What are adaptive trials?
An adaptive design allows the pre-specification of flexible components to the major aspects of the trial, like the treatment arms used (dose, frequency, duration, combinations, etc.), the allocation to the different treatment arms, the eligible patient population, and the sample size. An adaptive design can learn from the accruing data what the most therapeutic doses or arms are, allowing for example, the design to home in on the best arms.
Examples of adaptations are:
- Response adaptive randomisation
- Early stopping of the study for futility/efficacy
- Sample size re-estimation
- Participant population (adaptive enrichment)
- Dropping treatments that do not look promising
An overview of adaptive designs with examples of trials that employed these methods can be found as below:
| Design | Idea | Examples |
| Continual reassessment method | Model-based dose escalation to estimate the maximum tolerated dose | TRAFIC [136], Viola [137], RomiCar [138] |
| Group-sequential | Include options to stop the trial early for safety, futility or efficacy | DEVELOP-UK [139] |
| Sample size re-estimation | Adjust sample size to ensure the desired power | DEVELOP-UK [139] |
| Multi-arm multi-stage | Explore multiple treatments, doses, durations or combinations with options to ‘drop losers’ or ‘select winners’ early | TAILoR [31], STAMPEDE [67, 140], COMPARE [141], 18-F PET study [142] |
| Population enrichment | Narrow down recruitment to patients more likely to benefit (most) from the treatment | Rizatriptan study [143, 144] |
| Biomarker-adaptive | Incorporate information from or adapt on biomarkers | FOCUS4 [145], DILfrequency [146]; examples in [147, 148] |
| Adaptive randomisation | Shift allocation ratio towards more promising or informative treatment(s) | DexFEM [149]; case studies in [150, 151] |
| Adaptive dose-ranging | Shift allocation ratio towards more promising or informative dose(s) | DILfrequency [146] |
| Seamless phase I/II | Combine safety and activity assessment into one trial | MK-0572 [152], Matchpoint [153, 154] |
| Seamless phase II/III | Combine selection and confirmatory stages into one trial | Case studies in [133] |
*Table adapted from Pallmann,P et al., 2018
What are adaptive platform trials?
Adaptive platform trials enable the study of multiple targeted therapies in the context of a single disease in a perpetual manner, with therapies allowed to enter or leave the platform on the basis of a decision algorithm.
Key Features of Adaptive Platform Trials:
- Any number of subgroups
- Involves regular interim analyses
- No maximum sample size
- Has predefined decision rules for adaptation
- Treatments can be added or removed
- Treatment assignment controlled by accruing data
- Governed by a single master protocol
Key Features that are Determinants of the Appropriateness of an Adaptive Platform Model
- Is there currently low-quality evidence regarding current treatment options?
- Are there many new potential treatments or is there only one experimental treatment of interest?
- Are there likely to be new treatments that become available?
- The disease has a high public health impact
- The disease has multiple treatments administered in parallel or in series
- There is substantial uncertainty about optimal treatment, particularly with variation in practice (replace random care with randomised care) and / or lots of new treatments to evaluate
- Diseases with reasonable a priori likelihood of heterogeneity of treatment effect or treatment-by-treatment interactions
- It is an important disease that has available clinical trial infrastructure and access to adaptive trial expertise
Questions to consider in making this decision include:
- Whether the specific intervention best suits a conventional model or a whole disease area and may be better addressed with an adaptive platform trial model.
- Endpoint – is it immediately observed or long term?
- Disease progression/Survival endpoint – these trials have typically long endpoints that can make adaptation difficult
Master Protocol
Master Protocol Value Proposition Guide (ctti-clinicaltrials.org)
A master protocol is a unifying study design that includes multiple subgroups and substudies, with patients having same or different diseases and that employ one or multiple drugs to treat it (Bogin V, 2020)
This document outlines key scientific, operational, and funding considerations that can support early adopters’ efforts to think through the “why” and “how” of developing a master protocol study. The tool features four critical value domain sections: 1. Patient-centered Design Innovation 2. Operational Feasibility 3. Study Governance and Decision Making 4. Funding Considerations.
Treatment Characteristics of the Investigational Disease that make an adaptive platform trial appealing
- Multiple treatment domains with multiple treatment options within domains
- Low quality evidence regarding current treatment options:
- Effectiveness, comparative effectiveness, and cost-effectiveness within each domain of care
- Optimal combination and / or sequence of treatments; dose and duration
- Pipeline of new treatment options
- Variation in cost of treatments within domains
- Reasonable prior likelihood of differences in outcome and cost, high likelihood of differential treatment effect
The Benefits and Challenges of Adaptive Platform Trials
| Benefits | Challenges |
| Generally, has reduced participant numbers and consequently improved recruitment performance | Much more complex/time-consuming to develop, design and set-up than conventional designs requiring |
| Reduction in cost and time for trial implementation and conduct compared with running multiple conventional two-arm, parallel group designs | Need specialist statistical support including the conduct of simulation models to determine if the proposed planned adaptation introduces bias |
| Adaptive randomisation may allow a smaller portion of patients to be exposed to potentially inferior treatments than a traditional design. The modification of randomisation probabilities to favour the treatment arms with what cumulative data show as having the best treatment effect, or the best treatment effect for a patient’s particular sub-group. Often combined with a fixed allocation to control and a fix-allocation “burn-in” period before adaptive randomisation starts |
Logistical challenges with frequent interim analyses which may require blinded and unblinded teams. In some circumstances, particulary two-arm comparisons, adaptive randomisation may require a larger total number of patients than a fied desig |
| Enables improved understanding of intervention effects, e.g. can determine efficacy in subgroups of participants | Overall design is more difficult to understand which may impact trial conduct and study staff engagement |
| Greater acceptability to stakeholders (due to added flexibility) | Requires a more complex governance structure to oversee the trial |
| May increase the efficiency with which the effectiveness of a treatment is determined | Mid-study changes in treatments or population allotment can lead to Type I error inflation or operational bias |
| Enables multiple research questions to be addressed simultaneously | Statistical significance (alpha) penalties apply whenever adaptations are made and p-values can be challenging to define and compute |
| Ability to declare a futile treatment or study earlier in the process than traditional trial designs | Analysis that reports pooled efficacy rather than sub-group findings can make it hard to interpret the true value of treatment if some groups have significantly different results from other |
| Clinically important outcomes are known more quickly a than in traditional designs | An independent data analysis team or data monitoring committee required for preserving scientific validity and data integrity, conducting interim computations, and maintaining a blinded sponsor during adaptive decision-making, especially for phase-3 trials |
Case Studies
There are situations where an innovative design is more appropriate for a trial when compared to a trial with a traditional design. An example has just been published from the RECOVERY trial, a simulation study
Additional resources
NIHR resources – case studies and podcasts
Bogin V. Master protocols: New directions in drug discovery. Contemp Clin Trials Commun. 2020 Apr 25;18:100568. doi: 10.1016/j.conctc.2020.100568. PMID: 32395664; PMCID: PMC7205752.
Pallmann, P., Bedding, A.W., Choodari-Oskooei, B. et al. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med 16, 29 (2018). https://doi.org/10.1186/s12916-018-1017-7
Web Based Resources
ACTA website Resources
What is an adaptive trial? (2.30mins)
How do adaptive trial sizes work? (4mins)
What are the benefits of adaptive designs? (5mins)
ACTA’s Adaptive Platform Trials Workshop, Annual Scientific Meeting (7th Nov 2022)
Designing a Platform Trial, by Dr Julie Marsh
What questions are suitable for an Adaptive Platform Trial, by Prof Steve Webb
Operationalising Adaptive Platform Trial, by Mr Arlen Wilcox
Organisation of Adaptive Platform Trials, by Dr Colin McArthur
Consumer engagement & involvement, by Mr Mitch Messer
Funding strategies for platform trials, by Prof Steve Webb
The Adaptive Health Intelligence
EU -PEARL Consortium EU Patient-cEntric clinical tRial pLatforms
https://eu-pearl.eu/ and https://eu-pearl.eu/deliverables-patient-centric-clinical-trial-platforms/
CTTI
Master Protocol Studies – CTTI (ctti-clinicaltrials.org)
European Clinical Research Infrastructure Network (Ecrin)
Adaptive Platform Trial Toolbox | Ecrin
Health Authorities, academic groups or NGO:
Overview, hurdles, and future work in adaptive designs: perspectives from a National Institutes of Health-funded workshop. Clin Trials. 2012 December ; 9(6): 671–680. doi:10.1177/1740774512461859.
Innovative Clinical Trials Resource NHLBI ICTR Webinar – An introduction and overview of innovative trial design (41mins, Kert Viele)
Drug discovery and clinical trials
New clinical trial designs for the evaluation of antimicrobial agents
Focus on innovation in trial design and study delivery (NIHRtv)
PANDA: https://www.sheffield.ac.uk/scharr/research/centres/ctru/panda
SPHERE: Adaptive and Platform Trials Information Session (2hr8mins, SPHERE Clinical Trials Methodology Hub)
Consultancies & sponsored webinars:
Adaptive Design Clinical Trials (60mins, Scott Berry)
What clinicians should know about adaptive clinical trials (12mins, Roger Lewis)
Adaptive Trial Designs: Introduction for non-statisticians (60mins, Natasa Rajicic)
Guidelines from the FDA and EMA on adaptive trials:
ICH guidelines and training materials on adaptive trials: https://database.ich.org/sites/default/files/E20_FinalConceptPaper_2019_1107_0.pdf