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Changing Priorities

Clinical trials utilising adaptive designs are becoming increasingly widespread, with research showing they can increase effi ciency in the development process, and lead to the discovery and faster delivery of more effective treatments. A scientifically rigorous adaptive design ensures that clinical trial information is updated as it is gathered, and predicts the future course of the trial by incorporating modifications based on the accumulating information. These designs combine exploration and confirmation within a single trial, which reduces time lags and adheres to the principle of ‘adaptive by design’ to maintain trial integrity and validity.

According to data from Thomson Reuters, the number of trials using adaptive designs has increased over the last decade (with the exception of 2003 and 2009). The compound annual growth rate of these types of trials is a significant 15.2 per cent over the past 10 years, with a 15 per cent increase in 2012 and an estimated 20 per cent rise in 2013. The National Cancer Institute, Novartis, GlaxoSmithKline (GSK), Pfizer and Merck are the top five players in this field. Most of these trials have been carried out in the US, with European countries following behind.

Play the Winner

Adaptation is most valuable when study outcome or biomarker availability appear relatively early; the study involves substantial morbidity, risks and costs; and uncertainty exists regarding relative efficacy and adverse event rates.

Commonly used adaptations include:
  • Stopping early (or late, such as extending accrual), with a conclusion of either superiority, non-inferiority or futility
  • Dose finding
  • Dropping arms or doses (drop the loser)
  • Multiple phases of development that are included seamlessly in a single trial
  • Changing randomisation proportion (play the winner)
  • Responder population finding
  • Changing accrual rate
For each type of adaptation, researchers must ensure that the type 1 error rate (false positive) is controlled, the trial has a high probability of answering the research question of interest, and equipoise is maintained.

Response-adaptive strategies – play the winner, randomised play the winner, drop the loser, generalised drop the loser, and doubly-adaptive biased coin designs – are being considered for new treatment assignments in controlled clinical trials where minimising treatment failures is crucial. Such designs are attractive competitors to 1:1 randomised designs for comparing the success rates of two treatments. Using these designs, each new treatment assignment depends on previous outcomes, based on predefined rules.

The power of such response-adaptive designs is generally very close to the power of 1:1 randomised design, with play the winner, generalised drop the loser or doubly-adaptive biased coin designs outperforming the randomised play the winner approach.

Design Types

Three main types of adaptive designs are used in clinical trials, with numerous subsets for each:
  • Learning/exploratory phase adaptive designs: these are related to dosing, exposure, differential participant response, response modifiers or biomarker responses that enable the researchers to learn and optimise early clinical development processes
  • Confirmatory phase adaptive designs: these are performed to provide an initial confirmation of safety
  • Adaptive seamless combined designs: these combine exploration and confirmation within a single trial to potentially yield increased efficiency by reducing time intervals between phases 
Learning/Exploratory Designs

These designs are being used by GSK, which is currently recruiting subjects for a 12-week, dose-ranging Phase 2 study to investigate the safety, tolerability, pharmacodynamics and efficacy of various doses of GSK-2586184 in patients with systemic lupus erythematosus.

Learning phase adaptive designs are subclassified as either the adaptive dose response (toxicity dose) type, or adaptive dose response (efficacy dose).

Toxicity dose is a Bayesian continual reassessment method based dose escalation algorithm to define the maximum tolerated dose (MTD). The time-to-event continual reassessment method (TITE-CRM) allows for an MTD that exceeds that determined from traditional (intermittent dosing) studies. This approach has been primarily used in cancer and stroke studies.

The efficacy dose type is supported by the Pharmaceutical Research and Manufacturers of America’s adaptive dose response working group, which favours Bayesian modelling to identify an appropriate dose response for each new study participant, based on previous responses. This design is employed in the Acute Stroke Therapy by Inhibition of Neutrophils study of the recombinant glycoprotein UK-279,276 in 966 acute stroke patients, allowing for an early termination of the study for futility.

Confirmatory Designs

According to the Food and Drug Administration (FDA), some adaptive designs are well understood, while others are not. Confirmatory designs are described as group sequential (GS), deemed ‘well understood’ by the FDA, allowing the early stopping of a trial if it becomes clear that a treatment is superior or inferior.

The GS method is the most frequently used adaptive design in modern confirmatory clinical research. The MATISSE study is an apt example, involving a novel DNA cross-linker, palifosfamide-tris (in combination with carboplatin and etoposide chemotherapy, versus carboplatin and etoposide alone), in chemotherapy-naïve patients with extensive-stage small cell lung cancer. This study design uses an adaptive group sequential approach, with sample size re-estimation at the interim analysis.

Some designs are less well understood from the FDA perspective. Extensive planning and validation are required to prove that a particular therapeutic modality is advantageous, with a lack of bias. The usefulness and validity of adaptive randomisation, enrichment designs and sample size re-estimation designs are under debate.

Adaptive Randomisation

The response adaptive randomisation (play the winner) approach uses observed treatment outcomes from preceding participants to change allocation probabilities. An FDA draft guidance document states: “Adaptive randomisation should be used cautiously in adequate and well-controlled studies, as the analysis is not as easily interpretable as when fixed randomisation probabilities are used.”

One example of adaptive randomisation is the Efficacy Optimisation Research of Telbivudine Therapy initiative, a two-year, randomised, controlled, open-label, virologic response adaptive design, multi-centre study in China which optimised antiviral efficacy of telbivudine in adult patients with HBeAg-positive chronic Hepatitis B.

Another such study was initiated by Eisai in January 2013, with patient recruitment at multiple sites in the US. This Phase 2 trial of BAN-2401 in patients with early Alzheimer's disease uses a Bayesian design with response adaptive randomisation across placebo or five active arms of the drug, to determine clinical efficacy and explore the dose response of the drug. Called BAN2401-G000-201, the multinational, double-blind, placebo-controlled, parallel-group study is expected to enrol about 800 subjects who have mild Alzheimer's disease or mild cognitive impairment due to the disease.

Enrichment Design

The rizatriptan trial in paediatric patients with migraine is a model where an enrichment design has helped to identify treatment-responding subsets. This design targets therapies at patients who can benefit the most from a specific treatment. Another area that profits from adaptive enrichment design is pharmacogenetic research, where enrichment isolates genetic marker subgroups predicting treatment response. The efficiency of the study increases with the identity of genetic subgroups displaying increased treatment benefit.

Despite several disadvantages of this design – for example, complexity, bias and lack of information in excluded groups – adaptive enrichment designs currently have greatest value in late-learning stage designs.

Sample Size Re-Estimation

Working with a fixed sample size can lead to problems if a clinically significant treatment effect is expected, and conflicting parameters such as variance, overall event rate or accrual rate are at play, leading to an underpowered or overpowered study.

Sample size re-estimation designs allow the parameter estimates to be updated and adjusted during an ongoing trial. The aforementioned MATISSE cancer study represents this strategy, as does the Chinese comparative efficacy study of Qizhitongluo capsules to treat ischemic stroke patients in recovery phase.

Seamless Designs

When applied to early development, namely Phase 2 and 3, seamless designs promise an efficient use of sample size and resources in lieu of separate trials. LY-500307 (a selective estrogen receptor beta agonist trial), a seamless, two-staged, Phase 1b/2a adaptive design to evaluate dose and efficacy, and the Coenzyme Q10 QALS study (an adaptive, two-stage, randomised controlled Phase 1/2a trial to compare decline in amyotrophic lateral sclerosis and functional rating scale score) are some examples.

Such a strategy can involve a seamless dose escalation/ expansion with an adaptive randomisation scheme (SEARS) – formulating a design that combines Phase 1 dose escalation based on toxicity with Phase 2 dose expansion and dose comparison based on efficacy.

SEARS allows extension from Phase 1 to Phase 2 under one design with no time gap, and employs a dynamic and parallel procedure involving simultaneous dose escalation, dose graduation and adaptive randomisation. It integrates three components into a seamless scheme. In Phase 1, it applies the modified toxicity probability interval method to monitor dose escalation based on toxicity outcome. Doses that show promising efficacy and safety are immediately graduated to Phase 2, in which patients are adaptively randomised based on efficacy outcome.

Phase 1 dose escalation, dose graduation and Phase 2 adaptive randomisation proceed simultaneously throughout the entire trial. The Phase 2/3 design allows for the seamless, time-saving transition between Phase 2b (learning) and Phase 3 (confirming), using data obtained from both stages in the final analyses.

Trial Example

Following this design – and after six months of treatment – patients participating in the FOLFIRINOX study (combined therapy with oxaliplatin, irinotecan, leucovorin and fluorouracil) with metastatic pancreatic cancer displayed additional survival advantage and good performance status when compared to subjects on gemcitabine.

This design will also be incorporated in the GENETIC-AF trial of ARCA Biopharma and Medtronic, which will evaluate Gencaro (bucindolol hydrochloride) in comparison to metoprolol CR/XL for the prevention of atrial fibrillation in patients with heart failure and reduced left ventricular ejection fraction.

Malaria Prevention Study

Plasmodium vivax is responsible for more than 400 million malaria cases annually in Asia, South America and Africa. P. vivax malaria is currently prevented by primaquine, an 8-aminoquinoline that requires a 14-day treatment course, making compliance diffi cult. Moreover, it is associated with haemolytic anaemia in individuals with inherited glucose-6- phosphate dehydrogenase (G6PD) deficiency. Tafenoquine (TQ), another 8-aminoquinoline, potentially offers a shorter treatment course (single dose) and is being co-developed by GSK and Medicines for Malaria Venture.

The efficacy and safety of TQ for P. vivax malaria is being assessed in a seamless design Phase 2b/3 clinical study – the Dose and Efficacy Trial: Evaluation of Chloroquine and Tafenoquine In Vivax Elimination. In the first part of this randomised, double-blind, multi-centre, parallel-group study, some 324 patients were recruited to identify the most appropriate dose of TQ. All subjects were accounted for in terms of age, weight, G6PD enzymatic activity >70 per cent and gender.

At six-month post-treatment follow-up, TQ300/600mg in single doses plus chloroquine over three days was effective to prevent P. vivax relapses. TQ300mg was selected for Phase 3 development, since it predicts a lower haemolytic risk than TQ600mg. This will determine the safety and effi cacy of the fi nal dose in a larger patient population.

Comparative Effectiveness

Another example of a seamless adaptive design is the comparative effectiveness trials, which compare two or more treatments that have already been shown to be efficacious. Using a two-stage adaptive design, one of three decisions can be reached: declare efficacy (one treatment best); declare futility (unlikely to show difference between treatments); or if evidence suggests a smaller effect might exist, then proceed with a second stage powered to detect the smaller effect.

Maximum Impact

One of the biggest benefi ts of an adaptive design is to identify ineffective treatments earlier. This allows for a redistribution of resources to more promising, effective treatments. Although adaptive designs cannot change the answer regarding the effectiveness of particular treatments, they can increase the efficiency in finding one.

In short, adaptive designs help to create personalised medicine in research mode. Although they may not be conducive to every clinical trial situation, appropriately utilised adaptive designs can maximise gathered information, minimise risk to subjects and sponsors, improve efficacy and reduce costs.



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Shyama Ghosh is Scientific Editor at Thomson Reuters. She is Managing Editor of Drug Data Report Abstracts and collaborates editorially on the company’s other life sciences products. Shyama received her PhD in Molecular Biology from the Vrije Universiteit Brussels, Belgium. She has research experience in vaccine studies and hostparasite interactions in the fields of malaria, schistosomiasis and human papilloma virus infections.

Alvaro Arjona is Thomson Reuters’ Editorial Director of Drug Development. After exploring the circadian regulation of innate immunity at Rutgers University and the Yale School of Medicine, Alvaro joined Thomson Reuters in 2009. He has authored several book chapters and over 25 peer-reviewed articles in journals such as Nature Immunology, Immunity and The Journal of Clinical Investigation.
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Shyama Ghosh
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Alvaro Arjona
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