If you have an interest in being involved in this SIG, or have an interesting case study or experience to share please contact Fabian Tibaldi (email: fabian.tibaldi@gsk.com)
The COVID-19 pandemic has had effects on multiple operational aspects of clinical trials. Three notable areas of impact are an increase in pandemic-related missing data, disruption to patient recruitment, and acceleration of decentralized trials with alternative methods to conduct patient follow up. In the area of missing data, operational metrics that are leading indicators of potential issues with the primary efficacy endpoints have been helpful. Work will be presented on sophisticated metrics that have been developed that can flag problems even for complex endpoints such as progression-free survival (PFS). These measures can be used as QTLs and/or in centralized study monitoring at a study level; and can be summarized to quantify risk at a portfolio level. In the area of patient recruitment, recruitment in complex trials is often facilitated by the use of stochastic models. The COVID-19 pandemic brought an additional layer of complexity to recruitment modelling: as countries went into shutdown, sponsors faced the dilemma of re-planning study delivery, re-balancing their portfolios “on the fly”. That translated into the need to adapt the recruitment model to account for effect of COVID-19. Work will be presented on an approach that blends Poisson-Gamma models, real-time recruitment data updates and epidemiological modelling of COVID-19 spread. In the area of decentralized trials, the use of alternative mechanisms to conduct patient follow-up, such as telemedicine and remote assessments, in addition to core clinic visits has been accelerated by the COVID-19 pandemic. Clinical trial sponsors had to react quickly to incorporate different methods for managing the conduct of ongoing clinical trials assuring the robust collection of safety and efficacy data. Lessons learned will be shared on how the impact of changes in study conduct were managed and consequences to the planned analyses.
The session will highlight real life experiences implementing Bayesian designs in proof of concept and pivotal COVID-19 vaccine trials. The speakers and discussant will reflect on the key methodological considerations, regulatory interactions, and operational challenges. Our first speaker will present a Bayesian sequential proof-of-concept (POC) trial to investigate the efficacy of Bacillus Calmette-Guérin (BCG) in providing protection against COVID-19 infections through ""trained immunity"". The main design consideration is to provide a framework to rapidly establish a POC on the vaccine efficacy of BCG under a constantly evolving incidence rate and in absence of prior efficacy data. The trial design is based on taking several interim looks and calculating the predictive power with the current cohort at each look. Decisions to stop the trial for futility or stopping enrollment for efficacy are made based on the last two predictive power computations.
Our second speaker will discuss the statistical aspects of the Pfizer Phase III Bayesian adaptive vaccine trial. This trial incorporates multiple interim analyses, each based on achieving a sufficiently high Bayesian posterior probability of vaccine efficacy. The trial also incorporates early stopping for futility based on Bayesian predictive probabilities. The talk will include key statistical aspects and regulatory challenges of the design.
Following the outbreak of COVID-19 around the world, several COVID-19 vaccine candidates are in development across various clinical trial stages. While historically it has taken years or even decades to develop safe and effective vaccines from discovery to licensure, the urgency of developing a vaccine for COVID-19 presents enormous challenges and opportunities. Pharmaceutical companies across the world have joined efforts to race against the clock in order to develop effective vaccines and treatments to control the pandemic and to stop the spread of the disease that is causing a high number of deaths worldwide. Statisticians have played an important leadership role in dealing with these challenges. In this session, key opinion leaders from industry, regulatory, and academia will share their stories on handling challenges and innovative approaches for COVID-19 vaccine development.
Confirmed speakers and discussants:
- Geert Molenberghs (Universiteit Hasselt & KU Leuven), “COVID-19: modeling, epidemiological, clinical and vaccine aspects”
- Scott Patterson (Sanofi-Pasteur) “Statistical Observations on SARS-CoV-2 Clinical Vaccine Development”
- Ye Yang (CBER. FDA) “Statistical Challenges in COVID-19 Vaccine Trials”
- Tsai-Lien Lin (CBER, FDA), discussant
Vaccines have been playing a critical role in public health through prevention of infectious diseases. An effective vaccine could prevent serious diseases, reduce disease burden on families and communities, or even eradicate diseases (e.g. smallpox). Vaccine research and development have been and will be important in this everchanging world. In developing new vaccines and managing life cycles of existing vaccines, new challenges keep emerging, and innovations are following.
As an integral part of the vaccine development, statisticians also come up with innovations in study designs and analysis methodologies. Speakers from academia, industry and government will share their experiences with some of the following innovations in solving challenges in vaccine development: biomarker assessment (correlates of risk and correlates of protection) especially for first-in-class vaccines; bridging of vaccine efficacy to new settings; multiplicity challenges in multivalent vaccines (multiple serotypes of a pathogen) or due to co-administration with routine vaccines that results in testing of many hypotheses to show non-inferiority of the routine vaccines with vs. without investigational vaccine; evaluation of effects for new serotypes added on top of an existing vaccine; real world data/evidence implementation (e.g. hybrid trial design); application of estimands in vaccine trials to address intercurrent events; and safety assessment/monitoring.
Chair: Josh Chen
Organizers: Frank, Lihan Yan (FDA CBER) and Wenquan Wang (Sanofi)
Potential speakers for the session include, to be confirmed
Dr. Peter Gilbert, Fred Hutch
Dr. Lihan Yan, CBER, FDA
Dr. Judy Pan, Sanofi Pasteur
Dr. Jianing Li, Merck & Co., Inc.
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