Therapeutic innovation & regulatory science最新文献

Background: In Japan, prescription drug labeling has transitioned to a new structured format aimed at improving clarity and consistency, with full implementation in March 2024. Abnormal kidney function, a critical determinant of drug safety, necessitates clear and consistent contraindication labeling. However, current labeling practices have not been comprehensively evaluated.

Objective: To systematically assess how kidney-related contraindications are described in Japanese package inserts under the new labeling format.

Methods: We reviewed all electronically available prescription drug package inserts as of October 1, 2024. Using 20 kidney-related keywords, we extracted and analyzed statements in Sect. 2 ("Contraindications"), categorizing them into four domains: type of impairment, severity, disease progression, and quantitative criteria. Additionally, a network diagram of co-occurring terms was developed to illustrate the consistency and diversity of terminology.

Results: A total of 233 kidney-related contraindication statements were identified across 182 pharmaceutical ingredients. Type of impairment was mentioned in 81.5%, severity in 54.9%, and quantitative criteria in 38.2%. However, the terminology and threshold values used were inconsistent. Terms such as "severe abnormal kidney function" were used without standardized definitions, and quantitative parameters (e.g., creatinine clearance, estimated glomerular filtration rate) varied across products.

Conclusion: Despite regulatory efforts to enhance labeling structure, kidney-related contraindication descriptions in Japan remain variable and lack standardization. These inconsistencies may hinder safe prescribing practices and the integration of labeling into clinical decision support systems. Adoption of internationally harmonized terminology, such as KDIGO staging, and clearer regulatory guidance may improve the clinical utility of drug labeling.

Background: The World Health Organization (WHO) developed the WHO Global Benchmarking Tool (GBT) to assess and benchmark the drug regulatory systems and practices in national medicines regulatory authorities (NMRAs). The objective of the study was to identify strengths and opportunities for improvement by comparing the regulatory performance of the NMRAs in Egypt, Ghana, Nigeria, South Africa, Tanzania and Zimbabwe, all which have attained maturity level 3 status for medicines and /or vaccines, in order to enhance regulatory review processes and patients' access to medicines and/or vaccines.

Methods: The NMRAs selected for the study completed a questionnaire that collected data and metrics that facilitated comparative studies among the NMRAs.

Results: The comparative study showed that similarities among these authorities also translated into their strengths. The study revealed that the human resource capacity in African NMRAs is inadequate to fully execute regulatory mandates. Review process map comparison revealed the important observation that these NMRAs conducted labelling review early in the review process rather than in the latter stages of the process.

Conclusion: The study has identified the regulatory best practices that led to the NMRAs achieving WHO GBT maturity level 3. The African Medicines Agency should engage these maturity level-3 NMRAs to explore ways of benefiting from their experience and resources. It is hoped that through such engagement, the NMRAs will be encouraged to further develop their capacity to help the AMA to achieve its mandate. Additionally, by addressing the identified gaps and recommendations in the study these NMRAs can achieve WHO GBT maturity level 4 whilst NMRAs who have not yet reached GBT maturity level 3 can also benefit from this study in order to reach higher maturity levels.

Background: Patients often have suboptimal understanding of informed consent in clinical trials, impeding their ability to make informed decisions about participation. Additionally, translating complex informed consent information from English into other languages can introduce new areas of misunderstanding for patients. This qualitative study examined how English- and Spanish-speakers understood and perceived a complex clinical informed consent form.

Methods: We tested an informed consent form for a clinical trial on a gynecological medication with women who represented the study population. We conducted 18 semi-structured interviews with English- (n = 9) and Spanish-speaking (n = 9) participants to explore areas of misunderstanding, concerns, and preferences. With Spanish-speakers, we tested two professionally translated versions of the informed consent form-one generated by general translators and the second by translators with medical and scientific expertise. We used thematic analysis to explore patterns in the data.

Results: Five themes were common across both English- and Spanish-speakers: difficulty with medical jargon; unfamiliarity with the drug development and testing process; desire for understandable numeric information; aversion to uncertain or conflicting evidence; and affective reactions to information. Spanish-speakers generally preferred language from the medical translation over the general version, though this preference was not consistent.

Conclusions: Findings underscore the importance of pretesting informed consent materials to ensure that they are understandable, avoid difficult language, and do not evoke negative emotions or reactions, particularly when communicating about risk and uncertainty. Findings also suggest using a combination of translation approaches, when resources allow, and reinforce the value of using plain language familiar to audiences.

Background: Legislative initiatives have spurred an increase in pediatric drug development programs. However, some drug products studied in the pediatric population have not received an approved pediatric indication, and efforts have been made to improve the outcomes of a greater percentage of pediatric trials.

Objective: This analysis evaluated the rate of failure and the factors associated with those unsuccessful outcomes of recent pediatric drug development programs in comparison to earlier pediatric drug development programs.

Methods: Publicly available information for non-oncology pediatric drug development programs submitted to the FDA between 2015 and 2022 were reviewed.

Results: FDA reviews and drug product labeling for 211 drug products were examined. Of these, 32 (32/211, 15%) drug products for which pediatric trials were conducted did not receive an approved pediatric indication. The reasons for these unsuccessful outcomes were failure to demonstrate effectiveness only (18/32, 56%), failure to demonstrate safety only (7/32, 22%), or failure to demonstrate both effectiveness and safety (7/32, 22%). The psychiatry (8/32, 25%) and pain (5/32, 17%) therapeutic areas had the highest number of drug products that did not receive a pediatric indication.

Conclusion: The findings from this review suggest that, although this represents an improvement from pre-2012 pediatric drug development programs, that basic problems are still encountered in pediatric trial designs and dose selection. The 15% failure rate may represent close to a best-case scenario for pediatric drug development presently, but an increased use of pediatric extrapolation could change that.

Background: Tazemetostat, an EZH2 inhibitor approved for select sarcomas and lymphomas, has limited post-marketing safety data despite growing clinical use. This study aimed to evaluate the real-world safety profile of tazemetostat using data from the FDA Adverse Event Reporting System (FAERS) between Q1 2020 and Q4 2024.

Methods: Reports listing tazemetostat as the primary suspect drug were extracted, deduplicated, and analyzed using four disproportionality methods. Preferred Terms (PTs) were standardized via MedDRA 26.1 and mapped to System Organ Classes (SOCs). Subgroup analyses and time-to-onset assessments were performed across age, sex, and reporter types.

Results: A total of 1,179 adverse event reports associated with tazemetostat were retrieved from FAERS. Disproportionality analysis revealed significant signals across gastrointestinal, hematologic, and general systemic domains. Fatigue, nausea, decreased appetite, and anemia were the most commonly reported events. Significantly, taste disorder and somnolence were identified as new signals that were not present in FDA labeling. Most events occurred within the first 60 days of treatment, with similar onset patterns across demographic subgroups.

Conclusion: This FAERS-based analysis confirmed known toxicities and identified novel signals associated with tazemetostat in routine clinical use. These findings underscore the importance of continued pharmacovigilance to detect emerging adverse events and inform real-world monitoring strategies.

Clinical trial number: Not applicable.

Background and objectives: Tuberculosis (TB) remains a major global health challenge, driving the need for innovative approaches in diagnosis and drug development. The integration of artificial intelligence (AI), particularly machine learning (ML), has enabled significant advancements in areas such as drug resistance prediction, radiomics, prognostic modeling, and computational drug discovery. This study presents a comprehensive bibliometric analysis of global research on machine learning and tuberculosis (MLTB), highlighting trends relevant to therapeutic innovation and regulatory science.

Methods: A structured search of the Scopus database was conducted for English-language, data-driven publications on MLTB through May 1, 2024. Bibliometric indicators were analyzed using Biblioshiny and VOSviewer, focusing on publication trends, citation metrics, collaboration networks, and thematic clustering.

Results: The MLTB research field has grown rapidly, with an average annual growth rate of 22.12% between 2000 and 2024. Publications averaged 21.64 citations, and 40.11% involved international collaboration. Twelve major clusters were identified, including deep learning, drug discovery, bioinformatics, docking, random forest, and latent TB infection-highlighting the field's expanding scope in drug development and diagnostic applications.

Conclusion: MLTB research is evolving rapidly, driven by interdisciplinary collaboration and AI innovation. These findings offer insights for guiding future AI-enabled TB therapeutic strategies and aligning research efforts with regulatory and translational priorities.

The placebo lead-in design is commonly utilized in psychiatric clinical trials to mitigate high placebo response rates; conventional methods for estimating treatment effects typically rely solely on data from the second period, disregarding the enrichment process integral to this design. This limitation can result in an incomplete assessment of the true treatment effect in the intended target population, as desired in real-world clinical settings. To overcome this limitation, a novel adjusted estimator is proposed, leveraging the probability structure of the placebo lead-in design to provide a more accurate estimation of the treatment effect for the target population. When a treatment effect exists, the traditional estimator often tends to overestimate the effect. In contrast, the adjusted estimator delivers a more reliable estimate, particularly when the proportion of non-responders during the placebo lead-in period is sufficiently high (e.g., above 70%). A case study is included to illustrate the analysis approach and result interpretation. Furthermore, actionable recommendations are provided to support the effective implementation of the placebo lead-in design.

Kidney diseases have been a highly challenging area for new drug development because of traditional requirements for reaching doubling of serum creatinine, dialysis, or transplantation endpoints for regulatory approval, which translates into clinical trials needing several years of follow up and large numbers of study participants to achieve adequate power. In recent years, however, progress in surrogate endpoints (specifically proteinuria reduction and slowing of estimated glomerular filtration rate decline in rare glomerular diseases) has resulted in greatly increased interest by biotechnology and pharmaceutical sponsors in investing in these indications.

Lord-Bessen et al. demonstrated that both single-item-per-screen and multiple-items-per-screen ePRO formats are acceptable, with minimal differences in usability and completion time. While format preference may be individual-specific, broader considerations-including patient cognitive load, device type, language complexity, and trial phase-are crucial for context-aware ePRO design. Future research should explore adaptive systems that dynamically adjust format in real time, subgroup analyses for older adults and low digital literacy participants, and language-specific validation. Moving beyond fixed formats toward adaptive, patient-tailored delivery can better align with regulatory priorities for patient-focused drug development, enhancing both participant experience and data integrity.