Adaptive Trial Designs
Published:
What I learned from my internship at BeiGene?
Adaptive Design
The field of oncology is rapidly evolving, with new discoveries, technologies, and treatment approaches emerging continuously. Oncology drugs development has several important attributes as cancer is a life-threatening and highly diverse and complex disease, with multiple subtypes, varying genetic profiles, and different treatment responses. The amount of successfully approved new oncology drug is small and the whole process of clinical trials is time-consuming. Adaptive design in oncology drug development offers the potential to improve patient outcomes, optimize resource utilization, accelerate the drug development process. It makes oncology drug development much more efficient.
An adaptive design is defined as a clinical trial design that incorporates multiple stages or phases and allows modifications to the trial and/or statistical procedures of the trial after its initiation without undermining its validity and integrity. The purpose is to make clinical trials more flexible, efficient and fast. Due to the level of flexibility involved, these trial designs are also termed as “flexible designs”. It allows for modifications based on interim analyses of accumulating data to various aspects of the trial, such as sample size, treatment arms, patient population, or study endpoints, based on the results observed at each stage.
However, careful planning, rigorous statistical methods, and appropriate regulatory considerations are essential to ensure the integrity, validity, and interpretability of the trial results.
Here list several key features of adaptive design.
Sequential stages: The trial is divided into multiple stages or phases, often referred to as “adaptive stages” or “interim analysis stages.” Each stage evaluates the accumulated data and informs subsequent adaptations.
Interim analyses: After the completion of each stage, interim analyses are conducted to assess the trial’s progress, treatment effects, or other predefined endpoints. These analyses provide an opportunity to make adaptations or decisions based on the emerging data.
Adaptations: Based on the results of interim analyses, adaptations can be made to various aspects of the trial, such as sample size, randomization ratios, treatment arms, patient selection criteria, or study endpoints. The adaptations aim to optimize the trial design and increase the likelihood of success.
Statistical considerations: Multi-stage adaptive trials employ sophisticated statistical methods to account for the adaptations and maintain appropriate control of the type I error rate. Methods such as group sequential designs, Bayesian approaches, or adaptive randomization algorithms are often utilized.
Efficiency and flexibility: The design allows for more efficient use of resources and flexibility in decision-making, as it enables modifications based on evolving data and knowledge gained during the trial. This can result in reduced sample size requirements, shorter trial durations, or better-tailored treatment approaches.
Ethical considerations: Adaptive trial designs aim to enhance ethical considerations by allowing adaptations based on the emerging evidence. This can minimize exposure to ineffective or potentially harmful treatments by terminating or modifying ineffective treatment arms early in the trial.
Types of Adaptive Design Trials
| Name | Remark |
|---|---|
| Adaptive randomization design | * Alterations in the randomization schedule is allowed depending upon the varied or unequal probabilities of treatment assignment to increase the probability of success. |
| Group sequential design | * A trial can be stopped prematurely if there are safety or efficacy issues and depending upon the results of the interim analysis, additional modifications can be made. The most familiar example is the “3+3” Phase I trial design for finding a maximum-tolerated-dose. |
| Sample size re-estimation design | * A sample size can be modified or re-estimated in this type of design based on the observed data at interim. |
| Drop-the-loser design | * The subjects detected to have received inferior treatments at the interim analysis can be dropped out. |
| Adaptive dose-finding design | * It is often used in early-phase clinical development to identify the minimum effective dose and the maximum tolerable dose. |
| Biomarker-adaptive design | * Modification can be made in the ongoing trial based on the response of various biomarkers associated with the disease under consideration. |
| Adaptive treatment-switching design | * Sifting the patient from one treatment option to other is allowed, if there are concerns about the safety or efficacy |
| Hypothesis-adaptive design | * Modifications or changes in hypotheses based on interim analysis results are allowed. |
| Adaptive seamless phase II/III design | * This design combines the objectives of separate Phase IIb and Phase III in a single trial. |
| A multiple-adaptive design | * Any combination of the above adaptive designs. |
What is a seamless adaptive design?
In traditional clinical trial designs, there is a clear distinction between phase II and phase III trials. Phase II trials focus on assessing the treatment’s efficacy and safety in a relatively small group of patients, while phase III trials involve larger patient populations to confirm efficacy and further evaluate safety.
In a seamless 2-in-1 adaptive design, the transition between phase II and phase III is seamless, meaning there is no clear separation between the two phases. This design allows for a more flexible and adaptive approach to decision-making throughout the trial, based on interim analyses and accumulating data.