. Disagreements were resolved through discussion. Using thematic analysis and concept mapping, a narrative synthesis was performed, followed by a critical reflection on the synthesis process. This review presents the results of the concept mapping, which involved matching the identified factors to the TDF.

RESULTS

A total of 28 studies were included. Eleven domains influenced HCPs' implementation of medicine risk communications. A large number of studies included factors related to the "Knowledge" domain (n = 23), followed by "Beliefs about Consequences" (n = 13), "Memory, Attention and Decision Processes" (n = 12) and "Environmental Context and Resources" domains (n = 12). Seven studies reported "social influences" and six studies included factors relating to "Goals", followed by four studies involving factors related to "Social/Professional Role and Identity". Underrepresented domains included "Emotion" (n = 2), "Beliefs about Capabilities" (n = 2), "Behavioural Regulation" (n = 1), and "Reinforcement" (n = 1). On the other hand, none of the identified factors were related to the "Skills", "Optimism", or "Intentions" domains. Except for "Beliefs about Consequences", most studies contributing to the other three most commonly reported domains ("Knowledge"; "Environmental Context and Resources"; and "Memory, Attention and Decision Processes") scored low (1 or 2 out of 5) on the MMAT quality assessment. Moreover, the same number of studies (n = 5) contributing to the "Beliefs about Consequences" domain had low (1 or 2 out of 5), and intermediate (3 out of 5) scores on the MMAT.

CONCLUSION

Medicines risk communications are important tools for disseminating information that may influence the benefit-to-risk balance of medicines. Even though HCPs are required to implement the recommendations of these communications, they do not always adhere to them. Using the TDF enabled the categorization of the range of factors that affect whether or not HCPs implement the recommendations provided in a medicine risk communication. However, most of these factors relate to four domains only ("Knowledge"; "Beliefs about Consequences"; "Memory, Attention and Decision Processes"; and "Environmental Context and Resources"). Additionally, most of the studies contributing to three of these four domains were of low quality. Future research should focus on using implementation science to identify target behaviours for actionable medicine risk communications. Regulators should use such science to develop cost-effective strategies for improving the implementation of medicines risk communication by HCPs.

Pharmacovigilance in Brazil: The Government Monitoring of Adverse Events Reported from COVID-19 Vaccine-A Narrative Review

BACKGROUND

Is pharmacovigilance at a moment of prominence for science, and in relation to governments' responsibilities towards their nations, as the new coronavirus pandemic has surprised everyone in a negative and lethal way?

OBJECTIVE

Evaluate pharmacovigilance as a resource for controlling and understanding adverse events caused by vaccines in use.

METHODS

This is a narrative review of the literature. Scientific articles available in databases, government bulletins and similar bodies were used. The search was carried out using the descriptors: "Pharmacovigilance AND COVID-19 in Brazil", "Vaccine Development AND COVID-19", "Vaccination Hesitancy AND COVID-19", "Public Health Surveillance AND COVID-19". The period from May 2021 to June 2022 was covered.

RESULTS

The occurrence of some adverse events was observed, including cases of allergy, myocarditis and rheumatoid arthritis. It is important to highlight that these adverse events were identified as rare, occurring in a small percentage of the vaccinated population. Despite these adverse events, the benefits of vaccines proved to be essential for controlling the pandemic.

CONCLUSIONS

The information presented highlights the importance of pharmacovigilance to continuously monitor and evaluate the safety of vaccines, identifying any potential adverse events early. This balance between risk and benefit emphasizes the need for a careful and informed approach when making decisions about vaccination policies, prioritizing public health and population safety.

Contrastive analysis on the safety of brand and generic nebivolol: a real-world pharmacovigilance study based on the FDA adverse event reporting system

Background: The equivalence of generic drugs to their brand-name counterparts is a controversial issue. Current literature indicates disparities between the generic nebivolol (GN) and the brand nebivolol (BN). Aim: The study is designed to investigate the safety difference between GN and BN and provide reference information for clinical practice. Methods: We reviewed adverse event (AE) reports that recorded nebivolol as the primary suspect drug in the FDA Adverse Event Reporting System (FAERS) database from 2004 to 2022, conducted a disproportional analysis to detect signals for the GN and BN respectively, and compared the AE heterogeneity between them using the Breslow-Day test. Results: A total of 2613 AE reports of nebivolol were recorded in the FAERS database from 2004 to 2022, of which 2,200 were classified as BN, 346 as GN, and 67 unclassifiable AE reports were excluded. The signals of 37 AEs distributed in cardiac, gastrointestinal, psychiatric, and nervous systems were detected in disproportional analysis. 33 out of 37 AEs were positive signals, with 21 not previously listed on the drug label, indicating an unrecognized risk with nebivolol. In the heterogeneity analysis of AE signals between GN and BN, the GN generally showed a higher AE signal value than BN, especially 15 AEs distributed in the cardiac, neurological, and psychiatric systems that showed statistically significantly higher risk by taking GN. Conclusion: Our study shows some previously overlooked adverse effects of nebivolol. It suggests that the risk of GN's adverse effects may be higher than those in BN, which deserves further attention and investigation by healthcare professionals, regulators, and others.

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.

The International Working Group on New Developments in Pharmacovigilance: Advancing Methods and Communication in Pharmacovigilance

PURPOSE

In 2019, the International Working Group (IWG), focusing on New Developments in Pharmacovigilance, was established. This group is coordinated by the Drug Safety Research Unit in the United Kingdom, and the mission of the IWG is to progress pharmacovigilance methodologies and promote the safe and effective use of medicines and vaccines, thereby further protecting patients. Novel therapeutics are continuously being developed to alleviate medical conditions, but with advancing technologies, innovative pharmacovigilance methodologies need to be developed to effectively monitor the use and safety of these products. With reduced timelines proposed for premarketing clinical trials and increased application of real-world evidence supporting regulatory approvals, products may be used in real-world clinical practice in shorter timeframes than before. Therefore, the need for effective methods of monitoring medicines and collecting safety data in real-time is of paramount importance to public health.

METHODS

The IWG aims to advance existing methodologies used in the detection, monitoring, and analysis of safety data in pharmacovigilance and to communicate best practice proposals to support decision making in health care. The IWG will identify areas requiring review of current processes or methodologic research and will communicate the output of the IWG through peer-reviewed publications, reports, and presentation of findings at relevant conferences and scientific meetings.

FINDINGS

The IWG is currently reviewing two areas in pharmacovigilance; case-level causality assessment and the strengths and limitations of data sources. The IWG is advancing these areas by producing two scoping reviews which will be easily accessible to regulatory agencies, industry, academia, and interested persons or organizations.

IMPLICATIONS

The scoping reviews comply with the IWGs mission to progress pharmacovigilance methodologies and promote the safe and effective use of medicines and vaccines. The present article shares details of the objectives of the IWG and provides an overview on the status of IWG activities.

Drug-induced QT prolongation and torsade de pointes: a real-world pharmacovigilance study using the FDA Adverse Event Reporting System database

Introduction: Drug-induced QT prolongation and (or) Torsade de Pointes (TdP) is a well-known serious adverse reaction (ADR) for some drugs, but the widely recognized comprehensive landscape of culprit-drug of QT prolongation and TdP is currently lacking. Aim: To identify the top drugs reported in association with QT prolongation and TdP and provide information for clinical practice. Method: We reviewed the reports related to QT prolongation and TdP in the FDA Adverse Event Reporting System (FAERS) database from January 1, 2004 to December 31, 2022, and summarized a potential causative drug list accordingly. Based on this drug list, the most frequently reported causative drugs and drug classes of QT prolongation and TdP were counted, and the disproportionality analysis for all the drugs was conducted to in detect ADR signal. Furthermore, according to the positive-negative distribution of ADR signal, we integrated the risk characteristic of QT prolongation and TdP in different drugs and drug class. Results: A total of 42,713 reports in FAERS database were considered to be associated with QT prolongation and TdP from 2004 to 2022, in which 1,088 drugs were reported as potential culprit-drugs, and the largest number of drugs belonged to antineoplastics. On the whole, furosemide was the most frequently reported drugs followed by acetylsalicylic acid, quetiapine, citalopram, metoprolol. In terms of drug classes, psycholeptics was the most frequently reported drug classes followed by psychoanaleptics, analgesics, beta blocking agents, drugs for acid related disorders. In disproportionality analysis, 612 drugs showed at least one positive ADR signals, while citalopram, ondansetron, escitalopram, loperamide, and promethazine were the drug with the maximum number of positive ADR signals. However, the positive-negative distribution of ADR signals between different drug classes showed great differences, representing the overall risk difference of different drug classes. Conclusion: Our study provided a real-world overview of QT prolongation and TdP to drugs, and the presentation of the potential culprit-drug list, the proportion of reports, the detection results of ADR signals, and the distribution characteristics of ADR signals may help understand the safety profile of drugs and optimize clinical practice.

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.

Navigating the complex landscape of benzodiazepine- and Z-drug diversity: insights from comprehensive FDA adverse event reporting system analysis and beyond

Introduction

Medications which target benzodiazepine (BZD) binding sites of GABAA receptors (GABAARs) have been in widespread use since the nineteen-sixties. They carry labels as anxiolytics, hypnotics or antiepileptics. All benzodiazepines and several nonbenzodiazepine Z-drugs share high affinity binding sites on certain subtypes of GABAA receptors, from which they can be displaced by the clinically used antagonist flumazenil. Additional binding sites exist and overlap in part with sites used by some general anaesthetics and barbiturates. Despite substantial preclinical efforts, it remains unclear which receptor subtypes and ligand features mediate individual drug effects. There is a paucity of literature comparing clinically observed adverse effect liabilities across substances in methodologically coherent ways.

Methods

In order to examine heterogeneity in clinical outcome, we screened the publicly available U.S. FDA adverse event reporting system (FAERS) database for reports of individual compounds and analyzed them for each sex individually with the use of disproportionality analysis. The complementary use of physico-chemical descriptors provides a molecular basis for the analysis of clinical observations of wanted and unwanted drug effects.

Results and Discussion

We found a multifaceted FAERS picture, and suggest that more thorough clinical and pharmacoepidemiologic investigations of the heterogenous side effect profiles for benzodiazepines and Z-drugs are needed. This may lead to more differentiated safety profiles and prescription practice for particular compounds, which in turn could potentially ease side effect burden in everyday clinical practice considerably. From both preclinical literature and pharmacovigilance data, there is converging evidence that this very large class of psychoactive molecules displays a broad range of distinctive unwanted effect profiles - too broad to be explained by the four canonical, so-called "diazepam-sensitive high-affinity interaction sites". The substance-specific signatures of compound effects may partly be mediated by phenomena such as occupancy of additional binding sites, and/or synergistic interactions with endogenous substances like steroids and endocannabinoids. These in turn drive the wanted and unwanted effects and sex differences of individual compounds.

Exploratory pharmacovigilance with machine learning in big patient data: A focused scoping review

BACKGROUND

Machine learning can operationalize the rich and complex data in electronic patient records for exploratory pharmacovigilance endeavours.

OBJECTIVE

The objective of this review is to identify applications of machine learning and big patient data in exploratory pharmacovigilance.

METHODS

We searched PubMed and Embase and included original articles with an exploratory pharmacovigilance purpose, focusing on medicinal interventions and reporting the use of machine learning in electronic patient records with ≥1000 patients collected after market entry.

FINDINGS

Of 2557 studies screened, seven were included. Those covered six countries and were published between 2015 and 2021. The most prominent machine learning methods were random forests, logistic regressions, and support vector machines. Two studies used artificial neural networks or naive Bayes classifiers. One study used formal concept analysis for association mining, and another used temporal difference learning. Five studies compared several methods against each other. The numbers of patients in most data sets were in the order of thousands; two studies used what can more reasonably be considered big data with >1 000 000 patients records.

CONCLUSION

Despite years of great aspirations for combining machine learning and clinical data for exploratory pharmacovigilance, only few studies still seem to deliver somewhat on these expectations.

Using GPT-3 to Build a Lexicon of Drugs of Abuse Synonyms for Social Media Pharmacovigilance

Drug abuse is a serious problem in the United States, with over 90,000 drug overdose deaths nationally in 2020. A key step in combating drug abuse is detecting, monitoring, and characterizing its trends over time and location, also known as pharmacovigilance. While federal reporting systems accomplish this to a degree, they often have high latency and incomplete coverage. Social-media-based pharmacovigilance has zero latency, is easily accessible and unfiltered, and benefits from drug users being willing to share their experiences online pseudo-anonymously. However, unlike highly structured official data sources, social media text is rife with misspellings and slang, making automated analysis difficult. Generative Pretrained Transformer 3 (GPT-3) is a large autoregressive language model specialized for few-shot learning that was trained on text from the entire internet. We demonstrate that GPT-3 can be used to generate slang and common misspellings of terms for drugs of abuse. We repeatedly queried GPT-3 for synonyms of drugs of abuse and filtered the generated terms using automated Google searches and cross-references to known drug names. When generated terms for alprazolam were manually labeled, we found that our method produced 269 synonyms for alprazolam, 221 of which were new discoveries not included in an existing drug lexicon for social media. We repeated this process for 98 drugs of abuse, of which 22 are widely-discussed drugs of abuse, building a lexicon of colloquial drug synonyms that can be used for pharmacovigilance on social media.

Estimating Culprit Drugs for Adverse Drug Reactions Based on Bayesian Inference

The utility of big data in spontaneous adverse drug reactions (ADRs) reporting systems has improved the pharmacovigilance process. However, identifying culprit drugs in ADRs remains challenging, although it is one of the foremost steps to managing ADRs. Aiming to estimate the likelihood of prescribed drugs being culprit drugs for given ADRs, we devised a Bayesian estimation model based on the Japanese Adverse Drug Events Reports database. After developing the model, a validation study was conducted with 67 ADR reports with a gross of 1,387 drugs (67 culprit drugs and 1,320 concomitant drugs) prescribed and recorded at Yamaguchi University Hospital. As a result, the model estimated a culprit drug of ADRs with acceptable accuracy (area under the receiver operating characteristic curve 0.93 (95% confidence interval 0.88-0.97)). The estimation results provided by the model to healthcare practitioners can be used as one clue to determine the culprit drugs for various ADRs, which will improve the management of ADRs by shortening the treatment turnaround time and increasing the precision of diagnosis, leading to minimizing the adverse effects on patients.

Socio-historical analysis of the social importance of pharmacovigilance

Pharmacovigilance is a scientific discipline that has changed a lot in recent years and is of great social importance. The case of the so-called sulfonamide elixir showed society the importance of this discipline. Since then, pharmacovigilance has evolved into a scientific discipline with a strong social character. In this paper, a historical review is made of several paradigmatic examples of this discipline to reflect on what pharmacovigilance could be like finally. We conclude that this discipline could be more closely related to other areas of the social sciences, which would help to promote a more democratic social environment taking into account the needs of individuals and social groups.

Pharmacovigilance: reporting requirements throughout a product's lifecycle

Comprehensive methods for evaluating safety are needed to objectively assess the full risk profile of a medication. The confidence of the prescribing provider in the safety and effectiveness of pharmaceuticals is extremely important. Pharmacovigilance is a key component of drug safety regulatory processes and is paramount for ensuring the safety profile of medications used to treat patients. All participants in the healthcare system, including healthcare providers and consumers, should understand and meaningfully engage in the pharmacovigilance process; healthcare providers should integrate pharmacovigilance into everyday practice, inviting feedback from patients. This narrative review aims to give an overview of the main topics underlying pharmacovigilance and drug safety in pharmaceutical research phase after the authorization of a drug in the United States. The US Food and Drug Administration guidance and post-approval regulatory actions are considered from an industry perspective.

Plain language summary

Regulatory processes that ensure the safety of drugs is monitored Government agencies regulate the safe use of medicinal products. By determining and enforcing pharmacovigilance, the monitoring of drugs for potential risks, they safeguard the welfare of consumers of medicines. Comprehensive, documented methods for evaluating the safety of a drug during its development and its subsequent use allow identification of any risks associated with the drug's use throughout its lifetime. The comprehensive identification of safety issues associated with a drug is improved when all parties involved in the development and use of drugs participate in the pharmacovigilance process. For example, clinicians should regularly ask their patients if they are experiencing any issues with their treatment, and patients should be encouraged to report problems they encounter with a particular medication to their healthcare provider. This narrative review provides an overview of the main topics underlying pharmacovigilance and drug safety after approval of a drug in the United States. Guidelines and actions from the US Food and Drug Administration are considered from an industry perspective.

The role of in vitro testing in pharmacovigilance for ß-lactam-induced serum sickness-like reaction: A pilot study

Background: Current pharmacovigilance (PV) methods for detection of adverse drug reactions (ADRs) fail to capture rare immune-mediated drug hypersensitivity reactions (DHRs) due to their scarcity and the lack of clear diagnostic criteria. Drug-induced serum sickness-like reactions (SSLRs) are rare type of DHRs that occur in susceptible patients 1–3 weeks after exposure to the culprit drug with ß-lactam antibiotics being the most associated drugs. The diagnosis of drug induced SSLR is difficult due to the lack of safe and reliable diagnostic tests for identifying the culprit drug. The lymphocyte toxicity assay (LTA) is an in vitro test used as a diagnostic tool for drug hypersensitivity reactions (DHRs).

Objective: To evaluate the role of the LTA test for diagnosing and capturing SSLR due to ß-lactam antibiotics in a cohort of patients.

Methods: Patients were recruited from patients referred to the Drug Hypersensitivity Clinic at Clinic at London Health Science Centre with suspicion of drug allergy. Twenty patients (10 males and 10 females) were selected to be tested to confirm diagnosis. Demographic data was collected form the patents and blood samples were withdrawn from all patients and from 20 healthy controls. The LTA test was performed on all subjects and data is expressed as percentage increase in cell death compared to control (vehicle without the drug).

Results: In the result of LTA tests performed on samples from the selected 20 patients. There was a significant (p < 0.05) concentration-dependent increase in cell death in cells isolated from patients as compared to cells from healthy controls when incubated with the drug in the presence of phenobarbitone-induced rat liver microsomes.

Conclusion: Giving its safety and good predictive value the LTA test has very strong potential to be a useful diagnostic tool for ß-lactam-induced SSLR. The test procedure is relatively simple and not overly costly. Further studies including other drug classes are needed to evaluate the utility of the LTA test for SSLR due to other drugs.

Neuromuscular junction dysfunctions due to immune checkpoint inhibitors therapy: An analysis of FAERS data in the past 15 years

Introduction

The adverse effects of neuromuscular junction dysfunctions caused by immune checkpoint inhibitor (ICI) drugs have not been thoroughly assessed in the clinics.

Objective

To assess the neuromuscular junction dysfunctions in cancer patients with adverse events caused by ICI therapy by searching the Food and Drug Administration Adverse Event Reporting System (FAERS) database.

Methods

The FAERS data from January 2004 to December 2020 were collected to analyze the association between neuromuscular connection dysfunction and ICI use. Disproportionate analysis and Bayesian analysis were used to quantify the association between the neuromuscular junction dysfunctions and ICIs. The onset time and outcome of neuromuscular junction dysfunctions in different ICI regimens were also compared.

Results

Out of 88,617 adverse event reports, 557 neuromuscular junction dysfunction reports (0.63%) were analyzed. Marketed ICI drugs, including ipilimumab, nivolumab, pembrolizumab, atezolizumab, durvalumab, cemiplimab, avelumab, as well as their combinations, showed positive associations with four detection methods. Most of the adverse event reports were associated with the use of nivolumab (53.32%) and pembrolizumab (31.96%). However, nivolumab-related neuromuscular junction dysfunctions were similar with pembrolizumab (33.33% vs 33.14%, p &gt; 0.05). The onset time of neuromuscular junction dysfunctions showed no significant difference among different ICIs (p &gt; 0.05).

Conclusions

Analysis of FAERS data identified that over 30% (32.85%) of reports of neuromuscular junction dysfunctions resulted in death. Ongoing monitoring, risk evaluations, and further comparative studies of ICIs should be considered.

The effect of clinical pharmacists' intervention in adverse drug reaction reporting: a retrospective analysis with a 9-year interrupted time series

Background

In China, 85.4% of adverse drug reactions (ADRs) are spontaneously reported by healthcare facilities. As a result, many ADRs are not reported due to lack of mandatory reporting requirements. As healthcare professionals, clinical pharmacists (CPhs) serve as a bridge between clinical work and medication and ensure rational drug use. In China, A team of CPhs implemented an intervention for ADRs reporting, with the goal of improving the number of ADRs reports, the number of unreported ADRs, and the standardized reporting rate.

Methods

On June 01, 2015, a team of CPhs implemented an intervention for ADRs reporting at a Grade A, Class 3 hospital in China. The drug review catalogue (DRC) was used to screen physician orders for having visible symptoms of ADRs across departments, pooled the ADRs, and submitted them to the Center for Advanced Drug Monitoring (CNCAM). We retrospectively analysed the effect of a CPhs ADRs reporting intervention on the number of clinical ADRs reports, the number of unreported ADRs, and the standardized reporting rate over a 9-year period by interrupted time series (ITS). The method was implemented at the hospital on June 1, 2015, and a segmented regression model was used to analyse the data from January 1, 2010, to December 31, 2019.

Results

After the CPhs ADRs reporting intervention, the number of inpatient ADRs reports submitted to the CNCAM immediately increased by approximately 63 (62.658, P < 0.01) and then decreased by approximately 1 (0.701, P = 0.000151 < 0.01) per month afterward; the number of unreported ADRs was immediately reduced by approximately 44 (44.091, P < 0.01) and remained largely unchanged over time (P > 0.05); the standardized ADRs reporting rate per month immediately increased by 63.634% (P < 0.01) and remained largely unchanged over time (P > 0.05).

Conclusion

The CPhs ADRs reporting intervention had an immediate effect on improving ADRs reporting, which highlights the severity of ADRs underreporting in Chinese hospitals. The method is practical and should be used more widely in clinical practice. For example, the method can adjust and establish a DRC catalog that meets the actual situation of the implementing hospital based on the hospital's drug use habits and has the characteristics of good adaptability. However, it does have some limitations; for example, it may be difficult to detect early ADRs without visible symptoms.

Effects of the COVID-19 Pandemic on Pharmacovigilance Strategy, Systems and Processes of Large, Medium, and Small Companies: An Industry Survey

Purpose

The COVID-19 pandemic poses an unprecedented threat to global business relationships and dynamics. The pharmacovigilance function of pharmaceutical companies is particularly susceptible to changing external pressures because of its highly structured compliance activities. We conducted an industry-wide survey to provide insights on how the pharmacovigilance function responded to the challenges posed by the pandemic. We compared smaller companies and larger companies regarding impact on portfolios and operational activity metrics.

Methods

We conducted a survey through the Navitas Life Science annual benchmark of pvnet^TM, a network of large enterprise (LE) companies, and pvconnect^TM, a network of small and medium enterprise (SME) companies, using an online surveying tool during the first quarter of 2021. We collected information on pharmacovigilance activities, including quantitative measures of workload, costs, and key performance indicators, and qualitative data on the effects of the pandemic on product portfolios and operations.

Findings

Survey questions were posed to LE (pvnet) network members (n = 12) and SME (pvconnect) network members (n = 18) for the period from January 1 through December 31, 2020. The date of data collection was March 26, 2021. Descriptive median values of parameter metrics included the following: revenue ($28.4 billion for LE companies and $1.6 billion for SME companies), number of products (127 for LE companies and 19 for SME companies), and volume of individual case safety reports (391,000 for LE companies and 13,000 for SME companies). SME companies reported a greater impact on 2 survey categories, remote working and employee well-being, than did LE companies. However, LE companies reported a greater impact than did SME companies on all other survey categories: effect on strategic priorities, shift in product focus, workload changes, changes in sourcing model, effect on case reporting compliance, effect on business continuity, changes in pharmacovigilance technology strategy, impact of interactions with health authorities, effect on resource capacity, and impact on recruitment.

Implications

Four major themes emerge from this survey: (1) shift to remote working, (2) recognition of the impact on employee well-being, (3) shift in strategic priorities, and (4) newly recognized aspects of risk mitigation. The COVID-19 pandemic has had a marked effect on every aspect of pharmaceutical companies’ pharmacovigilance functions, although the effects appear to be different for LE companies than for SME companies.

Using Machine Learning for Pharmacovigilance: A Systematic Review

Pharmacovigilance is a science that involves the ongoing monitoring of adverse drug reactions to existing medicines. Traditional approaches in this field can be expensive and time-consuming. The application of natural language processing (NLP) to analyze user-generated content is hypothesized as an effective supplemental source of evidence. In this systematic review, a broad and multi-disciplinary literature search was conducted involving four databases. A total of 5318 publications were initially found. Studies were considered relevant if they reported on the application of NLP to understand user-generated text for pharmacovigilance. A total of 16 relevant publications were included in this systematic review. All studies were evaluated to have medium reliability and validity. For all types of drugs, 14 publications reported positive findings with respect to the identification of adverse drug reactions, providing consistent evidence that natural language processing can be used effectively and accurately on user-generated textual content that was published to the Internet to identify adverse drug reactions for the purpose of pharmacovigilance. The evidence presented in this review suggest that the analysis of textual data has the potential to complement the traditional system of pharmacovigilance.

Intelligent Telehealth in Pharmacovigilance: A Future Perspective

Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting in many adverse drug events being underreported or inaccurately reported. One challenge includes having access to large data sets from various sources including electronic health records and wearable medical devices. Artificial intelligence, including machine learning methods, such as natural language processing and deep learning, can detect and extract information about adverse drug events, thus automating the pharmacovigilance process and improving the surveillance of known and documented adverse drug events. In addition, with the increased demand for telehealth services, for managing both acute and chronic diseases, artificial intelligence methods can play a role in detecting and preventing adverse drug events. In this review, we discuss two use cases of how artificial intelligence methods may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.

The Importance of Direct Patient Reporting of Adverse Drug Reactions in the Safety Monitoring Process

All medicinal products authorized in the European Union are subjects of constant drug-safety monitoring processes. It is organized in a pharmacovigilance system that is designed to protect human health and life by the detection, analysis and prevention of adverse drug reactions (ADRs) and other drug-related problems. The main role of the aforementioned system is to collect and analyze adverse drug reaction reports. Legislation introduced several years ago allowed patients, their legal representatives and caregivers to report adverse drug reactions, which caused them to be an additional source of safety data. This paper presents the analysis of EudraVigilance data related to adverse drug reactions provided by patients, their representatives, as well as those obtained from healthcare professionals related to medicines which belong to M01A anti-inflammatory and antirheumatic products, a non-steroid group. The objective of the study was to identify the changes in the number and structure of adverse reaction reporting after the introduction of pharmacovigilance (PV) obligations in EU. A review of scientific literature was also conducted to assess the differences in adverse reactions reported by patients or their representatives and by healthcare professionals. We also identified other factors which, according to literature review, influenced the number of adverse reaction reports provided by patients. Analysis of data collected from the EudraVigilance showed that from 2011 to 2013 the number of reports made by patients and their caregivers increased by approx. 24 percentage points, and then, from 2014, it constituted around 30% of the total of reported reactions every year, so patient reporting is an important part of pharmacovigilance system and a source of drugs’ safety information throughout their use in healthcare practice. Additionally, there was no interrelationship between the seriousness of reported adverse reactions and the overall number of patient reports when compared to reports form healthcare professionals.

Pharmacosurveillance in Juvenile Idiopathic Arthritis

The advent of biologic disease-modifying antirheumatic drugs targeting specific cytokines or cell-cell interactions has dramatically changed the outlook of patients with juvenile idiopathic arthritis. However, safety concerns remain around the use of therapeutic agents for children with juvenile idiopathic arthritis. Foremost among these are the risks of serious infections and malignancy. This article provides an overview of methodologies for pharmacosurveillance in juvenile idiopathic arthritis, including spontaneous reporting systems and the use of diverse data sources, such as electronic health records, administrative claims, and clinical registries. The risks of infections and malignancies are then briefly reviewed.

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

Ophthalmic Solution Safety Profile: Active Surveillance of a Sodium Hyaluronate/Chondroitin Sulfate Combination in Peruvian Population

Background

Sodium hyaluronate/chondroitin sulfate fixed combination plays an essential role in the treatment of keratoconjunctivitis sicca, a multifactorial disease accompanied by ocular symptoms like alteration of the tear film. Despite low or no absorption of such drugs, these can cause secondary effects. An essential tool in the study of medication behavior is active pharmacovigilance. Unlike spontaneous reporting pharmacovigilance, this tool allows an appraisal of adverse drug reactions (ADRs)’ real incidence, a higher capacity to identify safety signals, the relationship with concomitant drugs and pathologies prevalent in the study population. This study aimed to evaluate the safety profile and identify and/or assess adverse reactions in an uncontrolled population.

Methods

Active pharmacovigilance by Drug Event Monitoring was performed. A total of 3 follow-up calls were made for 30 days for the identification of the ADRs, tolerability (ADR severity, seriousness, long term sequelae, and duration) and the possible risks (safety signals, medical interactions) of sodium hyaluronate and chondroitin sulfate (HUM).

Results

Thirty-five ADRs were identified in the 212 patients included in the study (0.17 ADR/patient). The 35 ADRs were classified into 3 System Organ Class (SOC) groups: general disorders and administration site conditions (74.2%), eye disorders (22.9%), and nervous system disorders (2.9%); and 4 Preferred Term (PT) groups: burning sensation (74.2%), followed by blurred vision (20%), ocular pain (2.9%) and headache (2.9%). All the ADRs were categorized as mild and not serious. No statistically significant differences were found in concomitantly medications, posology and age groups.

Conclusion

Good tolerability to the solution was identified, with a low incidence of ADRs. Just the same, all the associated ADRs were consistent with the information found in HUM’s physicochemical profile and the physiopathology of DED. No unknown risks were identified, reinforcing HUM’s safety profile.

Drug Safety in Translational Paediatric Research: Practical Points to Consider for Paediatric Safety Profiling and Protocol Development: A Scoping Review

Translational paediatric drug development includes the exchange between basic, clinical and population-based research to improve the health of children. This includes the assessment of treatment related risks and their management. The objectives of this scoping review were to search and summarise the literature for practical guidance on how to establish a paediatric safety specification and its integration into a paediatric protocol. PubMed, Embase, Web of Science, and websites of regulatory authorities and learned societies were searched (up to 31 December 2020). Retrieved citations were screened and full texts reviewed where applicable. A total of 3480 publications were retrieved. No article was identified providing practical guidance. An introduction to the practical aspects of paediatric safety profiling and protocol development is provided by combining health authority and learned society guidelines with the specifics of paediatric research. The paediatric safety specification informs paediatric protocol development by, for example, highlighting the need for a pharmacokinetic study prior to a paediatric trial. It also informs safety related protocol sections such as exclusion criteria, safety monitoring and risk management. In conclusion, safety related protocol sections require an understanding of the paediatric safety specification. Safety data from carefully planned paediatric research provide valuable information for children, parents and healthcare providers.

Drug safety in multiple sclerosis: From reporting to signal detection and benefit-risk management

BACKGROUND

Pharmacovigilance (PV) rules emerged in the late 60s-early 70s. Since that time, the World Health Organization Center for International Drug Monitoring carries out the corresponding tasks. Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system that generally starts in young adults between 20 and 40 years of age. Over the last 25 years, MS patients have benefited from the development of a plethora of disease modifying drugs (DMD). These changes in the therapeutic armamentarium have been associated with some serious adverse reactions challenging health authorities and neurologists involved in treatment and care for MS patients.

METHODS

The present review aims to describe, for MS DMDs, how adverse drug reactions are reported during clinical trials and the post-marketing period and how important signal detection and benefit-risk management have been in this disease until now. Several examples are reported to illustrate the different steps of PV processes.

CONCLUSION

Improvement of the PV system procedures has led to significant progress in the detection of signals, allowing better assessment of the benefit-risk balance and the implementation of risk management plans for MS treatments. The involvement of neurologists is essential to improve knowledge on the benefit-risk balance of these drugs. In addition, adverse drug reactions reporting by persons with MS should be encouraged.

The 2011–2020 Trends of Data-Driven Approaches in Medical Informatics for Active Pharmacovigilance

Pharmacovigilance, the scientific discipline pertaining to drug safety, has been studied extensively and is progressing continuously. In this field, medical informatics techniques and interpretation play important roles, and appropriate approaches are required. In this study, we investigated and analyzed the trends of pharmacovigilance systems, especially the data collection, detection, assessment, and monitoring processes. We used PubMed to collect papers on pharmacovigilance published over the past 10 years, and analyzed a total of 40 significant papers to determine the characteristics of the databases and data analysis methods used to identify drug safety indicators. Through systematic reviews, we identified the difficulty of standardizing data and terminology and establishing an adverse drug reactions (ADR) evaluation system in pharmacovigilance, and their corresponding implications. We found that appropriate methods and guidelines for active pharmacovigilance using medical big data are still required and should continue to be developed.

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.

Adverse Drug Reaction Case Safety Practices in Large Biopharmaceutical Organizations from 2007 to 2017: An Industry Survey

INTRODUCTION

Drug safety remains a top global public health concern. An increase in the number of data sources available has increased the complexity of pharmacovigilance operations, so the US FDA has created draft guidance focusing on optimizing drug safety data for well-characterized medicines. However, to date, no data demonstrating changes in reports have been presented.

OBJECTIVES

This study provided data assessing changes in individual case safety reports (ICSRs) and aggregate reports (ARs) for large biopharmaceutical companies from 2007 to 2017. This study also evaluated current trends on the use of advanced machine and deep learning in order to process all data captured for ICSRs as well as opinions from industry thought leaders on creating a sustainable case-processing operation.

METHODOLOGY

Using data captured from Navitas Life Science's annual pvnet^® benchmark, we calculated workload indicators characterizing pharmacovigilance operations for large biopharmaceutical organizations. Workload indicators included the number of ICSRs by organization, the number of ARs, and the number and types of data sources used. We also conducted structured in-depth interviews with seven biopharmaceutical executives to discover the reasons for changes in workload indicators across time as well as current strategies for increasing efficiencies in drug safety reporting.

RESULTS

The median number of ICSRs increased from 84,960 cases in 2007 to over 200,000 cases in 2017; this increase was largely attributable to an increase in both nonserious cases and follow-up cases. Member companies reported using 12 ± 3 data sources for case identification. The number of ARs also increased from a median of 70 reports in 2007 to 258 reports in 2017. To address these increases, 61% of the biopharmaceutical organizations we surveyed planned to adopt machine learning for full ICSR processing; however, as of 2018, none of the organizations surveyed had mechanisms in place.

CONCLUSION

This study demonstrated that pharmacovigilance departments are currently burdened by ever-increasing case volumes. With increased guidance from regulatory agencies, as well as improvements in artificial intelligence and natural language processing, biopharmaceutical organizations must determine the most resource-efficient and sustainable methods to process the growing volume of cases.

Signal Management in Pharmacovigilance: A Review of Activities and Case Studies

PURPOSE

After nearly 12 decades of pharmaceutical catastrophes and the associated groundbreaking regulatory innovations, pharmacovigilance has come down to us in the present day as 3 interlocking core disciplines: case management, signal management, and benefit-risk management. This review provides a state-of-the-art introduction to the great variety of sources of safety information, both dependent on and independent of the Individual Case Safety Report (ICSR), and explains how this content undergoes management-system processes with globally accepted definitions, standards, and structures that make possible the ongoing safe use of a pharmaceutical product throughout its lifecycle. This occurs in the context of: (1) new products coming to market with new risks for drug-drug interactions, and (2) new global threats to safe manufacturing and distribution.

METHODS

This narrative review, reflective of the author's experience, uses a large-frame system of signal management developed by the Council for International Organizations of Medical Sciences VIII Working Group and modified by the author to include governance. A key feature of the review is the regular inclusion of relevant case studies to provide a backdrop of the unexpected, with resulting tragic outcomes, to the ever-evolving regulatory landscape.

FINDINGS

Regarding content, beyond the commonly appreciated sources of safety information that find their way into ICSRs are non-ICSR-based sources, including preclinical data, manufacturing data, findings from subject-matter experts who participate on data-monitoring committees, outside expert panels, advocacy groups, and independent investigator studies. Regarding process, it is important to recognize that governance is crucial in the effective conduct of signal management, in that subject-matter experts are essential to the scientific and medical aspects of decision making, and business and policy executives are essential in determining the final courses of action, as these decisions have implications for the company.

IMPLICATIONS

Signal management is an integral part of pharmacovigilance practices that strive to obtain all of the information necessary for maintaining the safety profiles of a company's pharmaceutical and biological products, to support favorable benefit-risk balances, and to ensure safe use by health care providers and their patients.

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.

Adverse drug reactions in drug information databases: does presentation affect interpretation?

Objective

Formatting of adverse drug reaction (ADR) information differs among drug information (DI) resources and may impact clinical decision-making. The objective of this study was to determine whether ADR formatting impacts adverse event interpretation by pharmacy practitioners and students.

Methods

Participants were randomized to receive ADR information in a comparative quantitative (CQUANT), noncomparative quantitative (NQUANT), or noncomparative qualitative (NQUAL) format to interpret 3 clinical vignettes. Vignettes involved patients presenting with adverse events that varied in the extent to which they were associated with a medication. The primary outcome was interpretation of the likelihood of medication-induced adverse events on a 10-point Likert scale. Lower scoring on likelihood (i.e., ADR deemed unlikely) reflected more appropriate interpretation. Linear regression was performed to analyze the effects of ADR information format on the primary outcome.

Results

A total of 108 participants completed the study (39 students and 69 pharmacists). Overall, the CQUANT group had the lowest average likelihood compared to NQUAL (4.0 versus 5.4; p<0.01) and NQUANT (4.0 versus 4.9; p=0.016) groups. There was no difference between NQUAL and NQUANT groups (5.4 versus 4.9; p=0.14). In the final model, at least 2 years of postgraduate training (-1.1; 95% CI: -1.8 to -0.3; p<0.01) and CQUANT formatting (-1.3; 95% CI: -0.9 to -1.7; p<0.01) were associated with reduced likelihood.

Conclusions

Formatting impacts pharmacists' and pharmacy students' interpretation of ADR information. CQUANT formatting and at least two years of postgraduate training improved interpretation of adverse events.

Pharmacovigilance in perspective: drug withdrawals, data mining and policy implications

Considering that marketed drugs are not free from side effects, many countries have initiated pharmacovigilance programs. These initiatives have provided countries with methods of detection and prevention of adverse drug reactions at an earlier stage, thus preventing harm occurring in the larger population. In this review, examples of drug withdrawals due to effective pharmacovigilance programs have been provided with details. In addition, information concerning data mining in pharmacovigilance, an effective method to assess pharmacoepidemiologic data and detecting signals for rare and uncommon side effects, is also examined, which is a method synchronized with information technology and advanced electronic tools. The importance of policy framework in relation to pharmacovigilance is discussed in detail, and country experiences upon implementation of pharmacovigilance policies is highlighted.