Drug Safety最新文献

In the pharmaceutical industry, due diligence (DD) is a critical, cross-functional process used to evaluate the scientific and regulatory viability of products, particularly during in-licensing or acquisition. Among the various dimensions assessed, safety evaluation plays a pivotal role in determining whether a product is likely to achieve regulatory approval, maintain a favourable benefit-risk balance, and support sustainable market access. This article focuses on the unique role of pharmacovigilance (PV) and safety experts in the DD process. It outlines the key safety-related questions that must be addressed, highlights potential red flags-such as organ-specific toxicities, labelling liabilities, or risk management burdens-and provides practical considerations for evaluating the robustness of the safety data package. Drawing on extensive industry experience and regulatory precedents, this manuscript offers structured guidance for an area where no formal framework exists. It emphasizes the importance of forecasting the likelihood of achieving a positive benefit-risk profile and identifying foreseeable safety-related barriers-ranging from boxed warnings to withdrawal risk-that could delay approval or diminish product value. By proposing a systematic approach to safety DD, including a playbook and an inclusive checklist with colour-coded categorization framework, this paper aims to support more informed, proactive, and risk-calibrated decision making in pharmaceutical transactions.

Background and objective: Several systematic reviews and meta-analyses have been published with conflicting results on the risk of herpes zoster after coronavirus disease 2019 (COVID-19) vaccination. We aimed to study the risk of herpes zoster after COVID-19 vaccination using electronic health record data of general practices, from a large cohort in the Netherlands.

Methods: Persons aged ≥ 12 years who received at least one COVID-19 vaccination and were registered in the general practice databases of PHARMO and Nivel Primary Care Database were included. This study used a self-controlled design comparing the risk of herpes zoster in the risk period (28 days after COVID-19 vaccination) with the control period. Poisson regression was used to calculate incidence rate ratios, adjusting for severe acute respiratory syndrome coronavirus 2 infection.

Results: There were 2,098,683 COVID-19 vaccinated persons aged ≥ 12 years included, of whom 1,058,646 (50.4%) were female. An increased risk for herpes zoster was found after all the doses grouped together and the third dose of all COVID-19 vaccination (adjusted incidence rate ratio: all doses 1.07, 95% confidence interval [CI] 1.02-1.13 and third dose 1.21, 95% CI 1.05-1.38). After stratification on vaccine type, all doses and the third dose of messenger RNA vaccination (adjusted incidence rate ratio: all doses 1.06, 95% CI 1.00-1.12 and third dose 1.21, 95% CI 1.05-1.40) showed an increased risk.

Conclusions: Our study showed a slight increased risk of herpes zoster when taking into account all doses and all types of vaccines. After stratification on vaccine type, no increased risk of herpes zoster after the primary vaccination series and a slightly elevated risk after the third/booster vaccination with a messenger RNA vaccine were found.

Background: Many adverse drug reactions (ADRs) to dermatological drugs may be underrecognized due to limitations in traditional surveillance. Systematic, hypothesis-free screening for such ADRs using real-world data is an underutilized approach in dermatology.

Objective: The aim was to systematically screen commonly used dermatological drugs for potential unknown ADR signals using nationwide Danish health register data and to evaluate sequence symmetry analysis (SSA) as an epidemiological screening method in pharmacovigilance. This evaluation focuses on identifying key signals for dedicated follow-up studies, not on an exhaustive analysis of all potential associations.

Methods: A nationwide, register-based, hypothesis-free screening study using Danish national health registers was conducted. The study cohort comprised 5,877,711 Danish residents prescribed dermatological drugs or relevant immunosuppressants linked to a dermatological indication between 1996 and 2022. Data were analyzed from 1995 to 2024. Exposures were the first dispensation of included dermatological drugs. The primary outcome measure was the trend-adjusted sequence ratio (SR), an estimate of the incidence rate ratio for rare events, with 95% confidence intervals (CIs), for incident drug-drug and drug-diagnosis pairs within ±12-month windows of exposure initiation. To assess directionality, supplementary case-crossover (CCO) analyses were performed on top-ranked signals, estimating odds ratios (ORs) with 95% CIs.

Results: The screening of 22.5 million incident exposure prescriptions yielded 4010 drug-drug and 22,234 drug-diagnosis pairs. After filtering and review, several potential unknown ADR signals were identified and prioritized. Signals were manually reviewed and categorized by clinical experts to identify plausible novel ADRs. Notable associations (adjusted SR [95% CI]; CCO OR [95% CI]) included isotretinoin with systemic corticosteroids (1.44 [1.35-1.53]; 1.78 [1.61-1.98]) and hemorrhoid treatments (1.58 [1.49-1.68]; 1.83 [1.68-1.98]); azathioprine with bone-modifying drugs (1.42 [1.33-1.53]; 1.57 [1.36-1.81]); terbinafine with lipid-lowering therapy (1.04 [1.01-1.08]; 1.14 [1.07-1.20]) and vitamin B12/folate use (1.20 [1.14-1.26]; 1.12 [1.02-1.22]); and clobetasol with atrial fibrillation/flutter (1.11 [1.06-1.17]; 1.07 [1.00-1.14]).

Conclusions: Systematic hypothesis-free screening using SSA on nationwide real-world data can effectively identify potential unknown ADRs for dermatological drugs. The specific signals found in this study potentially have clinical implications and warrant further targeted investigations to support causality. This approach supports the implementation of routine real-world data screening to supplement traditional pharmacovigilance.

Chimeric antigen receptor T-cell (CAR-T) therapy is a rapidly expanding key therapeutic category, originally pioneered for haematological malignancies, now being developed into treatments for solid tumours and non-malignant immune-mediated conditions. Chimeric antigen receptor T-cell therapies have some relatively unique toxicities which can affect the liver, in addition to potential drug-induced liver injury and hepatitis B virus reactivation. This manuscript was developed by the IQ Consortium (International Consortium for Innovation and Quality in Pharmaceutical Development) Drug-induced Liver Injury (DILI) Initiative that consists of members from 17 pharmaceutical companies, in collaboration with academic and regulatory DILI experts. The aim was to produce a comprehensive guide to summarise the hepatic effects of CAR-T, and to propose an approach to the investigation of liver test changes. The clinical characteristics of liver test changes in association with cytokine release syndrome and immune-effector cell haemophagocytic lymphohistiocytosis are described, to enable these anticipated hepatic effects to be distinguished from other causes of abnormal liver tests. The frequency and timing of many primary and secondary liver conditions that may present after CAR-T therapy are described. This review provides the first detailed description of both anticipated and unpredictable hepatic effects of CAR-T cell therapies and is intended to assist in the future characterisation of hepatic effects of CAR-T therapies as programmes move into areas with a different benefit/risk profile, such as autoimmune or other non-oncology indications.

Observed versus expected (O/E) analyses have been used in an unprecedented scale for the safety monitoring of the COVID-19 mass vaccination. The extent of their usage changed its nature, which consisted of a mixture of medical expertise and epidemiology, into something more algorithmic and automated. By doing so, the observed versus expected analysis became closer to disproportionality analysis (DPA), which is also a type of observed versus expected analysis that differs in the way the expected is calculated. A qualitative assessment of the strengths and limitations of both methods concludes that the algorithmic O/E is more likely to underestimate under-reporting, is more likely to be sensitive to asymmetrical differences in the definition of the condition of interest, and is more dependent on a greater variety of data sources or medical knowledge that might not be accurate for emerging safety issues (exposure, background incidence rate, and risk window). Provided some adjustment (stratification and/or subgrouping) of the routine disproportionality into a targeted disproportionality occurs, which would account for the epidemiological specifics of the vaccine and event-of-interest, the targeted DPA has the potential to be promoted from a signal detection method into a signal evaluation method that could advantageously replace the algorithmic O/E analysis. Research on the setup of a sensitivity analysis framework integrating several standardized choices of disproportionality settings, along with measures (qualitative or quantitative) of the biases for each choice, could be more beneficial for the pharmacovigilance field than studies designed to estimate the background incidence rates of adverse events of special interest for the sole purpose of being used in O/E analyses.

Background: Affective disorders, particularly depression, are common among women of childbearing age, and pregnancy often exacerbates symptoms. Antidepressants are often required for treatment, but adherence during pregnancy is variable. Although some studies suggest potential risks to the foetus, many cannot rule out confounding by indication. In this context, understanding real-world patterns of antidepressant prescription and adherence during pregnancy is essential to inform clinical practice and ensure adequate mental healthcare.

Objective: The aim of the present study was to characterise the use of antidepressants in a cohort of pregnant women using electronic health records.

Methods: This observational cohort drug-utilisation study assessed antidepressant prescription patterns, adherence and persistence among pregnant women using data from the SIDIAP (Information System for the Development of Research in Primary Care) database in Catalonia from January 2011 to June 2020.

Results: Among 99,605 pregnancies, 14.9% involved antidepressant prescriptions, but only 5.8% of these were collected from pharmacies. The median pregnancy duration was 38.4 weeks, and the median maternal age was 33.5 years. Anxiety was the most common health issue associated with an antidepressant prescription. Paroxetine was the most frequently prescribed antidepressant, although sertraline usage increased over time. Antidepressant prescriptions and adherence decreased during pregnancy, with an increase in the postpartum period. About 11.6% of pregnancies involved a concurrent prescription of another antidepressant, and 29.2% of women resumed antidepressant use after pregnancy. Women who initiated antidepressants during pregnancy were more likely to persist with treatment than those with pre-existing prescriptions.

Conclusions: Our study describes antidepressant use during pregnancy in Catalonia. It is remarkable that there is a notable gap between antidepressant prescriptions and dispensations. Given the risks of untreated maternal depression, strengthening primary care with adequate resources and personalised support is essential for improving perinatal mental healthcare.

Background: Understanding changes over time in the quantity and characteristics of reports submitted to pharmacovigilance centres is crucial for accurately interpreting safety signals associated with exposure during pregnancy.

Objective: We aimed to assess temporal changes in the outcome measures for signal detection, specifically the number and clustering of reported adverse events concerning maternal valproate exposure and neurodevelopmental outcomes in offspring.

Methods: An observational study using VigiBase analysed changes in the number of reports and event clustering related to neurodevelopmental outcomes in offspring following valproate exposure during pregnancy. Reports from the start of VigiBase till 3 April, 2023 were identified using the VigiBase pregnancy algorithm. Time trend graphs illustrated reporting behavioural changes, with particular focus on the impact of major scientific publications and regulatory decisions. Report clusters, identified by the vigiGroup method, were randomised and independently reviewed by three qualified reviewers for clinical relevance to neurodevelopmental outcomes, morphological disorders or other entities.

Results: Over time, an increase in reports mentioning neurodevelopmental outcomes and a more diverse pattern of adverse events for valproate has been reported. An increase in the number of reports following key publications and international regulatory guidelines was visible.

Conclusions: Our study revealed an increase over time in reporting and awareness of neurodevelopmental outcomes and valproate exposure during pregnancy, following important publications and regulatory decisions. However, the extent to which these developments contributed to the observed increase remains unclear.