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Gillian DunngalvinAug 16, 2023 12:00:00 AM4 min read

All You Need to Know About Adaptive Design in Clinical Trials


As clinical research undergoes a transformative shift, advancements in trial methodologies are at the forefront. In this edition, we unpack adaptive design in clinical trials—a dynamic approach reshaping how we explore novel treatments and functional products.

Clinical trials serve as the bedrock of medical progress, offering vital insights into the safety and effectiveness of interventions. Traditionally bound by rigid protocols, these trials are now embracing a more flexible and data-driven approach. As our understanding of research methodologies evolves, so does our ability to enhance the efficiency and statistical robustness of these crucial studies.

What is an Adaptive Design in Clinical Trials?

An adaptive design clinical study is defined as a study that:

  • Includes a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypotheses based on analysis of data (usually interim data) from subjects in the study.
  • Analyses of the accumulating study data are performed at prospectively planned timepoints within the study, can be performed in a fully blinded manner or in an unblinded manner, and can occur with or without formal statistical hypothesis testing.

An adaptive design refers to a flexible and dynamic approach to clinical trial design and execution. Unlike the conventional fixed protocol approach, adaptive designs allow for modifications based on accumulating data throughout the trial. This adaptive nature enables researchers to make informed decisions, refine hypotheses, and ultimately increase the chances of success.

What is an interim analysis?

At the core of adaptive design lies the concept of interim analysis. Interim analyses are planned evaluations of accumulating data performed at pre-specified time points or upon reaching specific milestones during a trial, e.g. 50 subjects completed. These analyses provide valuable insights into treatment efficacy, safety profiles, and other relevant parameters. Armed with this information, researchers can make data-driven adaptations to trial design, such as modifying patient enrolment criteria, treatment arms, or sample sizes.
An interim analysis is:

  • any examination of data obtained from participants in a trial while that trial is ongoing and is not restricted to cases in which there are formal between-group comparisons.
  • The observed data used in the interim analysis can include one or more types, such as;
  1. Baseline data
  2. Safety outcome data
  3. Pharmacokinetic
  4. Pharmacodynamic
  5. Other biomarker data
  6. Efficacy outcome data

Types of Interim Data Review for multi-arm studies

Non-Comparative analysis
1. Blinded Safety Review – whole sample
2. Blinded Data Review – whole sample

Comparative analysis
1. Blinded Data Review – by blinded groups
2. Unblinded Data Review

Can you introduce an interim analysis after Study Initiation?

According to FDA guidance (2019):

  • Interim analysis should be planned (and details specified) before data is examined in an unblinded manner by any personnel involved in planning the revision.
  • This can include plans that are introduced or made final after the study has started if the blinded state of the personnel involved is unequivocally maintained when the modification plan is proposed.
  • In nearly all situations, potential adaptive design modifications should be planned and described in the clinical trial protocol (and in a separate statistical analysis plan) prior to initiation of the trial.

Why is interim analysis included?

It is typically conducted as part of an adaptive trial design to monitor the accumulating data in clinical trials formally. They are generally performed in trials that have a DMC, longer duration of recruitment, and potentially serious outcomes.

The main advantage is efficiency –

  • From a statistical perspective, an adaptive design may provide the same statistical power with a smaller expected sample size or shorter expected duration than a comparable non-adaptive design.
  • From an ethical perspective, the ability to stop a trial early if it becomes clear that the trial is unlikely to demonstrate effectiveness can reduce the number of participants exposed to the unnecessary risk of an ineffective investigational treatment and allow participants the opportunity to explore more promising therapeutic alternatives.

Clear and transparent communication is key when implementing adaptive designs. Defining the standard outcome measures in advance ensures that trial objectives are met without bias. Protocol amendments, accompanied by ethical review and regulatory approvals, should be well-documented to ensure transparency and adherence to scientific standards.

The potential benefits of adaptive design extend beyond the individual trial. By optimizing the allocation of resources, adaptive designs can expedite the food development process, leading to faster availability of potentially life-saving treatments. This approach allows researchers to explore multiple treatment arms simultaneously, increasing the efficiency of comparative effectiveness studies.

As we continue to push the boundaries of nutrition and microbiome research, adaptive design stands as a powerful tool that empowers researchers to adapt, refine, and optimize clinical trials in real-time. By embracing flexibility without compromising scientific rigor, we can unlock new insights, accelerate the pace of discovery, and bring innovative products to consumers.

At Atlantia we have over 10 years of expertise in human clinical studies. Take a look at our study design research service page or contact our team today to discuss your clinical program with our expert team!


Gillian Dunngalvin

Gillian Dunngalvin is the Statistics Manager here at Atlantia Clinical Trials. She adeptly navigates the interplay between physiological and psychosocial factors in research. With a keen understanding of statistical methodologies, she ensures rigorous analysis, driving insights that enhance the understanding of human health and behavior in clinical trials.