Increasing the efficiency of clinical trials in neurodegenerative disorders using group sequential trial designs

Development of a conceptual framework for defining trial efficiency

BACKGROUND

Globally, there is a growing focus on efficient trials, yet numerous interpretations have emerged, suggesting a significant heterogeneity in understanding "efficiency" within the trial context. Therefore in this study, we aimed to dissect the multifaceted nature of trial efficiency by establishing a comprehensive conceptual framework for its definition.

OBJECTIVES

To collate diverse perspectives regarding trial efficiency and to achieve consensus on a conceptual framework for defining trial efficiency.

METHODS

From July 2022 to July 2023, we undertook a literature review to identify various terms that have been used to define trial efficiency. We then conducted a modified e-Delphi study, comprising an exploratory open round and a subsequent scoring round to refine and validate the identified items. We recruited a wide range of experts in the global trial community including trialists, funders, sponsors, journal editors and members of the public. Consensus was defined as items rated "without disagreement", measured by the inter-percentile range adjusted for symmetry through the UCLA/RAND approach.

RESULTS

Seventy-eight studies were identified from a literature review, from which we extracted nine terms related to trial efficiency. We then used review findings as exemplars in the Delphi open round. Forty-nine international experts were recruited to the e-Delphi panel. Open round responses resulted in the refinement of the initial nine terms, which were consequently included in the scoring round. We obtained consensus on all nine items: 1) four constructs that collectively define trial efficiency containing scientific efficiency, operational efficiency, statistical efficiency and economic efficiency; and 2) five essential building blocks for efficient trial comprising trial design, trial process, infrastructure, superstructure, and stakeholders.

CONCLUSIONS

This is the first attempt to dissect the concept of trial efficiency into theoretical constructs. Having an agreed definition will allow better trial implementation and facilitate effective communication and decision-making across stakeholders. We also identified essential building blocks that are the cornerstones of an efficient trial. In this pursuit of understanding, we are not only unravelling the complexities of trial efficiency but also laying the groundwork for evaluating the efficiency of an individual trial or a trial system in the future.

Landscape of Phase II Trials in Alzheimer's Disease

BACKGROUND

Drug development in Alzheimer's disease (AD) over the past two decades has had high rates of failure. Novel trial designs, such as adaptive designs, have the potential to improve the efficiency of drug development in AD.

OBJECTIVE

To evaluate the design characteristics, temporal trends, and differences in design between sponsor types in phase II trials of investigational agents in AD.

METHODS

Phase I/II, II, and II/III trials for AD with drug or other biological interventions registered from December 1996 to December 2021 in ClinicalTrials.gov were included. Descriptive statistics were used to summarize trial characteristics. Linear, logistic, and multinomial regression models assessed temporal trends and differences between sponsor types in design characteristics.

RESULTS

Of N = 474 trials identified, randomized parallel group design was the most common design (72%). Only 12 trials (2.5%) used an adaptive design; adaptive features included early stopping rules, model-based dose-finding, adaptive treatment arm selection, and response adaptive randomization. The use of non-randomized parallel-group and open-label single arm designs increased over time. No temporal trend in the use of adaptive design was identified. Trials sponsored by industry only were more likely to use a randomized parallel-group design and have a larger estimated sample size than trials with other sponsor types.

CONCLUSION

Our systematic review showed that very few phase II trials in AD used an adaptive trial design. Innovation and implementation of novel trial designs in AD trials can accelerate the drug development process.

Challenging the Established Order: Innovating Clinical Trials for Amyotrophic Lateral Sclerosis

Development of effective treatments for amyotrophic lateral sclerosis (ALS) has been hampered by disease heterogeneity, a limited understanding of underlying pathophysiology, and methodologic design challenges. We have evaluated 2 major themes in the design of pivotal, phase 3 clinical trials for ALS—(1) patient selection and (2) analytical strategy—and discussed potential solutions with the European Medicines Agency. Several design considerations were assessed using data from 5 placebo-controlled clinical trials (n = 988), 4 population-based cohorts (n = 5,100), and 2,436 placebo-allocated patients from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. The validity of each proposed design modification was confirmed by means of simulation and illustrated for a hypothetical setting. Compared to classical trial design, the proposed design modifications reduce the sample size by 30.5% and placebo exposure time by 35.4%. By making use of prognostic survival models, one creates a potential to include a larger proportion of the population and maximize generalizability. We propose a flexible design framework that naturally adapts the trial duration when inaccurate assumptions are made at the design stage, such as enrollment or survival rate. In case of futility, the follow-up time is shortened and patient exposure to ineffective treatments or placebo is minimized. For diseases such as ALS, optimizing the use of resources, widening eligibility criteria, and minimizing exposure to futile treatments and placebo is critical to the development of effective treatments. Our proposed design modifications could circumvent important pitfalls and may serve as a blueprint for future clinical trials in this population.

Overcoming Barriers to Parkinson Disease Trial Participation: Increasing Diversity and Novel Designs for Recruitment and Retention

Parkinson disease (PD) is highly prevalent among neurodegenerative diseases, affecting a diverse patient population. Despite a general willingness of patients to participate in clinical trials, only a subset of patients enroll in them. Understanding the barriers to trial participation will help to alleviate this discrepancy and improve trial participation. Underrepresented minorities, older patients, and patients with more medical comorbidities in particular are underrepresented in research. In clinical trials, this has the effect of delaying trial completion, exacerbating disparities, and limiting our ability to generalize study results. Efforts to improve trial design and recruitment are necessary to ensure study enrollment reflects the diversity of patients with PD. At the trial design level, broadening inclusion criteria, attending to participant burden, and focusing on trial efficiency may help. At the recruitment stage, increasing awareness, with traditional outreach or digital approaches; improving engagement, particularly with community physicians; and developing targeted recruitment efforts can also help improve enrollment of underrepresented patient groups. The use of technology, for virtual visits, technology-based objective measures, and community engagement, can also reduce participant burden and increase recruitment. By designing trials to consider these barriers to trial participation, we can improve not only the access to research for all our patients but also the quality and generalizability of clinical research in PD.

Critical design considerations for time-to-event endpoints in amyotrophic lateral sclerosis clinical trials

BACKGROUND

Funding and resources for low prevalent neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) are limited, and optimising their use is vital for efficient drug development. In this study, we review the design assumptions for pivotal ALS clinical trials with time-to-event endpoints and provide optimised settings for future trials.

METHODS

We extracted design settings from 13 completed placebo-controlled trials. Optimal assumptions were estimated using parametric survival models in individual participant data (n=4991). Designs were compared in terms of sample size, trial duration, drug use and costs.

RESULTS

Previous trials overestimated the hazard rate by 18.9% (95% CI 3.4% to 34.5%, p=0.021). The median expected HR was 0.56 (range 0.33-0.66). Additionally, we found evidence for an increasing mean hazard rate over time (Weibull shape parameter of 2.03, 95% CI 1.93 to 2.15, p<0.001), which affects the design and planning of future clinical trials. Incorporating accrual time and assuming an increasing hazard rate at the design stage reduced sample size by 33.2% (95% CI 27.9 to 39.4), trial duration by 17.4% (95% CI 11.6 to 23.3), drug use by 14.3% (95% CI 9.6 to 19.0) and follow-up costs by 21.2% (95% CI 15.6 to 26.8).

CONCLUSIONS

Implementing distributional knowledge and incorporating accrual at the design stage could achieve large gains in the efficiency of ALS clinical trials with time-to-event endpoints. We provide an open-source platform that helps investigators to make more accurate sample size calculations and optimise the use of their available resources.

Pharmacogenetic interactions in amyotrophic lateral sclerosis: a step closer to a cure?

Genetic mutations related to amyotrophic lateral sclerosis (ALS) act through distinct pathophysiological pathways, which may lead to varying treatment responses. Here we assess the genetic interaction between C9orf72, UNC13A, and MOBP with creatine and valproic acid treatment in two clinical trials. Genotypic data was available for 309 of the 338 participants (91.4%). The UNC13A genotype affected mortality (p = 0.012), whereas C9orf72 repeat-expansion carriers exhibited a faster rate of decline in overall (p = 0.051) and bulbar functioning (p = 0.005). A dose-response pharmacogenetic interaction was identified between creatine and the A allele of the MOBP genotype (p = 0.027), suggesting a qualitative interaction in a recessive model (HR 3.96, p = 0.015). Not taking genetic information into account may mask evidence of response to treatment or be an unrecognized source of bias. Incorporating genetic data could help investigators to identify critical treatment clues in patients with ALS.