Development and Implementation of an Online Global Pharmacovigilance Certificate Program During the COVID-19 Pandemic.

Pharmacovigilance plays a lifesaving role in the practice of medicine. In 2021, during the Coronavirus Infectious Disease 2019 (COVID-19) pandemic, Loyola University Chicago launched a graduate-level Pharmacovigilance Certificate Program (PV-CERT) and a pre-professional non-graduate Pharmacovigilance Certificate Course (EPEC-PV), to provide students a comprehensive and contemporary understanding of the principles and practices of pharmacovigilance. Formal training in pharmacovigilance through this course provided a structured understanding of how safety data are generated through clinical trials and from real-world evidence as well as the regulatory environment in which data are monitored and interpreted. Pharmacovigilance training is of critical importance, especially during the COVID-19 pandemic, during which several drugs were re-purposed for the management of various stages of COVID-19 without conventional safety data. Moreover, the safety of currently-used vaccines is of concern in some populations. Although anticoagulants and antithrombotic medications are crucial in the management of COVID-19, a clear pharmacovigilance program on their use in this indication is not established. As the century progresses, new diseases and infectious agents will require novel therapies for which the evaluation of benefits versus risks will be as essential as it has been for the current COVID-19 pandemic. As such, the Loyola course and accompanying programs on pharmacovigilance will play a key role in educating the next generation of professionals in pursuing careers in the development of therapies that ultimately improve patient outcomes while maintaining rigorous safety standards.

Risk Minimization of Antibody-Drug Conjugates in Oncology: A Review.

Antibody-drug conjugates (ADCs) are new treatment options for certain cancers, especially those in advanced states with limited treatment options. Their unique design provides targeted therapy with toxins that otherwise would not be available, but they manifest toxicities that require risk minimization interventions to optimize their tolerability. We summarize selected toxicities for ADCs that have been approved through the end of 2020 and three investigational ADCs, which include both payload and linker, as described in the US Prescribing Information, the European Summary of Product Characteristics, and study protocols. These toxicities include peripheral neuropathy; pulmonary, skin, hepatic, and ocular toxicities; hyperglycemia; left ventricular dysfunction; and fluid-related events. We also review the risk minimization approaches to managing these toxicities as described in the product labels and study protocols. Our general observation suggests that the selected toxicities of the approved ADCs are primarily associated with off-target effects of the drug payloads. We also observed that the risk minimization approaches used to manage the selected toxicities are similar across product labels and study protocols. ADCs provide a unique treatment approach that is currently focused on advanced or refractory cancers. The risk minimization approaches for the selected toxicities for the approved ADCs per product label, or the study protocol for those in clinical investigation, are similar to those of standard chemotherapy agents and other pharmaceutical agents for the treatment of advanced malignancies. These risk minimization measures align with standard medical practice and are likely familiar to and feasible for physicians who prescribe for, and to other healthcare practitioners who care for, patients treated with ADCs.

Pharmacoepidemiologic Evaluation of Birth Defects from Health-Related Postings in Social Media During Pregnancy.

INTRODUCTION: Adverse effects of medications taken during pregnancy are traditionally studied through post-marketing pregnancy registries, which have limitations. Social media data may be an alternative data source for pregnancy surveillance studies. OBJECTIVE: The objective of this study was to assess the feasibility of using social media data as an alternative source for pregnancy surveillance for regulatory decision making. METHODS: We created an automated method to identify Twitter accounts of pregnant women. We identified 196 pregnant women with a mention of a birth defect in relation to their baby and 196 without a mention of a birth defect in relation to their baby. We extracted information on pregnancy and maternal demographics, medication intake and timing, and birth defects. RESULTS: Although often incomplete, we extracted data for the majority of the pregnancies. Among women that reported birth defects, 35% reported taking one or more medications during pregnancy compared with 17% of controls. After accounting for age, race, and place of residence, a higher medication intake was observed in women who reported birth defects. The rate of birth defects in the pregnancy cohort was lower (0.44%) compared with the rate in the general population (3%). CONCLUSIONS: Twitter data capture information on medication intake and birth defects; however, the information obtained cannot replace pregnancy registries at this time. Development of improved methods to automatically extract and annotate social media data may increase their value to support regulatory decision making regarding pregnancy outcomes in women using medications during their pregnancies.

An Alternative to Disproportionality: A Frequency-Based Method for Pharmacovigilance Data Mining.

BACKGROUND: Safety surveillance relies on mining of large pharmacovigilance (PV) databases to generate insights regarding the safe use of pharmaceutical products. The predominant approach to PV data mining involves computation of disproportionality scores for drug-adverse event (drug-AE) pairs. However, this approach requires a database to be sufficiently large, sufficiently diverse for the analysis to be reliably sensitive and specific, and fails to consider the particular safety profile of a product. OBJECTIVE: The present study proposes and tests a novel, frequency-based approach to PV data mining that (1) leverages product knowledge and historical drug-AE trends and (2) imposes no requirement for the size and diversity of the database to which it is applied. METHOD: A focus group of physicians and scientists was convened to identify quantitative characteristics of data trends that they consider informative when reviewing counts of adverse events for products under surveillance. Feedback was transferred into a series of decision rules that, when applied to adverse event counts, identifies adverse event trends that are classified as Continuing Trend, Emerging Trend, or No Trend. Regression analyses are completed to verify the presence of a linear trend; and categorical measures of association completed to compare this frequency-based approach to disproportionality scores in a simulated database. RESULTS: A significant, positive linear trend is present for the Continuing Trend and Emerging Trend categories ( P < .0001). There is a significant association between trend categorizations and disproportionality scores ( P < .0001). CONCLUSION: The proposed alternative frequency-based method for PV data mining would be useful where disproportionalities scores are not appropriate. Additionally, this method may be useful in conjunction with disproportionality scores, where appropriate, highlighting adverse events that are both reported disproportionately and have increasing trends.

Best-practices for the design and development of prescription medication information: A systematic review.

OBJECTIVE: To present evidence supporting best-practices for prescription drug labeling and educational materials. METHODS: Articles were selected from three online databases (PubMed, Embase, CINAHL). Eligible manuscripts were: 1) English-language, 2) randomized, controlled trials, and 3) focused on improving prescription drug labeling practices. RESULTS: Forty-nine articles were reviewed, and included both regulated label materials and pharmacy or health systems-generated tools. Best-practices included use of plain language principles, typographic cues, quantitative descriptors, and standardized formats, when applicable. Common outcomes included preference and comprehension, while few studies examined actual medication use (e.g. adherence, harms) or clinical health outcomes. Approximately half of studies directly engaged patients' perspectives in intervention development, which may have helped increase tool effectiveness. CONCLUSIONS: Several best practices were apparent in the literature, particularly for written materials and pharmacy-generated container labeling. Design principles for supplemental instructions and multimedia tools were less cohesive, albeit less researched. The impact of patient involvement in tool design is promising, though requiring further study. PRACTICE IMPLICATIONS: Definitive studies to inform practice standards on how to best communicate medication information to consumers are needed, especially as communication modalities continue to evolve. Increased research on if and how to incorporate patient-centered decision-making into the development process should be considered.

The future of safety science is happening now: The modernization of the benefit-risk paradigm.

The future of safety science is happening now and has the potential to improve patient outcomes through an evolving approach to benefit-risk assessment. Three building blocks for the future of safety science, cognitive and behavioral systems, medical assessment, and data science, individually and collaboratively advance and modernize the benefit-risk paradigm. Incorporating the patient perspective and patient experiences will help identify tools that are useful in real-world practice. Medical assessment teams will bring together the study of toxicity and toxicogenomics, biomarkers, and special populations to personalize the benefit-risk profile. Personalized benefit-risk profiles for patients will help improve outcomes. Data science and related quantitative sciences such as safety statistics, database integration, technology, and epidemiology will provide new approaches and tools for analysis of safety data as well as more rapid access to insights that benefit patients.

Progressive multifocal leukoencephalopathy after natalizumab discontinuation.

OBJECTIVE: To identify cases of laboratory- or biopsy-confirmed progressive multifocal leukoencephalopathy (PML) in patients with multiple sclerosis (MS) who previously discontinued natalizumab (NTZ) for reasons unrelated to suspected or proven PML and assess PML risk factors in these cases. METHODS: We searched the US Food and Drug Administration Adverse Event Reporting System and MEDLINE for reports submitted from 2006 to 2012 of laboratory-confirmed PML with symptom onset ≥30 days following NTZ withdrawal. We only analyzed cases where NTZ discontinuation was unrelated to suspected PML. RESULTS: Seventeen patients discontinued NTZ for reasons unrelated to PML but were subsequently diagnosed with the disease. The median NTZ duration was 47 monthly doses (range = 9-59 doses). All patients presented with compatible clinical symptoms within 6 months following withdrawal, and PML was confirmed by brain biopsy or by identifying JC virus in the cerebrospinal fluid by polymerase chain reaction. Immune reconstitution inflammatory syndrome (IRIS) was reported in 11 patients. Eleven patients (65%) received new MS treatments between NTZ discontinuation and PML confirmation. No deaths were reported. At NTZ withdrawal, 16 patients (94%) had ≥1 PML risk factor, including NTZ duration ≥2 years (n = 13), prior immunosuppressive agents (n = 8), and reported anti-JC virus seropositivity (n = 13). INTERPRETATION: NTZ-treated patients presenting clinically with PML within 6 months after NTZ withdrawal frequently have pre-existing PML risk factors. Clinicians need heightened awareness for new onset PML, IRIS, and MS relapse in evaluating neurological decline following NTZ discontinuation. Ann Neurol 2014;75:108-115.

Central nervous system herpes simplex and varicella zoster virus infections in natalizumab-treated patients.

We report on 20 natalizumab-treated patients with multiple sclerosis who developed laboratory-confirmed central nervous system (CNS) herpesvirus infections. In addition to progressive multifocal leukoencephalopathy, other CNS opportunistic infections have been rarely reported during natalizumab treatment. We encourage heightened awareness due to the risk for serious outcomes.

Adverse events with disease modifying antirheumatic drugs (DMARD): a cohort study of leflunomide compared with other DMARD.

OBJECTIVE: To determine and compare the incidence of serious adverse events (AE) during treatment of rheumatoid arthritis (RA) with disease modifying antirheumatic drugs (DMARD), focusing on leflunomide (LEF). METHODS: A retrospective cohort study of a large US insurance claims database was performed. Study groups were patients with RA classified by DMARD exposure as either no-DMARD therapy, single-agent DMARD (monotherapy), or combination-DMARD therapy. Specific DMARD examined were leflunomide (LEF) and methotrexate (MTX), compared to other DMARD (penicillamine, hydroxychloroquine, sulfasalazine, gold, etanercept, infliximab) and no DMARD (nonsteroidal antiinflammatory drugs, COX-2 inhibitors). All AE reported were considered endpoints; primary endpoints included hepatic, dermatologic, hematologic, infectious, respiratory, hypertension, and pancreatitis AE. RESULTS: The 40,594 RA patients of the study period (September 1998 to December 2000) accumulated 83,143 person-years (PY) of followup. Followup for each of the groups was: DMARD-monotherapy, 46,054 PY (55% of total); combination-DMARD, 25,830 PY (14%); and no-DMARD, 11,259 PY (14%). The incidence rate of all AE combined was significantly lower for LEF monotherapy (94 events/1000 PY) than MTX (145 events/1000 PY), other DMARD (143 events/1000 PY), or no DMARD (383 events/1000 PY) (p < 0.001 for all comparisons). The "all-AE" rates during combination therapy with LEF + MTX (43/1000 PY) and LEF + other DMARD (59/1000 PY) were lower than the "all-AE" rate for DMARD + MTX (70/1000 PY; p = 0.002). LEF monotherapy had the lowest rate of hepatic events in the DMARD monotherapy groups. CONCLUSION: The rates of AE in the LEF group, alone and combined with MTX, were generally lower than or comparable to the AE rates seen with MTX and other agents.