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With the increasing globalization of drug development and the publication of the International Council for Harmonisation (ICH) E17 guideline (ICH International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use 2017), multi-regional clinical trials (MRCTs) have become a preferred option to accelerate the availability of new medical products by design, execution and simultaneous submission under one protocol. MRCTs, with the participation of all major regions including countries from both developed and emerging markets, surely make new drug development more efficient. Even though the proposed estimand framework (ICH E9 (R1) (2019), came later in 2019 and was not mentioned in ICH E17, the application of the estimand framework has the potential to enhance the design, execution, and analysis in MRCTs. Defining an estimand within the regional context in MRCTs is an important issue that requires careful consideration. Given that consistency evaluation of treatment effects across regions is critical in MRCTs, the utilization of the estimand framework for regional consistency evaluation is also worth discussion. This paper aims to address these two questions. The five attributes of the estimand definition are discussed within a multi-regional context. It is imperative to thoroughly consider regional intrinsic/extrinsic factors when planning the estimand and estimation of MRCTs. A holistic approach is summarized to conduct consistency evaluation. When a regional inconsistency is observed, the possible reasons need to be further explored under five attributes of the estimand framework. Two real case studies are discussed to illustrate the application of the estimand framework in the consistency evaluation.

Defining the right question of interest is important to a clinical study. ICH E9 (R1) introduces the framework of an estimand and its five attributes, which provide a basis for connecting different components of a study with its clinical questions. Most of the applications of the estimand framework focus on efficacy instead of safety assessment. In this paper, we expand the estimand framework into the safety evaluation and compare/contrast the similarity and differences between safety and efficacy estimand. Furthermore, we present and discuss applications of a safety estimand to oncology trials and pooled data analyses. At last, we also discuss the potential usage of safety estimand to handle the impacts of COVID-19 pandemic on safety assessment.

Over the past decades, the primary interest in vaccine efficacy or immunogenicity evaluation mostly focuses on the biological effect of immunization in complying with the vaccination schedule in a targeted population. The safety questions, which are essential for vaccines as they are generally given to large healthy populations, need to be clearly defined to reflect the risk assessment of interest. ICH E9 (R1) provides a structured framework to clarify the clinical questions and formulate the treatment effect as an estimand. This paper applies the estimand framework to vaccine clinical trials on common clinical questions regarding efficacy, immunogenicity, and safety.

Safety evaluation of drug development is a comprehensive process across the product lifecycle. While a randomized clinical trial (RCT) can provide high-quality data to assess the efficacy and safety of a new intervention, the pre-marketing trials are limited in statistical power to detect causal elevation of rare but potentially serious adverse events. On the other hand, real-world data (RWD) sources play a critical role in further understanding the safety profile of the new intervention. Bringing together the breadth and strength of RWD and RCT data, we can maximize the utility of RWD and answer broader questions. In this manuscript, we propose a three-step statistical framework to corroborate findings from both RCT and RWD for evaluating important safety concerns identified in the pre-marketing setting. By the proposed approach, we first match the observational study to RCT, then the causal estimation is validated via the matched observational study with the target RCT by targeted maximum likelihood estimation (TMLE) method, and lastly the evidence from RCT and RWD can be combined in an integrative analysis. A potential application to cardiovascular outcome trials for type 2 diabetes mellitus is illustrated. Finally, simulation results suggest that the heterogeneity of patient population from RCT and RWD can lead to varying degrees of treatment effect estimation and the proposed approach may be able to mitigate such difference in the integrative analysis., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Clinical safety signal detection is of great importance in establishing the safety profile of new drugs and biologics during drug development. Bayesian hierarchical meta-analysis has proven to be a very effective method of identifying potential safety signals by considering the hierarchical structure of clinical safety data from multiple randomized clinical trials conducted under an Investigational New Drug (IND) application or Biological License Application (BLA). This type of model can integrate information across studies, for instance by grouping related adverse events using the MedDRA system-organ-class (SOC) and preferred terms (PT). It therefore improves the precision of parameter estimates compared to models that do not consider the hierarchical structure of the safety data. We propose to extend an existing four-stage Bayesian hierarchical model and consider the exposure adjusted incidence rate, assuming the number of adverse events (AEs) follows a Poisson distribution. The proposed model is applied to a real-world example, using data from three randomized clinical trials of a neuroscience drug and examine in three simulation studies motivated by real-world examples. Comparison is made between the proposed method and other existing methods. The simulation results indicate that our proposed model outperforms other two candidate models in terms of power and false detection rate., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: To determine the efficacy of a zoster vaccine on herpes zoster (HR)-related interference with activities of daily living (ADLs) and health-related quality of life (HRQL)., Design: Randomized double-blind placebo controlled trial., Setting: Twenty-two U.S. sites., Participants: Thirty eight thousand five hundred forty-six women and men aged 60 and olcer., Measurements: HZ burden of interference with ADLs and HRQL using ratings from the Zoster Brief Pain Inventory (ZBPI) and Medical Outcomes Study 12-item Short Form Survey (SF-12) mental component summary (MCS) and physical component summary (PCS) scores. Vaccine efficacy was calculated for the modified-intention-to-treat trial population and solely in participants who developed HZ., Results: For the modified-intention-to-treat population, the overall zoster vaccine efficacy was 66% (95% confidence interval (CI)=55-74%) for ZBPI ADL burden of interference score and 55% (95% CI=48-61%) for both the SF-12 MCS and PCS scores. Of participants who developed HZ, zoster vaccine reduced the ZBPI ADL burden of interference score by 31% (95% CI=12-51%) and did not significantly reduce the effect on HRQL., Conclusions: Zoster vaccine reduced the burden of HZ-related interference with ADLs in the population of vaccinees and in vaccinees who developed HZ. Zoster vaccine reduced the effect of HZ on HRQL in the population of vaccinees but not in vaccinees who developed HZ., (© 2010, Copyright the Authors. Journal compilation © 2010, The American Geriatrics Society.)