Therapeutic innovation & regulatory science最新文献

Objectives: In compliance with legal requirements, medications are mandated to include a patient information leaflet (PIL) in a physical/paper format that serves as a vital source of information about the medication. While the use of an electronic PIL (ePIL) ensures the availability of the most current information for patients, the prevailing preference between the traditional PIL and ePIL remains uncertain. This observational study aimed to address this gap by reporting the findings of an online survey designed to compare patient preferences for an ePIL versus a paper PIL.

Methods: Conducted across a total of 15 pharmacies in Sweden, the survey enlisted patients via convenience sampling to rate their preference for an ePIL versus a PIL on a 7-point scale together with other questions on, for example, the ease of information retrieval after their visit to the pharmacy. Data collection commenced in December 2022 and ended in November 2023. The primary hypothesis posited that the ePIL format would emerge as the preferred choice. Most participants were female (66%), and the average age was 56 years.

Results: The findings highlighted an inclination towards the ePIL as the preferred choice (58% preferred ePIL, 11% preferred PIL, and 31% were indifferent), with respondents expressing that information retrieval was notably more convenient compared to the paper-based format. Older participants were generally indifferent towards the format. The majority of patients reported familiarity with receiving information in digital formats.

Conclusions: These results suggest the readiness of patients in Sweden to transition to ePILs from the traditional paper PIL.

Traditional Risk-Based Monitoring (RBM) strategies emphasise key risk indicators and site-level performance metrics but seldom address the heterogeneity of patient eligibility profiles. We present a data-driven framework that captures temporal and inter-site shifts in baseline inclusion characteristics. Central to this framework are two new metrics-Borderline Inclusion Index and Eligibility Distribution Divergence-that quantify departures from expected enrolment patterns. A Bayesian composite score synthesises these indicators to prioritise oversight actions. Through simulation experiments and a worked case study, we show that monitoring eligibility pattern shifts offers an early warning signal of operational or scientific risk and strengthens overall trial integrity. We operationalize the framework through an interactive Shiny web application that computes indicator-specific posteriors, generates composite site risk scores, and provides visual decision-support for centralized RBM implementation.

Following oral administration of a drug, we observe an absorption delay before the drug enters systemic circulation. This delay is attributed to the time taken for disintegration of the drug delivery system, drug dissolution from the delivery system, migration of the drug to the absorption site, and transfer of the drug through absorption site tissue. Additionally, pharmacokinetic profiles of such drugs frequently exhibit substantial variability among individuals from different sub-populations. In this article, we present a hierarchical transit compartment model that systematically describes absorption delay in orally administered drugs, and explicitly accounts for between sub-population variations. Such a transit compartment model can be regarded as an accurate representation of the underlying physiology, that also accounts for the influence of drug formulation and the physicochemical properties of the drug on the absorption process. Here, we specify non-informative priors on the pharmacokinetic parameters of interest, and develop an efficient computational scheme based on Hamiltonian Monte Carlo algorithm to conduct inference. The proposed joint inferential procedure ensures valid uncertainty quantification, and enables us to conduct simultaneous inference on sub-population specific as well as population parameters. The utility of the methodology is demonstrated through simulation studies, and two case studies.

Obesity remains a critical global health challenge, with rising prevalence and a substantial cardiometabolic and psychosocial burden. Recent therapeutic advances, particularly in incretin-based strategies, underscore the need for a comprehensive characterization of the evolving pharmacological landscape. We conducted a systematic review of clinical trials registered on ClinicalTrials.gov between October 2019 and October 2024, focusing on pharmacological interventions for obesity from early exploratory stages to Phase 3. A total of 275 eligible trials were identified and analyzed. Incretin pathway modulators predominated (69.8%), especially GLP-1 receptor agonists and dual or triple agonists targeting GLP-1, GIP, and glucagon receptors. Most trials were in Phase 2 (40.7%) or Phase 3 (31.3%), indicating a maturing pipeline, while early-stage innovation remained limited (3.3% of trials). Drug repurposing was common (22.2%), notably involving semaglutide and liraglutide, originally approved for type 2 diabetes. Industry-sponsored trials constituted the majority (75.3%), with limited academic (22.2%) and governmental (2.5%) participation. Geographically, trials were concentrated in the United States, China, and Denmark, with relatively few international multicenter studies. While the obesity drug pipeline is expanding rapidly, it remains heavily centered on incretin-based therapies. This dominance, despite strong clinical efficacy, raises concerns regarding long-term safety, accessibility, and mechanistic diversity. Greater investment in early-phase innovation and alternative pharmacological targets will be essential to diversify treatment options and address the unmet need for equitable and sustainable obesity management.

Clinical trials for children with type II diabetes mellitus (T2DM) pose challenges often due to recruitment issues. The variability in the treatment effect for pediatrics with T2DM tends to be much larger than that for adults, therefore, a larger pediatric study is needed to independently detect a similar treatment effect. If leveraging adult information to a pediatric population can be appropriately justified, and scientific rational has been given for the relevancy of the adult information, then Bayesian borrowing methods can aid in reducing the number of patients needed for a pediatric study and therefore increase feasibility and efficiency. We introduce Bayesian borrowing methods to obtain scientifically sound and conclusive results with adequate study power in anti-diabetic products development for children with T2DM. To apply Bayesian borrowing methods, it is important to (1) identify the external data that can be leveraged, (2) pre-specify model parameters, (3) assess operating characteristics, and (4) pre-specify weights and the maximum amount of borrowing needed to achieve a study win. To protect against prior-data conflicts that may exist due to differences in T2DM between adults and pediatrics, we select a mixture prior to take an advantage that they adjust the degree of information borrowed based on the similarity between adults and pediatrics. We applied these methods to an anti-diabetic product. In conclusion, the outcomes of our step-by-step demonstration of the application of Bayesian borrowing methods provides a guide on how to pre-specify parameters and considerations that should be made when planning to implement said methods.

Purpose: The orphan legislation came into force in the European Union (EU) in 2000, providing incentives for the development of orphan medicines. To be eligible for incentives, the applicant needs to apply for an orphan designation (OD). However, at any time, the marketing authorisation holder (MAH) can request the removal of the OD. The possible motives underpinning premature removal of OD have been the subject of speculation. Our aim is to study every early OD removal for the orphan medicinal products (OMPs) approved in the EU between 2000 and 2024 and determine the main reasons behind this phenomenon.

Methods: We identified all the orphan medicines approved between 2000 and 2024. We considered approval date by the European Commission (EC), orphan designation (OD) status, company name, active substance name, trade name, ATC code and Therapeutic Area, and the date of the removal of the OD. Information on the OD withdrawal was cross-checked with the documents on the EMA website, and the legal status of the patent and supplementary protection certificates (SPC) was checked at the European Patent Register.

Results: During the period 2000-2024, 285 OMPs were approved by the EC. Overall, 41 (11.8%) orphan designations were prematurely removed, corresponding to 23 different OMPs.

Conclusions: Three main motives for the early removal of the OD were identified: lack of clinical evidence supporting the significant benefit for the new indication proposed, the companies' preference towards SPC extensions for the paediatric indication (instead of the two additional years of marketing exclusivity), or the new therapeutic indication added is not rare. There is no evidence of commercial "pay to enter" agreements between pharmaceutical companies.

Background: Data integrity (DI) has become a cornerstone of regulatory oversight in pharmaceutical manufacturing. The COVID-19 pandemic coincided with increased digitalization and wider use of remote inspection approaches, drawing renewed attention to data governance. In response, global regulatory agencies emphasized structured DI compliance through harmonized guidelines. However, empirical studies quantifying longitudinal enforcement patterns remain limited.

Methods: This study conducted a full-enumeration analysis of 1766 FDA Warning Letters issued between 2016 and 2023. DI-related violations were reclassified into nine categories based on the ALCOA and ALCOA + frameworks using a predefined rubric derived from EMA, PIC/S, and WHO guidance. Violations were segmented into pre-pandemic (2016-2019) and post-pandemic (2020-2023) periods. Descriptive statistics and exploratory t-tests and chi-square analyses were used to identify directional trends.

Results: Although statistical tests did not yield significant differences between the two periods, violations related to "Endurance," "Availability," and "completeness" showed year-over-year increases after 2020. The average number of DI violations per company increased in 2023. Because fewer firms were cited that year, this pattern may reflect more targeted inspections or an atypical case mix. However, causality cannot be inferred.

Conclusion: The observed patterns are consistent with a regulatory emphasis on risk-based DI oversight, particularly under remote or hybrid inspection models. For manufacturers-especially in PIC/S member countries where hybrid documentation persists-these findings underscore the practical importance of strengthening electronic quality systems. By offering a standardized ALCOA/ALCOA + -based rubric aligned with international guidance, this study provides a replicable framework for future DI inspection analysis and policy discussion.

Background: The Biomarker Qualification Program (BQP), formally established in 2016 under the 21st Century Cures Act, is a key pathway for developing novel biomarkers for regulatory use. We evaluated eight years of BQP experience to assess whether it has facilitated the qualification of novel biomarkers.

Methods: We collected characteristics and submission dates for accepted biomarker qualification projects from the FDA's Drug Development Tool Qualification Project Search database.

Results: As of July 1, 2025, 61 projects were accepted into the BQP. Safety (30%), Diagnostic (21%), and PD Response (20%) biomarkers were the most common. Projects primarily used molecular (46%) and radiologic/imaging (39%) methods and were split between measures of a disease/condition or drug response/effect of exposure. Few projects included surrogate endpoint biomarkers (n = 5). Half of the accepted projects remained at the initial Letter of Intent (LOI) stage, and only eight biomarkers were qualified through the program. LOI and Qualification Plan (QP) reviews frequently exceeded FDA targets by three months and seven months, respectively. For projects reaching the QP stage, QP development took a median of 32 months, with surrogate endpoints taking 47 months.

Conclusion: The BQP supports the development of certain biomarkers but has seen limited use for biomarkers intended as surrogate endpoints. Coupled with longer timelines for their QP development, these trends demonstrate the program may not be well-suited for advancing novel response biomarkers. Given significant stakeholder interest in novel surrogate measures, a dedicated program may better support novel response biomarker development, particularly for biomarkers with applicability across multiple drug development programs.

Introduction: Generic drug entry into the pharmaceutical market typically leads to a substantial decline in originator sales. Understanding the extent and trajectory of this erosion is essential for effective lifecycle management and strategic planning. This study quantified sales erosion after generic entry for originator drugs approved in the United States between 2010 and 2019 and developed a model to predict year-specific sales retention based on key product- and market-level characteristics.

Methods: A total of 140 originator drugs were analyzed using FDA approval records and sales data from Evaluate Pharma. Five-year retention patterns were modeled using a three-parameter exponential decay function. Subgroup analyses were conducted by year of generic entry, therapeutic class, and product-specific features. A polynomial regression model using 700 product-year observations incorporated three binary market indicators and linear and quadratic time terms.

Results: Sales retention declined from 73.1% in the first year after generic entry to 31.7% by year five. The exponential decay model demonstrated a strong goodness-of-fit (root mean squared error [RMSE] = 0.006), capturing the initial steep decline and subsequent stabilization. Subgroup analyses showed faster erosion for blockbuster drugs and in markets with multiple first-generation generics. The regression model explained 96.4% of annual variation in retention (RMSE = 0.033), accounting for product and market heterogeneity.

Conclusion: Sales decline after generic entry follows a predictable yet heterogeneous trajectory shaped by product and market factors. Exponential decay and polynomial regression models together offer a robust framework for forecasting sales retention and guiding strategic decisions in the pharmaceutical industry.