The Adaptive Platform Trials Coalition. Adaptive platform trials: definition, design, conduct and reporting considerations

Adaptive Trials in Stroke: Current Use and Future Directions

Inclusion of adaptive design features in a clinical trial provides preplanned flexibility to dynamically modify a trial during its conduct while preserving validity and integrity. Adaptive trials are needed to accelerate the conduct of more efficient, informative, and ethical clinical research in the field of neurology. Stroke is a natural candidate for adoption of these innovative approaches to trial design. This Research Methods in Neurology article is informed by a scoping review that identified 45 completed or ongoing adaptive clinical trials in stroke that were appraised: 15 trials had published results with or without a published protocol and 30 ongoing trials (14 trials had a published protocol, and 16 trials were registered only). Interventions spanned acute (n = 28), rehabilitation (n = 8), prevention (n = 8), and rehabilitation and prevention (n = 1). A subsample of these trials was selected to illustrate the utility of adaptive design features and discuss why each adaptive feature was incorporated in the design to best achieve the aim; whether each individual feature was used and whether it resulted in expected efficiencies; and any learnings during preparation, conduct, or reporting. We then discuss the operational, ethical, and regulatory considerations that warrant careful consideration during adaptive trial planning and reflect on the workforce readiness to deliver adaptive trials in practice. We conclude that adaptive trials can be designed, funded, conducted, and published for a wide range of research questions and offer future directions to support adoption of adaptive trial designs in stroke and neurologic research more broadly.

A Randomized Embedded Multifactorial Adaptive Platform for Extra Corporeal Membrane Oxygenation (REMAP ECMO) - Design and Rationale of the Left Ventricular Unloading trial domain

BACKGROUND

The use of Extracorporeal Membrane Oxygenation (ECMO) remains associated with high rates of complications, weaning failure and mortality which can be partly explained by a knowledge gap on how to properly manage patients on ECMO support. To address relevant patient management issues, we designed a "Randomized Embedded Multifactorial Adaptive Platform (REMAP)" in the setting of ECMO (REMAP ECMO) and a first embedded randomized controlled trial (RCT) investigating the effects of routine early left ventricular (LV) unloading through intra-aortic balloon pumping (IABP).

METHODS

REMAP ECMO describes a registry-based platform allowing for the embedding of multiple response adaptive RCTs (trial domains) which can perpetually address the effect of relevant patient management issues on ECMO weaning success. A first trial domain studies the effects of LV unloading by means of an IABP as an adjunct to veno-arterial (V-A) ECMO versus V-A ECMO alone on ECMO weaning success at 30 days in adult cardiogenic shock patients admitted to the Intensive Care Unit (ICU). The primary outcome of this trial is "successful weaning from ECMO" being defined as a composite of survival without the need for mechanical circulatory support, heart transplantation, or left ventricular assist device (LVAD) at 30 days after initiation of ECMO. Secondary outcomes include the need for interventional escalation of LV unloading strategy, mechanistic endpoints, survival characteristics until one year after ECMO initiation, and quality of life. Trial data will be analysed using a Bayesian statistical framework. The adaptive design allows for a high degree of flexibility, such as response adaptive randomization and early stopping of the trial for efficacy or futility. The REMAP ECMO LV unloading study is approved by the Medical Ethical Committee of the Erasmus Medical Center and is publicly registered.

CONCLUSION

This REMAP ECMO trial platform enables the efficient roll-out of multiple RCTs on relevant patient management issues. A first embedded trial domain will compare routine LV unloading by means of an IABP as an adjunct to V-A ECMO versus V-A ECMO alone.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT05913622.

Adaptive designs in clinical trials: a systematic review-part I

BACKGROUND

Adaptive designs (ADs) are intended to make clinical trials more flexible, offering efficiency and potentially cost-saving benefits. Despite a large number of statistical methods in the literature on different adaptations to trials, the characteristics, advantages and limitations of such designs remain unfamiliar to large parts of the clinical and research community. This systematic review provides an overview of the use of ADs in published clinical trials (Part I). A follow-up (Part II) will compare the application of AD in trials in adult and pediatric studies, to provide real-world examples and recommendations for the child health community.

METHODS

Published studies from 2010 to April 2020 were searched in the following databases: MEDLINE (Ovid), Embase (Ovid), and International Pharmaceutical Abstracts (Ovid). Clinical trial protocols, reports, and a secondary analyses using AD were included. We excluded trial registrations and interventions other than drugs or vaccines to align with regulatory guidance. Data from the published literature on study characteristics, types of adaptations, statistical analysis, stopping boundaries, logistical challenges, operational considerations and ethical considerations were extracted and summarized herein.

RESULTS

Out of 23,886 retrieved studies, 317 publications of adaptive trials, 267 (84.2%) trial reports, and 50 (15.8%) study protocols), were included. The most frequent disease was oncology (168/317, 53%). Most trials included only adult participants (265, 83.9%),16 trials (5.4%) were limited to only children and 28 (8.9%) were for both children and adults, 8 trials did not report the ages of the included populations. Some studies reported using more than one adaptation (there were 390 reported adaptations in 317 clinical trial reports). Most trials were early in drug development (phase I, II (276/317, 87%). Dose-finding designs were used in the highest proportion of the included trials (121/317, 38.2 %). Adaptive randomization (53/317, 16.7%), with drop-the-losers (or pick-the-winner) designs specifically reported in 29 trials (9.1%) and seamless phase 2-3 design was reported in 27 trials (8.5%). Continual reassessment methods (60/317, 18.9%) and group sequential design (47/317, 14.8%) were also reported. Approximately two-thirds of trials used frequentist statistical methods (203/309, 64%), while Bayesian methods were reported in 24% (75/309) of included trials.

CONCLUSION

This review provides a comprehensive report of methodological features in adaptive clinical trials reported between 2010 and 2020. Adaptation details were not uniformly reported, creating limitations in interpretation and generalizability. Nevertheless, implementation of existing reporting guidelines on ADs and the development of novel educational strategies that address the scientific, operational challenges and ethical considerations can help in the clinical trial community to decide on when and how to implement ADs in clinical trials. STUDY PROTOCOL REGISTRATION: https://doi.org/10.1186/s13063-018-2934-7 .

Reporting and communication of sample size calculations in adaptive clinical trials: a review of trial protocols and grant applications

BACKGROUND

An adaptive design allows modifying the design based on accumulated data while maintaining trial validity and integrity. The final sample size may be unknown when designing an adaptive trial. It is therefore important to consider what sample size is used in the planning of the study and how that is communicated to add transparency to the understanding of the trial design and facilitate robust planning. In this paper, we reviewed trial protocols and grant applications on the sample size reporting for randomised adaptive trials.

METHOD

We searched protocols of randomised trials with comparative objectives on ClinicalTrials.gov (01/01/2010 to 31/12/2022). Contemporary eligible grant applications accessed from UK publicly funded researchers were also included. Suitable records of adaptive designs were reviewed, and key information was extracted and descriptively analysed.

RESULTS

We identified 439 records, and 265 trials were eligible. Of these, 164 (61.9%) and 101 (38.1%) were sponsored by industry and public sectors, respectively, with 169 (63.8%) of all trials using a group sequential design although trial adaptations used were diverse. The maximum and minimum sample sizes were the most reported or directly inferred (n = 199, 75.1%). The sample size assuming no adaptation would be triggered was usually set as the estimated target sample size in the protocol. However, of the 152 completed trials, 15 (9.9%) and 33 (21.7%) had their sample size increased or reduced triggered by trial adaptations, respectively. The sample size calculation process was generally well reported in most cases (n = 216, 81.5%); however, the justification for the sample size calculation parameters was missing in 116 (43.8%) trials. Less than half gave sufficient information on the study design operating characteristics (n = 119, 44.9%).

CONCLUSION

Although the reporting of sample sizes varied, the maximum and minimum sample sizes were usually reported. Most of the trials were planned for estimated enrolment assuming no adaptation would be triggered. This is despite the fact a third of reported trials changed their sample size. The sample size calculation was generally well reported, but the justification of sample size calculation parameters and the reporting of the statistical behaviour of the adaptive design could still be improved.

Heterogeneity, Bayesian thinking, and phenotyping in critical care: A primer

PURPOSE

To familiarize clinicians with the emerging concepts in critical care research of Bayesian thinking and personalized medicine through phenotyping and explain their clinical relevance by highlighting how they address the issues of frequent negative trials and heterogeneity of treatment effect.

SUMMARY

The past decades have seen many negative (effect-neutral) critical care trials of promising interventions, culminating in calls to improve the field's research through adopting Bayesian thinking and increasing personalization of critical care medicine through phenotyping. Bayesian analyses add interpretive power for clinicians as they summarize treatment effects based on probabilities of benefit or harm, contrasting with conventional frequentist statistics that either affirm or reject a null hypothesis. Critical care trials are beginning to include prospective Bayesian analyses, and many trials have undergone reanalysis with Bayesian methods. Phenotyping seeks to identify treatable traits to target interventions to patients expected to derive benefit. Phenotyping and subphenotyping have gained prominence in the most syndromic and heterogenous critical care disease states, acute respiratory distress syndrome and sepsis. Grouping of patients has been informative across a spectrum of clinically observable physiological parameters, biomarkers, and genomic data. Bayesian thinking and phenotyping are emerging as elements of adaptive clinical trials and predictive enrichment, paving the way for a new era of high-quality evidence. These concepts share a common goal, sifting through the noise of heterogeneity in critical care to increase the value of existing and future research.

CONCLUSION

The future of critical care medicine will inevitably involve modification of statistical methods through Bayesian analyses and targeted therapeutics via phenotyping. Clinicians must be familiar with these systems that support recommendations to improve decision-making in the gray areas of critical care practice.

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.

Nirmatrelvir-Ritonavir and Symptoms in Adults With Postacute Sequelae of SARS-CoV-2 Infection: The STOP-PASC Randomized Clinical Trial

Importance

There is an urgent need to identify treatments for postacute sequelae of SARS-CoV-2 infection (PASC).

Objective

To assess the efficacy of a 15-day course of nirmatrelvir-ritonavir in reducing the severity of select PASC symptoms.

Design, Setting, and Participants

This was a 15-week blinded, placebo-controlled, randomized clinical trial conducted from November 2022 to September 2023 at Stanford University (California). The participants were adults with moderate to severe PASC symptoms of 3 months or longer duration.

Interventions

Participants were randomized 2:1 to treatment with oral nirmatrelvir-ritonavir (NMV/r, 300 mg and 100 mg) or with placebo-ritonavir (PBO/r) twice daily for 15 days.

Main Outcomes and Measures

Primary outcome was a pooled severity of 6 PASC symptoms (fatigue, brain fog, shortness of breath, body aches, gastrointestinal symptoms, and cardiovascular symptoms) based on a Likert scale score at 10 weeks. Secondary outcomes included symptom severity at different time points, symptom burden and relief, patient global measures, Patient-Reported Outcomes Measurement Information System (PROMIS) measures, orthostatic vital signs, and sit-to-stand test change from baseline.

Results

Of the 155 participants (median [IQR] age, 43 [34-54] years; 92 [59%] females), 102 were randomized to the NMV/r group and 53 to the PBO/r group. Nearly all participants (n = 153) had received the primary series for COVID-19 vaccination. Mean (SD) time between index SARS-CoV-2 infection and randomization was 17.5 (9.1) months. There was no statistically significant difference in the model-derived severity outcome pooled across the 6 core symptoms at 10 weeks between the NMV/r and PBO/r groups. No statistically significant between-group differences were found at 10 weeks in the Patient Global Impression of Severity or Patient Global Impression of Change scores, summative symptom scores, and change from baseline to 10 weeks in PROMIS fatigue, dyspnea, cognitive function, and physical function measures. Adverse event rates were similar in NMV/r and PBO/r groups and mostly of low grade.

Conclusions and Relevance

The results of this randomized clinical trial showed that a 15-day course of NMV/r in a population of patients with PASC was generally safe but did not demonstrate a significant benefit for improving select PASC symptoms in a mostly vaccinated cohort with protracted symptom duration. Further studies are needed to determine the role of antivirals in the treatment of PASC.

Trial Registration

ClinicalTrials.gov Identifier: NCT05576662.

Analysis of Nonconcurrent Controls in Adaptive Platform Trials: Separating Randomized and Nonrandomized Information

Adaptive platform trials allow treatments to be added or dropped during the study, meaning that the control arm may be active for longer than the experimental arms. This leads to nonconcurrent controls, which provide nonrandomized information that may increase efficiency but may introduce bias from temporal confounding and other factors. Various methods have been proposed to control confounding from nonconcurrent controls, based on adjusting for time period. We demonstrate that time adjustment is insufficient to prevent bias in some circumstances where nonconcurrent controls are present in adaptive platform trials, and we propose a more general analytical framework that accounts for nonconcurrent controls in such circumstances. We begin by defining nonconcurrent controls using the concept of a concurrently randomized cohort, which is a subgroup of participants all subject to the same randomized design. We then use cohort adjustment rather than time adjustment. Due to flexibilities in platform trials, more than one randomized design may be in force at any time, meaning that cohort-adjusted and time-adjusted analyses may be quite different. Using simulation studies, we demonstrate that time-adjusted analyses may be biased while cohort-adjusted analyses remove this bias. We also demonstrate that the cohort-adjusted analysis may be interpreted as a synthesis of randomized and indirect comparisons analogous to mixed treatment comparisons in network meta-analysis. This allows the use of network meta-analysis methodology to separate the randomized and nonrandomized components and to assess their consistency. Whenever nonconcurrent controls are used in platform trials, the separate randomized and indirect contributions to the treatment effect should be presented.

High-dose intravenous immunoglobulin versus albumin 4% in paediatric toxic shock syndrome: a randomised controlled feasibility study

PURPOSE

Toxic shock syndrome (TSS) is a rare disease responsible for significant morbidity and mortality. Intravenous immunoglobulin (IG) therapy in paediatric TSS could improve shock and organ failure, but more consistent efficacy and safety data are needed. Our objective was to determine whether a randomised clinical trial (RCT) assessing intravenous IG in TSS in children is feasible.

METHODS

We performed a multicentre, feasibility, double-blind RCT assessing efficacy of high-dose intravenous IG versus albumin 4% (control group) within the first 12 hours of shock onset. Included patients were aged above 1 month and below 18 years with suspected TSS and septic shock. Feasibility was assessed by measuring inclusion rate, protocol compliance and missing data regarding death and the Pediatric Logistic Organ Dysfunction-2 (PELOD-2) Score. Other secondary clinical outcomes were evaluated during hospital stay, at 60 day and 1 year.

RESULTS

28 patients, admitted in 6 paediatric intensive care units during 36 consecutive months and followed for 1 year, received the allocated treatment: 13 in intravenous IG group, 15 in control group. The median age was 10.6 years and the sex ratio was 1. Inclusion rate was above 50%, protocol deviations were below 30% and missing data regarding death and PELOD-2 Score below 10%. No difference concerning secondary clinical outcomes between groups was observed, and more adverse events were reported in the control group.

CONCLUSION

It seems to be feasible to conduct an RCT assessing intravenous IG efficacy and safety in paediatric TSS but must be realised internationally, with choice of a clinically relevant endpoint and a specific design in order to be realistic.

TRIAL REGISTRATION NUMBER

NCT02219165.

Platform trial design for neurofibromatosis type 1, NF2-related schwannomatosis and non-NF2-related schwannomatosis: A potential model for rare diseases

Background

Neurofibromatosis type 1, NF2-related schwannomatosis and non-NF2-related schwannomatosis (grouped under the abbreviation "NF") are rare hereditary tumor predisposition syndromes. Due to the low prevalence, variability in the range, and severity of manifestations, as well as limited treatment options, these conditions require innovative trial designs to accelerate the development of new treatments.

Methods

Within European Patient-Centric Clinical Trial Platforms (EU-PEARL), we designed 2 platform-basket trials in NF. The trials were designed by a team of multidisciplinary NF experts and trial methodology experts.

Results

The trial will consist of an observational and a treatment period. The observational period will serve as a longitudinal natural history study. The platform trial design and randomization to a sequence of available interventions allow for the addition of interventions during the trial. If a drug does not meet the predetermined efficacy endpoint or reveals unacceptable toxicities, participants may stop treatment on that arm and re-enter the observational period, where they can be re-randomized to a different treatment arm if eligible. Intervention-specific eligibility criteria and endpoints are listed in intervention-specific-appendices, allowing the flexibility and adaptability needed for highly variable and rare conditions like NF.

Conclusions

These innovative platform-basket trials for NF may serve as a model for other rare diseases, as they will enhance the chance of identifying beneficial treatments through optimal learning from a small number of patients. The goal of these trials is to identify beneficial treatments for NF more rapidly and at a lower cost than traditional, single-agent clinical trials.

Modulation of multiple sclerosis risk and pathogenesis by the gut microbiota: Complex interactions between host genetics, bacterial metabolism, and diet

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system, affecting nearly 2 million people worldwide. The etiology of MS is multifactorial: Approximately 30% of the MS risk is genetic, which implies that the remaining ~70% is environmental, with a number of factors proposed. One recently implicated risk factor for MS is the composition of the gut microbiome. Numerous case-control studies have identified changes in gut microbiota composition of people with MS (pwMS) compared with healthy control individuals, and more recent studies in animal models have begun to identify the causative microbes and underlying mechanisms. Here, we review some of these mechanisms, with a specific focus on the role of host genetic variation, dietary inputs, and gut microbial metabolism, with a particular emphasis on short-chain fatty acid and tryptophan metabolism. We put forward a model where, in an individual genetically susceptible to MS, the gut microbiota and diet can synergize as potent environmental modifiers of disease risk and possibly progression, with diet-dependent gut microbial metabolites serving as a key mechanism. We also propose that specific microbial taxa may have divergent effects in individuals carrying distinct variants of MS risk alleles or other polymorphisms, as a consequence of host gene-by-gut microbiota interactions. Finally, we also propose that the effects of specific microbial taxa, especially those that exert their effects through metabolites, are highly dependent on the host dietary intake. What emerges is a complex multifaceted interaction that has been challenging to disentangle in human studies, contributing to the divergence of findings across heterogeneous cohorts with differing geography, dietary preferences, and genetics. Nonetheless, this provides a complex and individualized, yet tractable, model of how the gut microbiota regulate susceptibility to MS, and potentially progression of this disease. Thus, we conclude that prophylactic or therapeutic modulation of the gut microbiome to prevent or treat MS will require a careful and personalized consideration of host genetics, baseline gut microbiota composition, and dietary inputs.

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 multi-interventional trial platform to improve patient care for fibrotic interstitial lung diseases

BACKGROUND

Fibrotic interstitial lung diseases (fILDs) are a heterogeneous group of lung diseases associated with significant morbidity and mortality. Despite a large increase in the number of clinical trials in the last 10 years, current regulatory-approved management approaches are limited to two therapies that prevent the progression of fibrosis. The drug development pipeline is long and there is an urgent need to accelerate this process. This manuscript introduces the concept and design of an innovative research approach to drug development in fILD: a global Randomised Embedded Multifactorial Adaptive Platform in fILD (REMAP-ILD).

METHODS

Description of the REMAP-ILD concept and design: the specific terminology, design characteristics (multifactorial, adaptive features, statistical approach), target population, interventions, outcomes, mission and values, and organisational structure.

RESULTS

The target population will be adult patients with fILD, and the primary outcome will be a disease progression model incorporating forced vital capacity and mortality over 12 months. Responsive adaptive randomisation, prespecified thresholds for success and futility will be used to assess the effectiveness and safety of interventions. REMAP-ILD embraces the core values of diversity, equity, and inclusion for patients and researchers, and prioritises an open-science approach to data sharing and dissemination of results.

CONCLUSION

By using an innovative and efficient adaptive multi-interventional trial platform design, we aim to accelerate and improve care for patients with fILD. Through worldwide collaboration, novel analytical methodology and pragmatic trial delivery, REMAP-ILD aims to overcome major limitations associated with conventional randomised controlled trial approaches to rapidly improve the care of people living with fILD.

The Integration of Clinical Trials With the Practice of Medicine: Repairing a House Divided

Importance

Optimal health care delivery, both now and in the future, requires a continuous loop of knowledge generation, dissemination, and uptake on how best to provide care, not just determining what interventions work but also how best to ensure they are provided to those who need them. The randomized clinical trial (RCT) is the most rigorous instrument to determine what works in health care. However, major issues with both the clinical trials enterprise and the lack of integration of clinical trials with health care delivery compromise medicine's ability to best serve society.

Observations

In most resource-rich countries, the clinical trials and health care delivery enterprises function as separate entities, with siloed goals, infrastructure, and incentives. Consequently, RCTs are often poorly relevant and responsive to the needs of patients and those responsible for care delivery. At the same time, health care delivery systems are often disengaged from clinical trials and fail to rapidly incorporate knowledge generated from RCTs into practice. Though longstanding, these issues are more pressing given the lessons learned from the COVID-19 pandemic, heightened awareness of the disproportionate impact of poor access to optimal care on vulnerable populations, and the unprecedented opportunity for improvement offered by the digital revolution in health care. Four major areas must be improved. First, especially in the US, greater clarity is required to ensure appropriate regulation and oversight of implementation science, quality improvement, embedded clinical trials, and learning health systems. Second, greater adoption is required of study designs that improve statistical and logistical efficiency and lower the burden on participants and clinicians, allowing trials to be smarter, safer, and faster. Third, RCTs could be considerably more responsive and efficient if they were better integrated with electronic health records. However, this advance first requires greater adoption of standards and processes designed to ensure health data are adequately reliable and accurate and capable of being transferred responsibly and efficiently across platforms and organizations. Fourth, tackling the problems described above requires alignment of stakeholders in the clinical trials and health care delivery enterprises through financial and nonfinancial incentives, which could be enabled by new legislation. Solutions exist for each of these problems, and there are examples of success for each, but there is a failure to implement at adequate scale.

Conclusions and Relevance

The gulf between current care and that which could be delivered has arguably never been wider. A key contributor is that the 2 limbs of knowledge generation and implementation-the clinical trials and health care delivery enterprises-operate as a house divided. Better integration of these 2 worlds is key to accelerated improvement in health care delivery.

Bringing platform trials closer to reality by enabling with digital research environment (DRE) connectivity

Platform trials are generally regarded as an innovative approach to address clinical valuation of early stage candidates, regardless of modality as the evidence evolves. As a type of randomized clinical trial (RCT) design construct in which multiple interventions are evaluated concurrently against a common control group allowing new interventions to be added and the control group to be updated throughout the trial, they provide a dynamic and efficient mechanism to compare and potentially discriminate new treatment candidates. Their recent use in the evaluation of new therapies for COVID-19 has spurred new interest in the approach. The paucity of platform trials is less influenced by the novelty and operational requirements as opposed to concerns regarding the sharing of intellectual property (IP) and the lack of infrastructure to operationalize the conduct in the context of IP and data sharing. We provide a mechanism how this can be accomplished through the use of a digital research environment (DRE) providing a safe and secure platform for clinical researchers, quantitative and physician scientists to analyze and develop tools (e.g., models) on sensitive data with the confidence that the data and models developed are protected. A DRE, in this context, expands on the concept of a trusted research environment (TRE) by providing remote access to data alongside tools for analysis in a securely controlled workspace, while allowing data and tools to be findable, accessible, interoperable, and reusable (FAIR), version-controlled, and dynamically grow in size or quality as a result of each treatment evaluated in the trial.

Novel approaches to enable equitable access to monoclonal antibodies in low- and middle-income countries

Monoclonal antibodies (mAbs) are revolutionizing management of non-communicable diseases in high-income countries and are increasingly being advanced for a range of infectious diseases (IDs). However, access to existing mAbs is limited in low- and middle-income countries (LMICs), and investment in developing fit-for-purpose mAbs for IDs that disproportionately affect LMICs has been limited. Underlying these access barriers are systemic challenges, including a lack of commercial incentives to target LMIC markets and complexity in manufacturing and regulatory processes. Novel strategies are needed to overcome systemic access barriers for mAbs. We outline key areas where new approaches could address these barriers, based on a multistakeholder consultation in March 2023. Three disease-market archetypes are identified to guide thinking about business models tailored to different contexts. New business models are needed to incentivize development and manufacturing of ID mAbs and to ensure mAbs are optimized with a target product profile and cost of goods that enable use in diverse LMIC settings. Lessons can be applied from voluntary licensing strategies and product development partnerships that have shown success in catalysing development and affordable supply for a range of infectious diseases. Technology transfer will be key to expand LMIC research and manufacturing capacity and to enable sustainable and diversified supply. Improved market intelligence, demand aggregation mechanisms, and portfolio-based manufacturing models could be used to de-risk commercial investment and establish a sustainable manufacturing ecosystem for affordable mAbs. Novel regulatory approaches and robust technology transfer may reduce data requirements and timelines for biosimilar approvals. Trailblazer products, with coordinated "end-to-end" support from funders, can demonstrate proof of concept for pathways to accessible mAbs across a broader range of LMICs. Research funders; local, regional, global health agencies; and, private sector partners should commit to implementing innovative partnerships and end-to-end strategies that enable equitable access to mAbs for infectious diseases in LMICs.

Home-monitoring for neovascular age-related macular degeneration in older adults within the UK: the MONARCH diagnostic accuracy study

Background

Most neovascular age-related macular degeneration treatments involve long-term follow-up of disease activity. Home monitoring would reduce the burden on patients and those they depend on for transport, and release clinic appointments for other patients. The study aimed to evaluate three home-monitoring tests for patients to use to detect active neovascular age-related macular degeneration compared with diagnosing active neovascular age-related macular degeneration by hospital follow-up.

Objectives

There were five objectives: Estimate the accuracy of three home-monitoring tests to detect active neovascular age-related macular degeneration. Determine the acceptability of home monitoring to patients and carers and adherence to home monitoring. Explore whether inequalities exist in recruitment, participants' ability to self-test and their adherence to weekly testing during follow-up. Provide pilot data about the accuracy of home monitoring to detect conversion to neovascular age-related macular degeneration in fellow eyes of patients with unilateral neovascular age-related macular degeneration. Describe challenges experienced when implementing home-monitoring tests.

Design

Diagnostic test accuracy cohort study, stratified by time since starting treatment.

Setting

Six United Kingdom Hospital Eye Service macular clinics (Belfast, Liverpool, Moorfields, James Paget, Southampton, Gloucester).

Participants

Patients with at least one study eye being monitored by hospital follow-up.

Reference standard

Detection of active neovascular age-related macular degeneration by an ophthalmologist at hospital follow-up.

Index tests

KeepSight Journal: paper-based near-vision tests presented as word puzzles. MyVisionTrack®: electronic test, viewed on a tablet device. MultiBit: electronic test, viewed on a tablet device. Participants provided test scores weekly. Raw scores between hospital follow-ups were summarised as averages.

Results

Two hundred and ninety-seven patients (mean age 74.9 years) took part. At least one hospital follow-up was available for 317 study eyes, including 9 second eyes that became eligible during follow-up, in 261 participants (1549 complete visits). Median testing frequency was three times/month. Estimated areas under receiver operating curves were < 0.6 for all index tests, and only KeepSight Journal summary score was significantly associated with the lesion activity (odds ratio = 3.48, 95% confidence interval 1.09 to 11.13, p = 0.036). Older age and worse deprivation for home address were associated with lower participation (χ2 = 50.5 and 24.3, respectively, p < 0.001) but not ability or adherence to self-testing. Areas under receiver operating curves appeared higher for conversion of fellow eyes to neovascular age-related macular degeneration (0.85 for KeepSight Journal) but were estimated with less precision. Almost half of participants called a study helpline, most often due to inability to test electronically.

Limitations

Pre-specified sample size not met; participants' difficulties using the devices; electronic tests not always available.

Conclusions

No index test provided adequate test accuracy to identify lesion diagnosed as active in follow-up clinics. If used to detect conversion, patients would still need to be monitored at hospital. Associations of older age and worse deprivation with study participation highlight the potential for inequities with such interventions. Provision of reliable electronic testing was challenging.

Future work

Future studies evaluating similar technologies should consider: Independent monitoring with clear stopping rules based on test performance. Deployment of apps on patients' own devices since providing devices did not reduce inequalities in participation and complicated home testing. Alternative methods to summarise multiple scores over the period preceding a follow-up.

Trial registration

This trial is registered as ISRCTN79058224.

Funding

This award was funded by the National Institute of Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 15/97/02) and is published in full in Health Technology Assessment; Vol. 28, No. 32. See the NIHR Funding and Awards website for further award information.

Challenges and opportunities in cancer immunotherapy: a Society for Immunotherapy of Cancer (SITC) strategic vision

Cancer immunotherapy has flourished over the last 10-15 years, transforming the practice of oncology and providing long-term clinical benefit to some patients. During this time, three distinct classes of immune checkpoint inhibitors, chimeric antigen receptor-T cell therapies specific for two targets, and two distinct classes of bispecific T cell engagers, a vaccine, and an oncolytic virus have joined cytokines as a standard of cancer care. At the same time, scientific progress has delivered vast amounts of new knowledge. For example, advances in technologies such as single-cell sequencing and spatial transcriptomics have provided deep insights into the immunobiology of the tumor microenvironment. With this rapid clinical and scientific progress, the field of cancer immunotherapy is currently at a critical inflection point, with potential for exponential growth over the next decade. Recognizing this, the Society for Immunotherapy of Cancer convened a diverse group of experts in cancer immunotherapy representing academia, the pharmaceutical and biotechnology industries, patient advocacy, and the regulatory community to identify current opportunities and challenges with the goal of prioritizing areas with the highest potential for clinical impact. The consensus group identified seven high-priority areas of current opportunity for the field: mechanisms of antitumor activity and toxicity; mechanisms of drug resistance; biomarkers and biospecimens; unique aspects of novel therapeutics; host and environmental interactions; premalignant immunity, immune interception, and immunoprevention; and clinical trial design, endpoints, and conduct. Additionally, potential roadblocks to progress were discussed, and several topics were identified as cross-cutting tools for optimization, each with potential to impact multiple scientific priority areas. These cross-cutting tools include preclinical models, data curation and sharing, biopsies and biospecimens, diversification of funding sources, definitions and standards, and patient engagement. Finally, three key guiding principles were identified that will both optimize and maximize progress in the field. These include engaging the patient community; cultivating diversity, equity, inclusion, and accessibility; and leveraging the power of artificial intelligence to accelerate progress. Here, we present the outcomes of these discussions as a strategic vision to galvanize the field for the next decade of exponential progress in cancer immunotherapy.

How Much More Efficient Are Adaptive Platform Trials Than Multiple Stand-Alone Trials? A Comprehensive Simulation Study for Streamlining Drug Development During a Pandemic

With the coronavirus disease 2019 (COVID-19) pandemic, there is growing interest in utilizing adaptive platform clinical trials (APTs), in which multiple drugs are compared with a single common control group, such as a placebo or standard-of-care group. APTs evaluate several drugs for one disease and accept additions or exclusions of drugs as the trials progress; however, little is known about the efficiency of APTs over multiple stand-alone trials. In this study, we simulated the total development period, total sample size, and statistical operating characteristics of APTs and multiple stand-alone trials in drug development settings for hospitalized patients with COVID-19. Simulation studies using selected scenarios reconfirmed several findings regarding the efficiency of APTs. The APTs without staggered addition of drugs showed a shorter total development period than stand-alone trials, but the difference rapidly diminished if patient's enrollment was accelerated during the trials owing to the spread of infection. APTs with staggered addition of drugs still have the possibility of reducing the total development period compared with multiple stand-alone trials in some cases. Our study demonstrated that APTs could improve efficiency relative to multiple stand-alone trials regarding the total development period and total sample size without undermining statistical validity; however, this improvement varies depending on the speed of patient enrollment, sample size, presence/absence of family-wise error rate adjustment, allocation ratio between drug and placebo groups, and interval of staggered addition of drugs. Given the complexity of planning and implementing APT, the decision to implement APT during a pandemic must be made carefully.

A Systematic Review of Potential Biomarkers for Bacterial Burden and Treatment Efficacy Assessment in Tuberculosis Platform-Based Clinical Trials

Adaptive platform trials can be more efficient than classic trials for developing new treatments. Moving from culture-based to simpler- or faster-to-measure biomarkers as efficacy surrogates may enhance this advantage. We performed a systematic review of treatment efficacy biomarkers in adults with tuberculosis. Platform trials can span different development phases. We grouped biomarkers as: α, bacterial load estimates used in phase 2a trials; β, early and end-of treatment end points, phase 2b-c trials; γ, posttreatment or trial-level estimates, phase 2c-3 trials. We considered as analysis unit (biomarker entry) each combination of biomarker, predicted outcome, and their respective measurement times or intervals. Performance metrics included: sensitivity, specificity, area under the receiver-operator curve (AUC), and correlation measures, and classified as poor, promising, or good. Eighty-six studies included 22 864 participants. From 1356 biomarker entries, 318 were reported with the performance metrics of interest, with 103 promising and 41 good predictors. Group results were: α, mycobacterial RNA and lipoarabinomannan (LAM) in sputum, and host metabolites in urine; β, mycobacterial RNA and host transcriptomic or cytokine signatures for early treatment response; and γ, host transcriptomics for recurrence. A combination of biomarkers from different categories could help in designing more efficient platform trials. Efforts to develop efficacy surrogates should be better coordinated.

Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review

Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatments, interventions, and medical procedures. The Bayesian framework offers a unique advantage over the classical framework, especially when incorporating prior information into a new trial with quality external data, such as historical data or another source of co-data. In recent years, there has been a significant increase in regulatory submissions using Bayesian statistics due to its flexibility and ability to provide valuable insights for decision-making, addressing the modern complexity of clinical trials where frequentist trials are inadequate. For regulatory submissions, companies often need to consider the frequentist operating characteristics of the Bayesian analysis strategy, regardless of the design complexity. In particular, the focus is on the frequentist type I error rate and power for all realistic alternatives. This tutorial review aims to provide a comprehensive overview of the use of Bayesian statistics in sample size determination, control of type I error rate, multiplicity adjustments, external data borrowing, etc., in the regulatory environment of clinical trials. Fundamental concepts of Bayesian sample size determination and illustrative examples are provided to serve as a valuable resource for researchers, clinicians, and statisticians seeking to develop more complex and innovative designs.

Leveraging external control data in the design and analysis of neuro-oncology trials: Pearls and perils

BACKGROUND

Randomized controlled trials have been the gold standard for evaluating medical treatments for many decades but they are often criticized for requiring large sample sizes. Given the urgent need for better therapies for glioblastoma, it has been argued that data collected from patients treated with the standard regimen can provide high-quality external control data to supplement or replace concurrent control arm in future glioblastoma trials.

METHODS

In this article, we provide an in-depth appraisal of the use of external control data in the context of neuro-oncology trials. We describe several clinical trial designs with particular attention to how external information is utilized and address common fallacies that may lead to inappropriate adoptions of external control data.

RESULTS

Using 2 completed glioblastoma trials, we illustrate the use of an assessment tool that lays out a blueprint for assembling a high-quality external control data set. Using statistical simulations, we draw caution from scenarios where these approaches can fall short on controlling the type I error rate.

CONCLUSIONS

While this approach may hold promise in generating informative data in certain settings, this sense of optimism should be tampered with a healthy dose of skepticism due to a myriad of design and analysis challenges articulated in this review. Importantly, careful planning is key to its successful implementation.

Operational complexities in international clinical trials: a systematic review of challenges and proposed solutions

OBJECTIVE

International trials can be challenging to operationalise due to incompatibilities between country-specific policies and infrastructures. The aim of this systematic review was to identify the operational complexities of conducting international trials and identify potential solutions for overcoming them.

DESIGN

Systematic review.

DATA SOURCES

Medline, Embase and Health Management Information Consortium were searched from 2006 to 30 January 2023.

ELIGIBILITY CRITERIA

All studies reporting operational challenges (eg, site selection, trial management, intervention management, data management) of conducting international trials were included.

DATA EXTRACTION AND SYNTHESIS

Search results were independently screened by at least two reviewers and data were extracted into a proforma.

RESULTS

38 studies (35 RCTs, 2 reports and 1 qualitative study) fulfilled the inclusion criteria. The median sample size was 1202 (IQR 332-4056) and median number of sites was 40 (IQR 13-78). 88.6% of studies had an academic sponsor and 80% were funded through government sources. Operational complexities were particularly reported during trial set-up due to lack of harmonisation in regulatory approvals and in relation to sponsorship structure, with associated budgetary impacts. Additional challenges included site selection, staff training, lengthy contract negotiations, site monitoring, communication, trial oversight, recruitment, data management, drug procurement and distribution, pharmacy involvement and biospecimen processing and transport.

CONCLUSIONS

International collaborative trials are valuable in cases where recruitment may be difficult, diversifying participation and applicability. However, multiple operational and regulatory challenges are encountered when implementing a trial in multiple countries. Careful planning and communication between trials units and investigators, with an emphasis on establishing adequately resourced cross-border sponsorship structures and regulatory approvals, may help to overcome these barriers and realise the benefits of the approach. OPEN SCIENCE FRAMEWORK REGISTRATION NUMBER: osf-registrations-yvtjb-v1.

Characteristics, Progression, and Output of Randomized Platform Trials: A Systematic Review

Importance

Platform trials have become increasingly common, and evidence is needed to determine how this trial design is actually applied in current research practice.

Objective

To determine the characteristics, progression, and output of randomized platform trials.

Evidence Review

In this systematic review of randomized platform trials, Medline, Embase, Scopus, trial registries, gray literature, and preprint servers were searched, and citation tracking was performed in July 2022. Investigators were contacted in February 2023 to confirm data accuracy and to provide updated information on the status of platform trial arms. Randomized platform trials were eligible if they explicitly planned to add or drop arms. Data were extracted in duplicate from protocols, publications, websites, and registry entries. For each platform trial, design features such as the use of a common control arm, use of nonconcurrent control data, statistical framework, adjustment for multiplicity, and use of additional adaptive design features were collected. Progression and output of each platform trial were determined by the recruitment status of individual arms, the number of arms added or dropped, and the availability of results for each intervention arm.

Findings

The search identified 127 randomized platform trials with a total of 823 arms; most trials were conducted in the field of oncology (57 [44.9%]) and COVID-19 (45 [35.4%]). After a more than twofold increase in the initiation of new platform trials at the beginning of the COVID-19 pandemic, the number of platform trials has since declined. Platform trial features were often not reported (not reported: nonconcurrent control, 61 of 127 [48.0%]; multiplicity adjustment for arms, 98 of 127 [77.2%]; statistical framework, 37 of 127 [29.1%]). Adaptive design features were only used by half the studies (63 of 127 [49.6%]). Results were available for 65.2% of closed arms (230 of 353). Premature closure of platform trial arms due to recruitment problems was infrequent (5 of 353 [1.4%]).

Conclusions and Relevance

This systematic review found that platform trials were initiated most frequently during the COVID-19 pandemic and declined thereafter. The reporting of platform features and the availability of results were insufficient. Premature arm closure for poor recruitment was rare.

The Rise of Adaptive Platform Trials in Critical Care

As durable learning research systems, adaptive platform trials represent a transformative new approach to accelerating clinical evaluation and discovery in critical care. This Perspective provides a brief introduction to the concept of adaptive platform trials, describes several established and emerging platforms in critical care, and surveys some opportunities and challenges for their implementation and impact.

Flex-IT! Applying "Platform Trials" Methodology to Immunotherapy for Food Allergy in Research and Clinical Practice

There is an increasing trend in the management of food allergy toward active treatment using allergen immunotherapy (AIT). Although AIT is efficacious, treatment-related adverse events are common, particularly with oral immunotherapy in those with high levels of allergen-specific IgE sensitization. In clinical practice, these adverse events inevitably create challenges: clinicians and patients routinely face decisions whether to alter the dose itself, the frequency of dosing, and the pace of escalation, or indeed discontinue AIT altogether. Flexibility is therefore needed to adapt treatment, particularly in clinical practice, so that participants are "treated-to-target." For example, this may entail a significant change in the dosing protocol or even switching from one route of administration to another in response to frequent adverse events. We refer to this approach as flexible immunotherapy. However, there is little evidence to inform clinicians as to what changes to treatment are most likely to result in treatment success. Classical clinical trials rely, by necessity, on relatively rigid updosing protocols. To provide an evidence base to optimize AIT, the food allergy community should adopt adaptive platform trials, where a "master protocol" facilitates more efficient evaluation, including longer-term outcomes of multiple interventions. Within a single clinical trial, participants are able to switch between different treatment arms; interventions can be added or dropped without compromising the integrity of the trial. Developing platform trials for food AIT may initially be costly, but they represent a significant opportunity to grow the evidence base (with respect to both treatment outcomes and biomarker discovery) at scale. In addition, they could help understand longitudinal disease trajectories that are difficult to study in clinical trials for food allergy due to the time needed to demonstrate changes in efficacy. Finally, their adoption would achieve greater collaboration and consistency in approaches to proactive management of food allergy in routine clinical practice. As a community, we need to actively pursue this with funders and established research collaborations to deliver the very best outcomes for our patients and their families.

Advanced and alternative research methods for the acute care surgeon scientist

Clinical research has evolved significantly over the last few decades to include many advanced and alternative study designs to answer unique questions. Recognizing a potential knowledge gap, the AAST Associate Member Council and Educational Development Committee created a research course at the 2022 Annual Meeting in Chicago to introduce junior researchers to these methodologies. This manuscript presents a summary of this AAST Annual Meeting session, and reviews topics including hierarchical modeling, geospatial analysis, patient-centered outcomes research, mixed methods designs, and negotiating complex issues in multicenter trials.

Pulmonary Fibrosis Stakeholder Summit: A Joint NHLBI, Three Lakes Foundation, and Pulmonary Fibrosis Foundation Workshop Report

Despite progress in elucidation of disease mechanisms, identification of risk factors, biomarker discovery, and the approval of two medications to slow lung function decline in idiopathic pulmonary fibrosis and one medication to slow lung function decline in progressive pulmonary fibrosis, pulmonary fibrosis remains a disease with a high morbidity and mortality. In recognition of the need to catalyze ongoing advances and collaboration in the field of pulmonary fibrosis, the NHLBI, the Three Lakes Foundation, and the Pulmonary Fibrosis Foundation hosted the Pulmonary Fibrosis Stakeholder Summit on November 8-9, 2022. This workshop was held virtually and was organized into three topic areas: 1) novel models and research tools to better study pulmonary fibrosis and uncover new therapies, 2) early disease risk factors and methods to improve diagnosis, and 3) innovative approaches toward clinical trial design for pulmonary fibrosis. In this workshop report, we summarize the content of the presentations and discussions, enumerating research opportunities for advancing our understanding of the pathogenesis, treatment, and outcomes of pulmonary fibrosis.

Pancreatic Cancer Action Network's SPARK: A Cloud-Based Patient Health Data and Analytics Platform for Pancreatic Cancer

PURPOSE

Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use.

MATERIALS AND METHODS

The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis.

RESULTS

Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service.

CONCLUSION

The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.

Design and Execution of Clinical Trials in the Cardiac Intensive Care Unit

Clinical practice in the contemporary cardiac intensive care unit (CICU) has evolved significantly over the last several decades. With more frequent multisystem organ failure, increasing use of advanced respiratory support, and the advent of new mechanical circulatory support platforms, clinicians in the CICU are increasingly managing patients with complex comorbid disease in addition to their high-acuity cardiovascular illnesses. Here, the authors discuss challenges associated with traditional trial design in the CICU setting and review novel clinical trial designs that may facilitate better evidence generation in the CICU.

The critical need to accelerate cerebral palsy research with consumer engagement, global networks, and adaptive designs

The prevalence of cerebral palsy (CP) varies globally, with higher rates and burden of disease in low- and middle-income countries. CP is a lifelong condition with no cure, presenting diverse challenges such as motor impairment, epilepsy, and mental health disorders. Research progress has been made but more is needed, especially given consumer demands for faster advancements and improvements in the scientific evidence base for interventions. This paper explores three strategies to accelerate CP research: consumer engagement, global clinical trial networks, and adaptive designs. Consumer engagement involving individuals with lived experience enhances research outcomes. Global clinical trial networks provide efficiency through larger and more diverse participant pools. Adaptive designs, unlike traditional randomized controlled trials, allow real-time modifications based on interim analyses, potentially answering complex questions more efficiently. The establishment of a CP Global Clinical Trials Network, integrating consumer engagement, global collaboration, and adaptive designs, marks a paradigm shift. The Network aims to address consumer-set research priorities. While challenges like ethical considerations and capacity building exist, the potential benefits for consumers, clinicians, researchers, and funding bodies are substantial. This paper underscores the urgency of transforming CP research methodologies for quicker translation of novel treatments into clinical practice to improve quality of life for those with CP.

Inaugural Results of the Individualized Screening Trial of Innovative Glioblastoma Therapy: A Phase II Platform Trial for Newly Diagnosed Glioblastoma Using Bayesian Adaptive Randomization

PURPOSE

The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial that uses response adaptive randomization and genomic profiling to efficiently identify novel therapies for phase III testing. Three initial experimental arms (abemaciclib [a cyclin-dependent kinase [CDK]4/6 inhibitor], neratinib [an epidermal growth factor receptor [EGFR]/human epidermal growth factor receptor 2 inhibitor], and CC-115 [a deoxyribonucleic acid-dependent protein kinase/mammalian target of rapamycin inhibitor]) were simultaneously evaluated against a common control arm. We report the results for each arm and examine the feasibility and conduct of the adaptive platform design.

PATIENTS AND METHODS

Patients with newly diagnosed O6-methylguanine-DNA methyltransferase-unmethylated glioblastoma were eligible if they had tumor genotyping to identify prespecified biomarker subpopulations of dominant glioblastoma signaling pathways (EGFR, phosphatidylinositol 3-kinase, and CDK). Initial random assignment was 1:1:1:1 between control (radiation therapy and temozolomide) and the experimental arms. Subsequent Bayesian adaptive randomization was incorporated on the basis of biomarker-specific progression-free survival (PFS) data. The primary end point was overall survival (OS), and one-sided P values are reported. The trial is registered with ClinicalTrials.gov (identifier: NCT02977780).

RESULTS

Two hundred thirty-seven patients were treated (71 control; 73 abemaciclib; 81 neratinib; 12 CC-115) in years 2017-2021. Abemaciclib and neratinib were well tolerated, but CC-115 was associated with ≥ grade 3 treatment-related toxicity in 58% of patients. PFS was significantly longer with abemaciclib (hazard ratio [HR], 0.72; 95% CI, 0.49 to 1.06; one-sided P = .046) and neratinib (HR, 0.72; 95% CI, 0.50 to 1.02; one-sided P = .033) relative to the control arm but there was no PFS benefit with CC-115 (one-sided P = .523). None of the experimental therapies demonstrated a significant OS benefit (P > .05).

CONCLUSION

The INSIGhT design enabled efficient simultaneous testing of three experimental agents using a shared control arm and adaptive randomization. Two investigational arms had superior PFS compared with the control arm, but none demonstrated an OS benefit. The INSIGhT design may promote improved and more efficient therapeutic discovery in glioblastoma. New arms have been added to the trial.

Ethics Along the Continuum of Research Involving Persons with Disorders of Consciousness

Interest in disorders of consciousness (DoC) has grown substantially over the past decade and has illuminated the importance of improving understanding of DoC biology; care needs (use of monitoring, performance of interventions, and provision of emotional support); treatment options to promote recovery; and outcome prediction. Exploration of these topics requires awareness of numerous ethics considerations related to rights and resources. The Curing Coma Campaign Ethics Working Group used its expertise in neurocritical care, neuropalliative care, neuroethics, neuroscience, philosophy, and research to formulate an informal review of ethics considerations along the continuum of research involving persons with DoC related to the following: (1) study design; (2) comparison of risks versus benefits; (3) selection of inclusion and exclusion criteria; (4) screening, recruitment, and enrollment; (5) consent; (6) data protection; (7) disclosure of results to surrogates and/or legally authorized representatives; (8) translation of research into practice; (9) identification and management of conflicts of interest; (10) equity and resource availability; and (11) inclusion of minors with DoC in research. Awareness of these ethics considerations when planning and performing research involving persons with DoC will ensure that the participant rights are respected while maximizing the impact and meaningfulness of the research, interpretation of outcomes, and communication of results.

Novel Immunotherapies and Combinations: The Future Landscape of Multiple Myeloma Treatment

In multiple myeloma impressive outcomes have improved with the introduction of new therapeutic approaches, mainly those including naked monoclonal antibodies such as daratumumab and isatuximab. However, moving to earlier lines of therapy with effective anti-myeloma drugs led to an increase in the number of patients who developed multi-refractoriness to them early on. Currently, triple- or multi-refractory MM represents an unmet medical need, and their management remains a complicated challenge. The recent approval of new immunotherapeutic approaches such as conjugated monoclonal antibodies, bispecific antibodies, and CAR T cells could be a turning point for these heavily pretreated patients. Nevertheless, several issues regarding their use are unsolved, such as how to select patients for each strategy or how to sequence these therapies within the MM therapeutic landscape. Here we provide an overview of the most recent data about approved conjugated monoclonal antibody belantamab, mafodotin, bispecific antibody teclistamab, and other promising compounds under development, mainly focusing on the ongoing clinical trials with monoclonal antibody combination approaches in advanced and earlier phases of MM treatment.

OptiBreech collaborative care versus standard care for women with a breech-presenting fetus at term: A pilot parallel group randomised trial to evaluate the feasibility of a randomised trial nested within a cohort

OptiBreech collaborative care is a multi-disciplinary care pathway for breech presentation at term, with continuity from a breech specialist midwife, including where chosen, for vaginal breech birth (VBB). Pilot randomised trial using unblinded 1:1 parallel group allocation to OptiBreech versus standard care, within a cohort. Participants were women with a breech-presenting fetus > 33 weeks, at four sites in England, January-June 2022. A two-stage consent process was used. Participants consented to undergo random selection to be offered a 'new care process', with a choice to accept it, or not. Primary objectives were to identify recruitment, acceptance, and attrition rates. Randomisation procedures and potential primary outcomes for a substantive study were also feasibility-tested. 68 women were randomised between January-June 2022. The consent process was acceptable to participants, but randomisation was unacceptable to women who specifically sought OptiBreech care. Two women withdrew due to concerns about sharing personal information. More women planned a VBB when randomised to OptiBreech Care (23.5% vs 0, p = .002, 95% CI = 9.3%,37.8%). Women randomised to OptiBreech care had: lower rates of cephalic presentation at birth (38.2% vs 54.5%), higher rates of vaginal birth (32.4% vs 24.2%), lower rates of in-labour caesarean birth (20.6% vs 36.4%), lower rates of neonatal intensive care (5.9% vs 9.1%), and lower rates of severe neonatal morbidity (2.9% vs 9.1%). Randomisation was stopped on the advice of the steering committee before the planned sample of 104, as lack of access to VBB within standard care prohibited comparison of outcomes. Demand for VBB is sufficient for a cohort study, but comparison of outcomes by 1:1 randomisation is not feasible. OptiBreech care would be best evaluated using stepped wedge cluster randomisation. Funded by the United Kingdom National Institute for Health and Care Research (NIHR300582). Clinical trial registration: ISRCTN 14521381.

Translational Challenges and Prospective Solutions in the Implementation of Biomimetic Delivery Systems

Biomimetic delivery systems (BDSs), inspired by the intricate designs of biological systems, have emerged as a groundbreaking paradigm in nanomedicine, offering unparalleled advantages in therapeutic delivery. These systems, encompassing platforms such as liposomes, protein-based nanoparticles, extracellular vesicles, and polysaccharides, are lauded for their targeted delivery, minimized side effects, and enhanced therapeutic outcomes. However, the translation of BDSs from research settings to clinical applications is fraught with challenges, including reproducibility concerns, physiological stability, and rigorous efficacy and safety evaluations. Furthermore, the innovative nature of BDSs demands the reevaluation and evolution of existing regulatory and ethical frameworks. This review provides an overview of BDSs and delves into the multifaceted translational challenges and present emerging solutions, underscored by real-world case studies. Emphasizing the potential of BDSs to redefine healthcare, we advocate for sustained interdisciplinary collaboration and research. As our understanding of biological systems deepens, the future of BDSs in clinical translation appears promising, with a focus on personalized medicine and refined patient-specific delivery systems.

Novel targets for immune-checkpoint inhibition in cancer

Immune-checkpoint inhibitors have revolutionized cancer therapy, yet many patients either do not derive any benefit from treatment or develop a resistance to checkpoint inhibitors. Intrinsic resistance can result from neoantigen depletion, defective antigen presentation, PD-L1 downregulation, immune-checkpoint ligand upregulation, immunosuppression, and tumor cell phenotypic changes. On the other hand, extrinsic resistance involves acquired upregulation of inhibitory immune-checkpoints, leading to T-cell exhaustion. Current data suggest that PD-1, CTLA-4, and LAG-3 upregulation limits the efficacy of single-agent immune-checkpoint inhibitors. Ongoing clinical trials are investigating novel immune-checkpoint targets to avoid or overcome resistance. This review provides an in-depth analysis of the evolving landscape of potentially targetable immune-checkpoints in cancer. We highlight their biology, emphasizing the current understanding of resistance mechanisms and focusing on promising strategies that are under investigation. We also summarize current results and ongoing clinical trials in this crucial field that could once again revolutionize outcomes for cancer patients.

Demonstration of a 'leapfrog' randomized controlled trial as a method to accelerate the development and optimization of psychological interventions

BACKGROUND

The scale of the global mental health burden indicates the inadequacy not only of current treatment options, but also the pace of the standard treatment development process. The 'leapfrog' trial design is a newly-developed simple Bayesian adaptive trial design with potential to accelerate treatment development. A first leapfrog trial was conducted to provide a demonstration and test feasibility, applying the method to a low-intensity internet-delivered intervention targeting anhedonia.

METHODS

At the start of this online, single-blind leapfrog trial, participants self-reporting depression were randomized to an initial control arm comprising four weeks of weekly questionnaires, or one of two versions of a four-week cognitive training intervention, imagery cognitive bias modification (imagery CBM). Intervention arms were compared to control on an ongoing basis via sequential Bayesian analyses, based on a primary outcome of anhedonia at post-intervention. Results were used to eliminate and replace arms, or to promote them to become the control condition based on pre-specified Bayes factor and sample size thresholds. Two further intervention arms (variants of imagery CBM) were added into the trial as it progressed.

RESULTS

N = 188 participants were randomized across the five trial arms. The leapfrog methodology was successfully implemented to identify a 'winning' version of the imagery CBM, i.e. the version most successful in reducing anhedonia, following sequential elimination of the other arms.

CONCLUSIONS

The study demonstrates feasibility of the leapfrog design and provides a foundation for its adoption as a method to accelerate treatment development in mental health. Registration: clinicaltrials.gov, NCT04791137.

Extending the vision of adaptive point-of-care platform trials to improve targeted use of drug therapy regimens: An agile approach in the learning healthcare system toolkit

OBJECTIVES

Improving the targeted use of drug regimens requires robust real-world evidence (RWE) to address the uncertainties that remain regarding their real-world performance following market entry. However, challenges in the current state of RWE production limit its impact on clinical decisions, as well as its operational scalability and sustainability. We propose an adaptive point-of-care (APoC) platform trial as an approach to RWE production that improves both clinical and operational efficiencies.

METHODS AND FINDINGS

We explored design innovations, operational challenges, and infrastructure needs within a multi-stakeholder consortium to evaluate the potential of an APoC platform trial for studying chronic disease treatment regimens using rheumatoid arthritis as a case study. The concept integrates elements from adaptive clinical trials (dynamic treatment regimen strategies) and point-of-care trials (research embedded into routine clinical care) under a perpetual platform infrastructure. The necessary components to implement an APoC platform trial within outpatient settings exist, and present an opportunity for a cross-disciplinary, multi-stakeholder approach. Effective engagement of key stakeholders involved in and impacted by the platform is critical to success. Our collaborative design process identified three high-impact stakeholder-engagement areas: (1) focus on research question(s), (2) design and implementation planning such that it is feasible and fit-for-purpose, and (3) measurement, or meaningful metrics for both clinical (patient outcomes) and system (operational efficiencies) impact.

CONCLUSIONS

An APoC platform trial for rheumatoid arthritis integrating innovative design elements in a scalable infrastructure has the potential to reduce important uncertainties about the real-world performance of biomedical innovations and improve clinical decisions.

How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials

Large volumes of data are collected on critically ill patients, and using data science to extract information from the electronic medical record (EMR) and to inform the design of clinical trials represents a new opportunity in critical care research. Using improved methods of phenotyping critical illnesses, subject identification and enrollment, and targeted treatment group assignment alongside newer trial designs such as adaptive platform trials can increase efficiency while lowering costs. Some tools such as the EMR to automate data collection are already in use. Refinement of data science approaches in critical illness research will allow for better clinical trials and, ultimately, improved patient outcomes.