Therapeutic innovation & regulatory science最新文献

Background: Whereas anecdotal reports suggest that the use of decentralized clinical trial (DCT) solutions can improve participant diversity in clinical trials there is no quantitative evidence to support such reports.

Methods: Tufts CSDD conducted this initial study based on data collected from prior research and publicly available data drawn from Clinicaltrials.gov to compare and contrast participant diversity in trials which included various DCT solutions - virtual visits or televisits, home visits, devices or wearables, and the use of local labs.

Results: The results of this analysis indicate that the use of local labs is associated with a lower percentage of white participants; the use of virtual visits or televisits is associated with a lower percentage of Black participants; and the use of devices or wearables was not associated with any significant change in participant demographics. The use of home visits could not be tested for significant differences.

A clinical trial is any research on human subjects that involves an investigational medicinal product or device. Investigational medicinal products include unlicensed drugs or drugs used outside the product license (e.g. for a new indication) (ICH-GCP). As per the internationally accepted ICH-GCP guidelines, clinical trials should be conducted strictly per the approved protocol. However, during the lifecycle of a trial, protocol deviations may occur. Under ICH efficacy guidelines, protocol deviations are divided into non-important (minor) or important (major), and the latter can jeopardise the participant's rights, safety or the quality of data generated by the study. Existing guidelines on protocol deviation management do not detail or standardise actions to be taken for participants, investigational products, data or samples as part of a holistic management of important protocol deviations. Herein, we propose guidelines to address the current literature gap and promote the standardisation of actions to address important protocol deviations in clinical trials. The advised actions should complement the existing local institutional review board and national regulatory authority requirements.

Introduction: Competency-based education has been commonly used to enhance the healthcare workforce for some time. A translational discipline that is integral to drug development and impactful on healthcare and public health is clinical pharmacology. With such contribution, it is essential that the clinical pharmacology workforce is adequately equipped to address the demands of emerging trends of drug development.

Objectives: The primary objective of this study was to determine the most significant competencies needed for a clinical pharmacologist in the regulatory environment.

Methods: A two round modified Delphi technique was administered to 29 clinical pharmacologists within the Office of Clinical Pharmacology (OCP) between November 2021-January 2022. A questionnaire consisting of core and technical competencies was administered electronically using SurveyMonkey ® to gain consensus about essential clinical pharmacology competencies. Participants used a Likert scale to rank importance of competencies from strongly agree (1), agree (2), neutral (3), disagree (4), strongly disagree (5). Participants also suggested topics to be included in the next round. Consensus was set at 60%. The competencies receiving the most consensus at 60% in round one and the new topics proceeded to the second round. In the second and final round, participants ranked the suggested competencies. Descriptive statistics and a McNemar change test were utilized to analyze data. Only data from the participants who completed both rounds was used in the study.

Results: In round one participants ranked all fifty-six core and technical competencies as essential with consensus of at least 60%. In round two, participants ranked sixty-two competencies as essential with consensus of at least 60%. A McNemar change test demonstrated stability of ranking between rounds.

Conclusion: Essential core and technical competencies can build education programs to sustain the emerging clinical pharmacology workforce in the Office of Clinical Pharmacology. The Delphi technique is a suitable approach to determine essential competencies because it cultivates consensus and gains insight from experts in the forefront of drug development.

Real-World Evidence (RWE), which has historically been used to support post-approval safety studies, has recently gained acceptance for new drug applications as supportive evidence or as new clinical evidence for medicinal products with orphan designation and/or in disease areas with high unmet need. Here, we present a case study for the use of RWE in the approval of abaloparatide in the European Union (EU) under the tradename Eladynos. In addition to data from the pivotal Phase 3 study, the marketing authorization application (MAA) included clinical data from additional interventional and observational studies, as well as post-marketing data obtained from the United States (US) market since approval of abaloparatide by the Food and Drug Administration (FDA) in 2017. The new interventional studies were not designed to assess fracture efficacy and cardiovascular safety which were topics of concern raised by the Committee for Medicinal Products for Human Use (CHMP) during their review of the initial MAA submitted in 2015. However, these studies taken together with the RWE formed the basis for a new MAA. Prior to the planned resubmission in the EU, national Scientific Advice (SA) was sought on the proposed clinical program, specifically on the relevance of Real-World Data (RWD) derived from an observational study to support and complement the efficacy and safety data already available from prospective randomized clinical trials. This case study demonstrates successful use of RWE to address a previously identified gap raised by the CHMP during the review of an earlier MAA, which led to the approval of Eladynos for the treatment of osteoporosis in the EU.

Artificial intelligence (AI)-enabled technologies in the MedTech sector hold the promise to transform healthcare delivery by improving access, quality, and outcomes. As the regulatory contours of these technologies are being defined, there is a notable lack of literature on the key stakeholders such as the organizations and interest groups that have a significant input in shaping the regulatory framework. This article explores the perspectives and contributions of these stakeholders in shaping the regulatory paradigm of AI-enabled medical technologies. The formation of an AI regulatory framework requires the convergence of ethical, regulatory, technical, societal, and practical considerations. These multiple perspectives contribute to the various dimensions of an evolving regulatory paradigm. From the global governance guidelines set by the World Health Organization (WHO) to national regulations, the article sheds light not just on these multiple perspectives but also on their interconnectedness in shaping the regulatory landscape of AI.

Background: Multiple criteria decision analysis (MCDA) and stochastic multi-criteria acceptability analysis (SMAA) in their current implementation cannot incorporate prior or external information on benefits and risks. We demonstrate how to incorporate prior data using a Bayesian mixture model approach while conducting quantitative benefit-risk assessments (qBRA) for medical products.

Methods: We implemented MCDA and SMAA in a Bayesian framework. To incorporate information from a prior study, we use mixture priors on each benefit and risk attribute that mixes information from a previous study with a vague prior distribution. The degree of borrowing is varied using a mixing proportion parameter.

Results: A demonstration case study for qBRA using the supplementary New Drug Application (sNDA) filing for Rivaroxaban for the indication of reduction in the risk of major thrombotic vascular events in patients with peripheral artery disease (PAD) was used to illustrate the method. Net utility scores, obtained from the randomized controlled trial data to support the sNDA, from the MCDA for Rivaraxoban and comparator were 0.48 and 0.56, respectively, with Rivaroxaban being the preferred alternative only 33% of the time. We show that with only 30% borrowing from a previous RCT, the MCDA and SMAA results are favorable for Rivaroxaban, accounting for the seemingly aberrant results on all-cause death in the trial data used to support the sNDA.

Conclusion: Our method to formally incorporate prior data in MCDA and SMAA is easy to use and interpret. Software in the form of an RShiny App is available here: https://sai-dharmarajan.shinyapps.io/BayesianMCDA_SMAA/ .

Background: Drug approval lag is the time difference for new medicine to obtain marketing authorization approval in the study country compared to the first global approval. Drug approval lag delays the availability of innovative medicine to patients. This may lead to delay in treatment and severe public health implications. The study aimed to determine drug approval lag in Malaysia, the factors associated with drug approval lag (drug characteristics, regulatory factors and applicant type) and the association of the submission lag and review time with the regulation change.

Methods: All new pharmaceutical products approved between January 2015 and March 2021 were examined (n = 136) using publicly available information. Factors associated with drug approval lag were determined using multiple linear regression.

Results: The median drug approval lag was 855 days. Drug approval lag was associated with drug characteristics and regulatory factors. Median submission lag and median review time for products which fulfilled the requirement for the new regulations (Conditional Registration/ Facilitated Registration Pathway) were shorter compared to products which did not fulfil the requirement.

Conclusion: Drug approval lag may delay the access of innovative medicine to patients, and this may lead to an increase in morbidity, mortality and healthcare costs. Good Regulatory Practices ensure efficient and transparent regulatory system which support the public health policy objectives in the most efficient way. The new regulations in Malaysia reduced the median submission lag and review time. The findings may be useful for regulators to consider for future policy development for medication access.

Introduction: Integration of precision medicine (PM) competencies across the Medical Technology and Pharmaceutical industry is critical to enable industry professionals to understand and develop the skills needed to navigate the opportunities arising from rapid scientific and technological innovation in PM. Our objective was to identify the key competency domains required by industry professionals to enable them to upskill themselves in PM-related aspects of their roles.

Methods: A desktop research review of current literature, curriculum, and healthcare trends identified a core set of domains and subdomains related to PM competencies that were consistent across multiple disciplines and competency frameworks. A survey was used to confirm the applicability of these domains to the cross-functional and multi-disciplinary work practices of industry professionals. Companies were requested to trial the domains to determine their relevance in practice and feedback was obtained.

Results: Four PM-relevant domains were identified from the literature review: medical science and technology; translational and clinical application; governance and regulation and professional practice. Survey results refined these domains, and case studies within companies confirmed the potential for this framework to be used as an adjunct to current role specific competency frameworks to provide a specific focus on needed PM capabilities.

Conclusion: The framework was well accepted by local industry as a supplement to role specific competency frameworks to provide a structure on how to integrate new and evolving technologies into their current workforce development planning and build a continuous learning and cross-disciplinary mindset.

The complexity and inter-connectedness of operating in a global world for drug product supply has become an undeniable reality, further underscored by the COVID-19 pandemic. For Post-Approval Changes (PACs) that are an inevitable part of a product's commercial life, the impact of the growing global regulatory complexity and related drug shortages has brought the Global PAC Management System to an inflection point in particular for companies that have their products marketed in many countries.This paper illustrates through data analyzed for the first time from 145,000 + PACs for 156 countries, collected by 18 global pharma companies over a 3-year period (2019-2021), how severe the problem of global regulatory complexity is. Only PACs requiring national regulatory agency (NRA) approval prior to implementation were included in the data set. 1 of the 156 country NRAs approved all submitted PACs within a period of 6 months. The 6-month timeline was chosen because it is the recommended review timeline for major changes in the WHO guidance for vaccines and biotherapeutic products. 10 out of the 156 (6%) countries had no more than 10% of the PACs reviewed and approved in > 6 months. In 33 (22%) countries more than half of the PACs took > 6 months for approval. It is rare that the same PAC is approved globally within 6 months as individual NRAs take from a few months to years (in some cases > 5 years) for their review.The global PAC management complexity has steadily grown over the past 20 years. Attempts thus far to solve this problem have not made any meaningful difference. Senior leaders and decision-makers across the interdependent components of the complex Global PAC Management System (industry and regulators) must come together and collaboratively manage the problem holistically with the objective of ensuring global drug product availability instead of continuing with distinct stakeholder or country-focused solutions, which can tend to worsen the problem.In this paper, the Chief Quality Officers (CQOs) from 18 of the largest innovator pharma companies (see Acknowledgements) are speaking with One-Voice-of-Quality for PACs (1VQ for PACs Initiative). They are recommending a set of 8 approaches to activate a holistic transformation of the Global PAC Management System. This article presents their view on the problem of global regulatory complexity for managing PACs, it's impact on continual improvement and the risk to drug product supply, as well as approaches that can help alleviate the problem.

While industry and regulators' interest in decentralized clinical trials (DCTs) is long-standing, the Covid-19 pandemic accelerated and broadened the adoption and experience with these trials. The key idea in decentralization is bringing the clinical trial design, typically on-site, closer to the patient's experience (on-site or off-site). Thus, potential benefits of DCTs include reducing the burden of participation in trials, broadening access to a more diverse population, or using innovative endpoints collected off-site. This paper helps researchers to carefully evaluate the added value and the implications of DCTs beyond the operational aspects of their implementation. The proposed approach is to use the ICH E9(R1) estimand framework to guide the strategic decisions around each decentralization component. Furthermore, the framework can guide the process for clinical trialists to systematically consider the implications of decentralization, in turn, for each attribute of the estimand. We illustrate the use of this approach with a fully DCT case study and show that the proposed systematic process can uncover the scientific opportunities, assumptions, and potential risks associated with a possible use of decentralization components in the design of a trial. This process can also highlight the benefits of specifying estimand attributes in a granular way. Thus, we demonstrate that bringing a decentralization component into the design will not only impact estimators and estimation but can also correspond to addressing more granular questions, thereby uncovering new target estimands.