Practical Guidelines for Standardised Resolution of Important Protocol Deviations in Clinical Trials Conducted in Sub-Saharan AfricaZemsi, Armel; Nekame, Lorraine Jinette Guedem; Mohammed, Nuredin; Batchilly, Elizabeth Stanley; Dabira, Edgard; Sillah, Sheikh Omar; Sey, Gibbi; Williams, Daisy H.; Dondeh, Bai-Lamin; Cerami, Carla; Clarke, Ed; D’Alessandro, Umberto
doi: 10.1007/s43441-023-00604-3pmid: 38285370
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.
Translating a Culture of Quality to Clinical Research Conduct: Expanding the Clinical Development Quality FrameworkTorok, Michael; Sam, Leslie; Hebert, Jennifer
doi: 10.1007/s43441-023-00610-5pmid: 38324149
The International Council on Harmonisation E8 Guidance Revision 1 (ICH E8(R1)) calls for creating a Culture of Quality that “values and rewards critical thinking and open, proactive dialogue about what is critical to quality.” Across the biopharma landscape, clinical sites, sponsors, and service providers are working to translate this far-reaching guideline into working practices. This manuscript deconstructs key elements that comprise the critical thinking and open, proactive Culture of Quality “enablers.” In addition, maturity models are provided so readers can visualize what a Culture of Quality looks like in their clinical research organization. These provide examples of high performing cultures of quality and useful tools for teams or organizations to measure and evolve their respective quality cultures.
Incorporating Prior Data in Quantitative Benefit–Risk Assessments: Case Study of a Bayesian MethodDharmarajan, Sai; Yuan, Zhong; Chen, Yeh-Fong; Lackey, Leila; Mukhopadhyay, Saurabh; Singh, Pritibha; Tiwari, Ram
doi: 10.1007/s43441-023-00611-4pmid: 38265736
BackgroundMultiple 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.MethodsWe 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.ResultsA 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.ConclusionOur 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/.
Approaches to Design an Efficient, Predictable Global Post-approval Change Management System that Facilitates Continual Improvement and Drug Product AvailabilityVinther, Anders; Ramnarine, Emma; Gastineau, Thierry; O’Brien, Laura; Brehm, Oliver; Fryrear, David
doi: 10.1007/s43441-024-00614-9pmid: 38369639
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 GlobalPACManagement 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.
The Next Horizon of Drug Development: External Control Arms and Innovative Tools to Enrich Clinical Trial DataZou, Kelly H.; Vigna, Chelsea; Talwai, Aniketh; Jain, Rahul; Galaznik, Aaron; Berger, Marc L.; Li, Jim Z.
doi: 10.1007/s43441-024-00627-4pmid: 38528279
Conducting clinical trials (CTs) has become increasingly costly and complex in terms of designing and operationalizing. These challenges exist in running CTs on novel therapies, particularly in oncology and rare diseases, where CTs increasingly target narrower patient groups. In this study, we describe external control arms (ECA) and other relevant tools, such as virtualization and decentralized clinical trials (DCTs), and the ability to follow the clinical trial subjects in the real world using tokenization. ECAs are typically constructed by identifying appropriate external sources of data, then by cleaning and standardizing it to create an analysis-ready data file, and finally, by matching subjects in the external data with the subjects in the CT of interest. In addition, ECA tools also include subject-level meta-analysis and simulated subjects’ data for analyses. By implementing the recent advances in digital health technologies and devices, virtualization, and DCTs, realigning of CTs from site-centric designs to virtual, decentralized, and patient-centric designs can be done, which reduces the patient burden to participate in the CTs and encourages diversity. Tokenization technology allows linking the CT data with real-world data (RWD), creating more comprehensive and longitudinal outcome measures. These tools provide robust ways to enrich the CT data for informed decision-making, reduce the burden on subjects and costs of trial operations, and augment the insights gained for the CT data.
The Evolving Regulatory Paradigm of AI in MedTech: A Review of Perspectives and Where We Are TodayZhou, Karen; Gattinger, Ginny
doi: 10.1007/s43441-024-00628-3pmid: 38528278
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.
A Modified Delphi Study to Establish Essential Clinical Pharmacology CompetenciesJohnson-Williams, Bernadette; Reynolds, Kellie; Gobburu, Joga; Rundio, Albert
doi: 10.1007/s43441-023-00609-ypmid: 38319585
IntroductionCompetency-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.ObjectivesThe primary objective of this study was to determine the most significant competencies needed for a clinical pharmacologist in the regulatory environment.MethodsA 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.ResultsIn 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.ConclusionEssential 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.