As clinical trials become more complex and distributed, principal investigators (PIs) face an expanding scope of oversight. ICH E6(R3) Good Clinical Practice permits delegation while retaining investigator responsibility and proportionate oversight for activities undertaken under their responsibility. Operational authority and portfolio-level oversight capacity often do not expand in proportion to these demands. This Perspective proposes a dual-mismatch framework: site-level clinical accountability may exceed both the PI’s influence over operational dependencies and the capacity available to oversee them. The concern is not merely workload, but its relationship to authority and capacity. Decentralisation amplifies rather than creates these longstanding mismatches, although its net effect depends on how work is organised. Current regulatory provisions recognise relevant responsibilities but may not fully resolve these mismatches in practice. Four complementary directions are proposed: weighted portfolio-level capacity assessment, interface-level accountability mapping, operational levers, and redesigned distributed clinical leadership. These approaches preserve the PI’s ultimate oversight responsibility while clarifying other parties’ duties and sharing supervisory activities. The framework and proposed measures require empirical validation. A research agenda would examine their associations with timely safety review, important protocol deviations and data quality, and evaluate whether organisational changes improve oversight.
The FDA frequently solicits public input to inform advisory committee meetings reviewing new drug applications. Although intended to enhance transparency and incorporate patient perspectives, the content of these submissions has not been well described. To characterize public comments to FDA advisory committee meetings and examine the values and considerations expressed. Qualitative study using inductive content analysis with an iterative coding framework. Comments were coded by one reviewer and independently double-coded for a random subset; disagreements were resolved through discussion (Light's kappa = 0.81). Public comments associated with FDA advisory committee meetings for five new drug applications reviewed between January 2020 and December 2024. A random sample of 600 public comments from the five products with the highest public engagement: (1) sodium phenylbutyrate–taurursodiol for ALS; (2) teplizumab for type 1 diabetes; (3) midomafetamine (MDMA-assisted therapy) for PTSD; (4) delandistrogene moxeparvovec for Duchenne muscular dystrophy; and (5) eflornithine tablets for pediatric neuroblastoma. Stakeholder role, stance regarding drug approval, and thematic content. Submissions were most commonly from caregivers or immediate family members (31.5
ICH M14 reached Step 4 in September 2025 and became effective in the European Union (EU) on March 18, 2026. This narrative review compares the institutional pathways and methodological considerations linking real-world data (RWD) studies to risk management plans (RMPs) in the EU, Japan, and the Republic of Korea across eight author-defined domains derived from M14. Regulatory documents, selected EU outcomes of imposed non-interventional post-authorization safety studies (PASS) involving nationally authorized products, and a published review of Japanese post-marketing database studies (PMDS) were synthesized as distinct evidence streams. Regulator-led and academic studies provided separate contextual evidence. EU and Japanese documents link RMP safety concerns to study planning and regulatory reassessment, but differ in the documented arrangements for study-level disclosure and product-level RMP communication. The selected EU cases illustrate different approaches to safety risk assessment and evaluation of prescription restrictions. A Japanese review reported 85 PMDS in 63 of 619 RMPs after deduplication. Korea established database study provisions in 2020 and methodological guidance in 2021 before unified RMP management. The synthesis identified clear safety questions, question-appropriate data and design, and the linkage of the findings to regulatory review and follow-up as practical implementation considerations. Complementary guidance remains relevant for utilization and risk-minimization studies outside M14’s direct scope. Differences in sampling frames and study maturity limit quantitative comparisons of uptake and outcomes, and public sources have not established the extent of RWD use within individual Korean RMPs.
Data from the industry-driven reliance pilot projects for Chemistry, Manufacturing and Controls (CMC) Post-approval Changes (PACs) as presented in this paper have indicated the potential to reduce review and approval timelines by 12-80% in the cases discussed herein. This may help improve the availability of medicines and vaccines for patients globally. Such outcomes are attributed to collaboration between regulators and the pharmaceutical industry. This article describes the approach taken for these pilots and presents data from the initial eight PAC reliance pilots that have completed their reliance procedure and also includes information from three pilots still underway. All pilots focused on major and moderate PACs (EU Type II and Type IB variations). Data collected included product modality, types of CMC changes, involvement of regulatory authorities and approval rates. The article also explores the benefits and possible limitations of reliance approaches for CMC changes and considers steps towards making reliance pathways a routine option for global CMC post-approval changes. As pilot programmes progress, future publications may expand on these observations with data from other ongoing and planned pilot projects.
Randomized controlled trials (RCTs) remain the gold standard for evaluating medical interventions, yet they face persistent methodological challenges: patient dropout, inadequate sample sizes, premature termination, missing data, and the limitations of indirect treatment comparisons. The emergence of digital twin technology—computational patient representations that generate simulated clinical trajectories statistically indistinguishable from real-world data—offers a promising methodological complement to address these limitations. We synthesize evidence from key methodological literature, regulatory guidance (ICH E9(R1), FDA, EMA), and proof-of-concept studies across oncology, neurology, and Alzheimer’s disease. A taxonomy of in silico clinical trial approaches provides the organizational framework. This article is a narrative perspective rather than a systematic review; no predefined search strategy, database range, or inclusion/exclusion criteria were applied. Digital twins may provide complementary methodological approaches across nine trial challenges: model-based sensitivity analyses for missing (MNAR) outcomes; Bayesian and posterior predictive modeling of partially observed longitudinal outcomes; prognostic covariate adjustment and virtual augmentation to improve efficiency; prospective simulation of futility stopping rules; prospective calibration of efficacy stopping boundaries; individualized control-arm (ICA) construction; hybrid augmented and synthetic control strategies; pre-trial protocol optimization through in silico simulation; and population-adjusted indirect treatment comparison. Digital twins represent an emerging methodological ecosystem rather than isolated tools. Their methodological potential depends on consistent validation and explainability standards; frameworks for detecting algorithmic bias; clarification of regulatory acceptance criteria; and comprehensive data infrastructure addressing representativeness gaps. Digital twin approaches should be viewed as complementary to—not replacements for—established randomized trial methodology.
