Recent developments in the implementation of novel designs for early-phase combination studies

Adapting isotonic dose-finding to a dynamic set of drug combinations with application to a phase I leukemia trial

BACKGROUND/AIMS

This article describes the proposed design of a phase I study evaluating the safety of ceramide nanoliposome and vinblastine among an initial set of 19 possible dose combinations in patients with relapsed/refractory acute myeloid leukemia and patients with untreated acute myeloid leukemia who are not candidates for intensive induction chemotherapy.

METHODS

Extensive collaboration between statisticians and clinical investigators revealed the need to incorporate several adaptive features into the design, including the flexibility of adding or eliminating certain dose combinations based on safety criteria applied to multiple dose pairs. During the design stage, additional dose levels of vinblastine were added, increasing the dimension of the drug combination space and thus the complexity of the problem. Increased complexity made application of existing drug combination dose-finding methods unsuitable in their current form.

RESULTS

Our solution to these challenges was to adapt a method based on isotonic regression to meet the research objectives of the study. Application of this adapted method is described herein, and a simulation study of the design's operating characteristics is conducted.

CONCLUSION

The aim of this article is to bring to light examples of novel design applications as a means of augmenting the implementation of innovative designs in the future and to demonstrate the flexibility of adaptive designs in satisfying changing design conditions.

Efficient dose-finding for drug combination studies involving a shift in study populations

This paper describes the design of an early phase, prospective trial evaluating the safety and tolerability of the combination of the histone deacetylase inhibitor, entinostat, in combination with capecitabine. The study consists of two parts; an initial phase evaluating the safety of the combination in participants with metastatic breast cancer, followed by a second phase assessing the safety of the combination in participants with residual disease after neo-adjuvant chemotherapy for breast cancer. We describe the adaptation of a model-based design for identifying the maximum tolerated dose combination that efficiently moves from the initial phase in an advanced disease population to the second phase in the target population. Operating characteristics demonstrate the ability of the method to accurately predict true maximum tolerated dose combinations in a high percentage of trials with reasonable sample sizes, while treating participants at and around desirable combinations. The proposed design is a practical, early-phase, adaptive method for use with drug combination dose finding in the presence of shifting patient populations. More challenging research questions are being investigated in early-phase trials, which has created the need to implement more flexible designs that can meet the objectives of current studies, such as those exploring drug combinations while addressing patient heterogeneity. Our goal is to facilitate acceptance and application of more novel designs in contemporary early-phase studies.

Tailoring early-phase clinical trial design to address multiple research objectives

INTRODUCTION

In contemporary oncology drug development, implementation of novel early-phase designs with the ability to address multiple research objectives is needed to better refine regimens. This paper describes an adaptive design strategy for identifying a range of optimal regimens based on two endpoints within multiple cohorts. The proposed design was developed to address objectives in an early-phase trial of cancer vaccines in combination with agonistic antibodies to CD40 and CD27.

MATERIALS AND METHODS

We describe a model-based design strategy that was developed for a trial evaluating the safety and immunogenicity of vaccination with (1) peptides plus CD40 antibody and TLR3 ligand, (2) systemic administration of an agonistic CD27 antibody, and (3) to assess immune response from (1) and (2) compared to optimal controls in participants with stage IIB-IV melanoma.

RESULTS AND CONCLUSIONS

The proposed design is a practical adaptive method for use with combined immunotherapy regimens with multiple objectives within multiple cohorts of interest. Further advances in the effectiveness of cancer immunotherapies will require new approaches that include redefining optimal strategies to take multiple regimens forward into later phases, incorporating additional endpoints in the dose selection process and testing drug combination therapies to improve efficacy and reduce toxicity. Our goal is to facilitate the acceptance and application of more novel designs in contemporary early development trials.

Implementation of a Model-Based Design in a Phase Ib Study of Combined Targeted Agents

In recent years, investigators have recognized the rigidity of single-agent, safety-only, traditional designs, rendering them ineffective for conducting contemporary early-phase clinical trials, such as those involving combinations and/or biological agents. Novel approaches are required to address these research questions, such as those posed in trials involving targeted therapies. We describe the implementation of a model-based design for identifying an optimal treatment combination, defined by low toxicity and high efficacy, in an early-phase trial evaluating a combination of two oral targeted inhibitors in relapsed/refractory mantle cell lymphoma. Operating characteristics demonstrate the ability of the method to effectively recommend optimal combinations in a high percentage of trials with reasonable sample sizes. The proposed design is a practical, early-phase, adaptive method for use with combined targeted therapies. This design can be applied more broadly to early-phase combination studies, as it was used in an ongoing study of a melanoma helper peptide vaccine plus novel adjuvant combinations. Clin Cancer Res; 23(23); 7158-64. ©2017 AACR.

Statistical controversies in clinical research: early-phase adaptive design for combination immunotherapies

Background

In recent years, investigators have asserted that the 3 + 3 design lacks flexibility, making its use in modern early-phase trial settings, such as combinations and/or biological agents, inefficient. More innovative approaches are required to address contemporary research questions, such as those posed in trials involving immunotherapies.

Design

We describe the implementation of an adaptive design for identifying an optimal treatment regimen, defined by low toxicity and high immune response, in an early-phase trial of a melanoma helper peptide vaccine plus novel adjuvant combinations.

Results

Operating characteristics demonstrate the ability of the method to effectively recommend optimal regimens in a high percentage of trials with reasonable sample sizes.

Conclusions

The proposed design is a practical, early-phase, adaptive method for use with combined immunotherapy regimens. This design can be applied more broadly to early-phase combination studies, as it was used in an ongoing study of two small molecule inhibitors in relapsed/refractory mantle cell lymphoma.

Implementation of adaptive methods in early-phase clinical trials

There has been constant development of novel statistical methods in the design of early-phase clinical trials since the introduction of model-based designs, yet the traditional or modified 3+3 algorithmic design remains the most widely used approach in dose-finding studies. Research has shown the limitations of this traditional design compared with more innovative approaches yet the use of these model-based designs remains infrequent. This can be attributed to several causes including a poor understanding from clinicians and reviewers into how the designs work, and how best to evaluate the appropriateness of a proposed design. These barriers are likely to be enhanced in the coming years as the recent paradigm of drug development involves a shift to more complex dose-finding problems. This article reviews relevant information that should be included in clinical trial protocols to aid in the acceptance and approval of novel methods. We provide practical guidance for implementing these efficient designs with the aim of augmenting a broader transition from algorithmic to adaptive model-guided designs. In addition we highlight issues to consider in the actual implementation of a trial once approval is obtained. Copyright © 2016 John Wiley & Sons, Ltd.

Practical designs for Phase I combination studies in oncology

Phase I trials evaluating the safety of multidrug combinations are becoming more common in oncology. Despite the emergence of novel methodology in the area, it is rare that innovative approaches are used in practice. In this article, we review three methods for Phase I combination studies that are easy to understand and straightforward to implement. We demonstrate the operating characteristics of the designs through illustration in a single trial, as well as through extensive simulation studies, with the aim of increasing the use of novel approaches in Phase I combination studies. Design specifications and software capabilities are also discussed.

Statistical controversies in clinical research: requiem for the 3 + 3 design for phase I trials

BACKGROUND

More than 95% of published phase I trials have used the 3 + 3 design to identify the dose to be recommended for phase II trials. However, the statistical community agrees on the limitations of the 3 + 3 design compared with model-based approaches. Moreover, the mechanisms of action of targeted agents strongly challenge the hypothesis that the maximum tolerated dose constitutes the optimal dose, and more outcomes including clinical and biological activity increasingly need to be taken into account to identify the optimal dose.

PATIENTS AND METHODS

We review key elements from clinical publications and from the statistical literature to show that the 3 + 3 design lacks the necessary flexibility to address the challenges of targeted agents.

RESULTS

The design issues raised by expansion cohorts, new definitions of dose-limiting toxicity and trials of combinations are not easily addressed by the 3 + 3 design or its extensions.

CONCLUSIONS

Alternative statistical proposals have been developed to make a better use of the complex data generated by phase I trials. Their applications require a close collaboration between all actors of early phase clinical trials.