Innovative trial designs and analyses for vaccine clinical development

Using the 'Leapfrog' Design as a Simple Form of Adaptive Platform Trial to Develop, Test, and Implement Treatment Personalization Methods in Routine Practice

The route for the development, evaluation and dissemination of personalized psychological therapies is complex and challenging. In particular, the large sample sizes needed to provide adequately powered trials of newly-developed personalization approaches means that the traditional treatment development route is extremely inefficient. This paper outlines the promise of adaptive platform trials (APT) embedded within routine practice as a method to streamline development and testing of personalized psychological therapies, and close the gap to implementation in real-world settings. It focuses in particular on a recently-developed simplified APT design, the 'leapfrog' trial, illustrating via simulation how such a trial may proceed and the advantages it can bring, for example in terms of reduced sample sizes. Finally it discusses models of how such trials could be implemented in routine practice, including potential challenges and caveats, alongside a longer-term perspective on the development of personalized psychological treatments.

Vaccine value profile for Chikungunya

Chikungunya virus (CHIKV) a mosquito-borne alphavirus is the causative agent of Chikungunya (CHIK), a disease with low mortality but high acute and chronic morbidity resulting in a high overall burden of disease. After the acute disease phase, chronic disease including persistent arthralgia is very common, and can cause fatigue and pain that is severe enough to limit normal activities. On average, around 40% of people infected with CHIKV will develop chronic arthritis, which may last for months or years. Recommendations for protection from CHIKV focus on infection control through preventing mosquito proliferation. There is currently no licensed antiviral drug or vaccine against CHIKV. Therefore, one of the most important public health impacts of vaccination would be to decrease burden of disease and economic losses in areas impacted by the virus, and prevent or reduce chronic morbidity associated with CHIK. This benefit would particularly be seen in Low and Middle Income Countries (LMIC) and socio-economically deprived areas, as they are more likely to have more infections and more severe outcomes. This 'Vaccine Value Profile' (VVP) for CHIK is intended to provide a high-level, holistic assessment of the information and data that are currently available to inform the potential public health, economic and societal value of vaccines in the development pipeline and vaccine-like products.This VVP was developed by a working group of subject matter experts from academia, non-profit organizations, public private partnerships, and multi-lateral organizations. All contributors have extensive expertise on various elements of the CHIK VVP and collectively aimed to identify current research and knowledge gaps.The VVP was developed using only existing and publicly available information.

Innovative approaches for vaccine trials as a key component of pandemic preparedness - a white paper

BACKGROUND

WHO postulates the application of adaptive design features in the global clinical trial ecosystem. However, the adaptive platform trial (APT) methodology has not been widely adopted in clinical research on vaccines.

METHODS

The VACCELERATE Consortium organized a two-day workshop to discuss the applicability of APT methodology in vaccine trials under non-pandemic as well as pandemic conditions. Core aspects of the discussions are summarized in this article.

RESULTS

An "ever-warm" APT appears ideally suited to improve efficiency and speed of vaccine research. Continuous learning based on accumulating APT trial data allows for pre-planned adaptations during its course. Given the relative design complexity, alignment of all stakeholders at all stages of an APT is central. Vaccine trial modelling is crucial, both before and in a pandemic emergency. Various inferential paradigms are possible (frequentist, likelihood, or Bayesian). The focus in the interpandemic interval may be on research gaps left by industry trials. For activation in emergency, template Disease X protocols of syndromal design for pathogens yet unknown need to be stockpiled and updated regularly. Governance of a vaccine APT should be fully integrated into supranational pandemic response mechanisms.

DISCUSSION

A broad range of adaptive features can be applied in platform trials on vaccines. Faster knowledge generation comes with increased complexity of trial design. Design complexity should not preclude simple execution at trial sites. Continuously generated evidence represents a return on investment that will garner societal support for sustainable funding. Adaptive design features will naturally find their way into platform trials on vaccines.

Adaptive designs in public health: Vaccine and cluster randomized trials go Bayesian

Clinical trials in public health-particularly those conducted in low- and middle-income countries-often involve communicable and non-communicable diseases with high disease burden and unmet needs. Trials conducted in these regions often are faced with resource limitations, so improving the efficiencies of these trials is critical. Adaptive trial designs have the potential to save trial time and resources and reduce the number of patients receiving ineffective interventions. In this paper, we provide a detailed account of the implementation of vaccine and cluster randomized trials within the framework of Bayesian adaptive trials, with emphasis on computational efficiency and flexibility with regard to stopping rules and allocation ratios. We offer an educated approach to selecting prior distributions and a data-driven empirical Bayes method for plug-in estimates for nuisance parameters.

An adaptive seamless 2-in-1 design with biomarker-driven subgroup enrichment

Adaptive seamless phase 2/3 subgroup enrichment design plays a pivotal role in streamlining efficient drug development within a competitive landscape, while also enhancing patient access to promising treatments. This design approach identifies biomarker subgroups with the highest potential to benefit from investigational regimens. The seamless integration of Phase 2 and Phase 3 ensures a timely confirmation of clinical benefits. One significant challenge in adaptive enrichment decisions is determining the optimal timing and maturity of the primary endpoint. In this paper, we propose an adaptive seamless 2-in-1 biomarker-driven subgroup enrichment design that addresses this challenge by allowing subgroup selection using an early intermediate endpoint that predicts clinical benefits (i.e. a surrogate endpoint). The proposed design initiates with a Phase 2 stage involving all participants and can potentially expand into a Phase 3 study focused on the subgroup demonstrating the most favorable clinical outcomes. We will show that, under certain correlation assumptions, the overall type I error may not be inflated at the end of the study. In scenarios where the assumptions may not hold, we present a general framework to control the multiplicity. The flexibility and efficacy of the proposed design are highlighted through an extensive simulation study and illustrated in a case study in multiple myeloma.

Bayesian borrowing from historical control data in a vaccine efficacy trial

In the context of vaccine efficacy trial where the incidence rate is very low and a very large sample size is usually expected, incorporating historical data into a new trial is extremely attractive to reduce sample size and increase estimation precision. Nevertheless, for some infectious diseases, seasonal change in incidence rates poses a huge challenge in borrowing historical data and a critical question is how to properly take advantage of historical data borrowing with acceptable tolerance to between-trials heterogeneity commonly from seasonal disease transmission. In this article, we extend a probability-based power prior which determines the amount of information to be borrowed based on the agreement between the historical and current data, to make it applicable for either a single or multiple historical trials available, with constraint on the amount of historical information to be borrowed. Simulations are conducted to compare the performance of the proposed method with other methods including modified power prior (MPP), meta-analytic-predictive (MAP) prior and the commensurate prior methods. Furthermore, we illustrate the application of the proposed method for trial design in a practical setting.

Treating intrusive memories after trauma in healthcare workers: a Bayesian adaptive randomised trial developing an imagery-competing task intervention

Intensive care unit (ICU) staff continue to face recurrent work-related traumatic events throughout the COVID-19 pandemic. Intrusive memories (IMs) of such traumatic events comprise sensory image-based memories. Harnessing research on preventing IMs with a novel behavioural intervention on the day of trauma, here we take critical next steps in developing this approach as a treatment for ICU staff who are already experiencing IMs days, weeks, or months post-trauma. To address the urgent need to develop novel mental health interventions, we used Bayesian statistical approaches to optimise a brief imagery-competing task intervention to reduce the number of IMs. We evaluated a digitised version of the intervention for remote, scalable delivery. We conducted a two-arm, parallel-group, randomised, adaptive Bayesian optimisation trial. Eligible participants worked clinically in a UK NHS ICU during the pandemic, experienced at least one work-related traumatic event, and at least three IMs in the week prior to recruitment. Participants were randomised to receive immediate or delayed (after 4 weeks) access to the intervention. Primary outcome was the number of IMs of trauma during week 4, controlling for baseline week. Analyses were conducted on an intention-to-treat basis as a between-group comparison. Prior to final analysis, sequential Bayesian analyses were conducted (n = 20, 23, 29, 37, 41, 45) to inform early stopping of the trial prior to the planned maximum recruitment (n = 150). Final analysis (n = 75) showed strong evidence for a positive treatment effect (Bayes factor, BF = 1.25 × 106): the immediate arm reported fewer IMs (median = 1, IQR = 0-3) than the delayed arm (median = 10, IQR = 6-16.5). With further digital enhancements, the intervention (n = 28) also showed a positive treatment effect (BF = 7.31). Sequential Bayesian analyses provided evidence for reducing IMs of work-related trauma for healthcare workers. This methodology also allowed us to rule out negative effects early, reduced the planned maximum sample size, and allowed evaluation of enhancements. Trial Registration NCT04992390 ( www.clinicaltrials.gov ).

Recent innovations in adaptive trial designs: A review of design opportunities in translational research

Clinical trials are constantly evolving in the context of increasingly complex research questions and potentially limited resources. In this review article, we discuss the emergence of "adaptive" clinical trials that allow for the preplanned modification of an ongoing clinical trial based on the accumulating evidence with application across translational research. These modifications may include terminating a trial before completion due to futility or efficacy, re-estimating the needed sample size to ensure adequate power, enriching the target population enrolled in the study, selecting across multiple treatment arms, revising allocation ratios used for randomization, or selecting the most appropriate endpoint. Emerging topics related to borrowing information from historic or supplemental data sources, sequential multiple assignment randomized trials (SMART), master protocol and seamless designs, and phase I dose-finding studies are also presented. Each design element includes a brief overview with an accompanying case study to illustrate the design method in practice. We close with brief discussions relating to the statistical considerations for these contemporary designs.

Immunogenicity of a Third Scheduled Dose of Rotarix in Australian Indigenous Infants: A Phase IV, Double-blind, Randomized, Placebo-Controlled Clinical Trial

BACKGROUND

Rotarix (GlaxoSmithKline) oral rotavirus vaccine is licensed as 2 doses in the first 6 months of life. In settings with high child mortality rates, clinical protection conferred by 2 doses of Rotarix is reduced. We assessed vaccine immune response when an additional dose of Rotarix was given to Australian Aboriginal children 6 to <12 months old.

METHODS

ORVAC is a 2-stage, double-blind, randomized, placebo-controlled trial. Australian Aboriginal children 6 to <12 months old who had received 1 or 2 prior doses of Rotarix rotavirus vaccine were randomized 1:1 to receive an additional dose of Rotarix or matched placebo. The primary immunological end point was seroresponse defined as an anti-rotavirus immunoglobulin A level ≥20 AU/mL, 28-56 days after the additional dose of Rotarix or placebo.

RESULTS

Between March 2018 and August 2020, a total of 253 infants were enrolled. Of these, 178 infants (70%) had analyzable serological results after follow-up; 89 were randomized to receive Rotarix, and 89 to receive placebo. The proportion with seroresponse was 85% after Rotarix compared with 72% after placebo. There were no occurrences of intussusception or any serious adverse events.

CONCLUSIONS

An additional dose of Rotarix administered to Australian Aboriginal infants 6 to <12 months old increased the proportion with a vaccine seroresponse.

CLINICAL TRIALS REGISTRATION

NCT02941107.

Using surrogate information to improve confirmatory platform trial with sample size re-estimation

Platform design which allows exploring multiple arms with a common control simultaneously is becoming essential for efficient drug development. However, one of the critical challenges for confirmatory platform trials is immature data for interim decisions, particularly for the treatment arm selection and sample size determination with limited data available. We use a modified conditional power (CP) for both treatment arm selection and sample size determination at interim analysis for the proposed platform trial. The modified CP uses the available data from both primary and surrogate endpoints. We also demonstrated the application in a case study of a lung cancer trial.

Borrowing historical information for non-inferiority trials on Covid-19 vaccines

Non-inferiority vaccine trials compare new candidates to active controls that provide clinically significant protection against a disease. Bayesian statistics allows to exploit pre-experimental information available from previous studies to increase precision and reduce costs. Here, historical knowledge is incorporated into the analysis through a power prior that dynamically regulates the degree of information-borrowing. We examine non-inferiority tests based on credible intervals for the unknown effects-difference between two vaccines on the log odds ratio scale, with an application to new Covid-19 vaccines. We explore the frequentist properties of the method and we address the sample size determination problem.

WHO guidance on COVID-19 vaccine trial designs in the context of authorized COVID-19 vaccines and expanding global access: Ethical considerations

While the degree of COVID-19 vaccine accessibility and uptake varies at both national and global levels, increasing vaccination coverage raises questions regarding the standard of prevention that ought to apply to different settings where COVID-19 vaccine trials are hosted. A WHO Expert Group has developed guidance on the ethical implications of conducting placebo-controlled trials in the context of expanding global COVID-19 vaccine coverage. The guidance also considers alternative trial designs to placebo controlled trials in the context of prototype vaccines, modified vaccines, and next generation vaccines.

Year-to-year variation in attack rates could result in underpowered RSV vaccine efficacy trials

OBJECTIVE

Year-to-year variation of respiratory viruses may result in lower attack rates than expected. We aimed to illustrate the impact of year-to-year variation in attack rates on the likelihood of demonstrating vaccine efficacy (VE) .

STUDY DESIGN AND SETTING

We considered an individually randomized maternal vaccine trial against respiratory syncytial virus-associated hospitalisations (RSVH). For 10 RSVH per 1,000 infants, sample size to have 80% power for true VE of 50% and 70% was 9,846 and 4,424 participants. We reported power to show VE for varying attack rates, selected to reflect realistic year-to-year variation using observational studies. Eight scenarios including varying number of countries and seasons were developed to assess the influence of these trial parameters.

RESULTS

Including up to three seasons decreased the width of the interquartile range for power. Including more seasons concentrated statistical power closer to 80%. Least powered trials had higher statistical power with more seasons. In all scenarios, at least half of the trials had <80% power. For three-season trials, increasing the sample size by 10% reduced the percentage of underpowered trials to less than one-quarter of trials.

CONCLUSION

Year-to-year variation in RSV attack rates should be accounted for during trial design. Mitigation strategies include recruiting over more seasons, or adaptive trial designs.

A dose-reduction HPV vaccine immunobridging trial of two HPV vaccines among adolescent girls in Tanzania (the DoRIS trial) - Study protocol for a randomised controlled trial

BACKGROUND

Human papillomavirus (HPV) infection is the primary cause of cervical cancer. In 2018, the World Health Organization (WHO) Director General announced his commitment to eliminate cervical cancer, with HPV vaccination as a priority. However, the costs of setting up a multi-dose HPV vaccination programme remain a barrier to its introduction.

METHODS/DESIGN

We are conducting a randomised-controlled trial of reduced dose schedules of HPV vaccine in Tanzania to establish whether a single dose produces immune responses that will be effective in preventing cervical cancer. 930 girls aged 9-14 years in Mwanza, Tanzania, were randomised to one of 6 arms, comprising 3 different dose schedules of the 2-valent (Cervarix) and 9-valent (Gardasil-9) HPV vaccines: 3 doses; 2 doses given 6 months apart; or a single dose. All participants will be followed for 36 months; those in the 1 and 2 dose arms will be followed for 60 months. Trial outcomes focus on vaccine immune responses including HPV 16/18-specific antibody levels, antibody avidity, and memory B cell responses. Results will be immunobridged to historical cohorts of girls and young women in whom efficacy has been demonstrated.

DISCUSSION

This is the first randomised trial of the single dose HPV vaccine schedule in the target age group. The trial will allow us to examine the quality and durability of immune responses of reduced dose schedules in a population with high burden of malaria and other infections that may affect vaccine immune responses. Initial results (24 months) are expected to be published in early 2021.