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What You Need to Know WRITTEN by CONTACT INFORMATION FEATURED CONTACT INFORMATION WRITER SynteractHCR Greg Wei, Ph.D. 5759 Fleet St., Carlsbad, CA 92008 Statistical Research Fellow SynteractHCR.com Adaptive Trial Design in Clinical Trials: What You Need to Know WRITTEN BY CONTACT INFORMATION Greg Wei, Ph.D. SynteractHCR Statistical Research Fellow, 5759 Fleet St., Carlsbad, CA 92008 SynteractHCR SynteractHCR.com Adaptive Trial Design in Clinical Trials: What You Need to Know Even as spending in biomedical research has surged, the pace of successful pharmaceutical development has slowed. This has motivated the development of innovative adaptive designs (AD) in clinical trials. AD trials take advantage of accumulating information, enabling modifications after a trial has commenced. Adaptive designs reduce both time and cost, and help determine the best dose as well as the appropriate patient populations for which a drug may be efficacious. As defined by FDA Guidelines, adaptive design is: 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. While adaptive design is a fairly young concept, the Food and Drug Administration (FDA), the European Medicines Agency (EMEA), and the pharmaceutical industry have responded positively, developing guidelines and encouraging the use of this innovation. Types of adaptive designs It is important that the trial protocol is set prior to initiation of the trial, even in an adaptive trial design. The adaptation process may continue throughout the trial, as previously pre-set by the protocol. Modifications made may include dosage, sample size, patient selection criteria and sometimes, even the formulation of the drug undergoing trial or its mix with companion drugs. Trial adaptations can incorporate a number of designs, including the following: • Adaptive randomization: With this design, we can alter the ratio between placebo and treatment. This approach enables us to make the study more efficient. • Group sequential: Interim analyses allows the sponsor to stop the trial. • Sample size re-estimation: Enables a change in sample size based on blind or unblinded interim analysis. 1 • Drop-the-loser design: Two stage design that drops inferior specified patient groups, or arms. • Adaptive dose finding design: Accomplished through continuous assessment (CRM) and Bayesian methodology. • Biomarker adaptive design: Allows design adaptation based on patient biomarkers. • Adaptive treatment - switch design: Treatment is switched due to efficacy or safety. • Adaptive hypotheses design: Examples include switching from a superiority hypothesis to a non-inferiority hypothesis and between the primary study endpoint and secondary endpoints. • Adaptive seamless phase II/III design: No pause when Phase II transitions into a Phase III trial. • Multiple adaptive design: A combination of designs. Why we need adaptive designs Adaptive designs speed up new drug development and overcome the limitations of FIXED, or quantitative, designs. Earlier decisions can be made in terms of saving patient exposure and resources as well as for conditional new drug application (NDA) filing. Optimal treatment dose and patient population can be determined. Adaptive designs assist in developing personalized medicine to deliver superior efficacy and reduce adverse events (AE). Cautionary tales – What clients need to know While adaptive designs can speed up clinical trials and help put new drugs on the market faster, they do come with caveats and precautions. Balance is of supreme importance, where flexibility and efficiency are on equal footing with validity, integrity and interpretability, with neither sacrificed. Adaptation must not alter the quality of the trial. A Type I error (incorrect rejection, or false positive) should be preserved and observed, especially in Phase III trials. A data monitoring committee (DMC) is necessary to maintain the trial’s validity. Trial feasibility should be carefully evaluated to ensure that patients most appropriate for the study are recruited. What adaptive designs are not Just as important as the reasons for using adaptive designs, they should not be used to meet certain ends. For example, adaptive designs are not used for real time data review; while studies go through a lot of review for safety, that is not the purpose of AD. Adaptive design cannot be used to bury the reality of a poor study. If the recruitment is faulty, the trial drug is not effective or the patients do not comply with the requirements, an adaptive design trial will not provide valid results. The data is not meant to be looked at out of mere curiosity or pressure by the company board. Ultimately, adaptive design clinical trials must maintain the same integrity and validity as other trials and not be seen as cheap, quick and dirty studies. Why a DMC is needed Adaptive design clinical trials require a data monitoring committee as a set of eyes separate from those conducting the studies. The DMC is responsible for monitoring for safety and for interim analysis of efficacy during Phase III trials. A DMC can be valuable in key Phase II trials as well. An independent statistical analysis center (SAC) is required to produce materials for review by the DMC. Adaptive design for early clinical trials Adaptive designs (AD) when applied to clinical trials allow use of accumulated data to modify a trial after it has commenced. This enables the study to save time and resources, getting to go/no go decisions more quickly. Studies move through phases as the best patient cohorts, dosage and application are determined. Ultimately, the goal for adaptive trial designs is to assist in developing drugs that deliver superior efficacy and reduce serious adverse events (SAE). 2 Early clinical trials are designed to assist in understanding toxicities, find optimal doses, explore biomarkers and surrogate endpoints and provide proof of concept. Simon’s One-Arm Two Stage Adaptive Design One-arm, two stage adaptive design is an approach with which most are familiar. The purpose of this design is to minimize the number of patients exposed to the trial drug and still maintain the power for hypothesis testing. The Stage 2 is needed only if the hypothesis couldn’t either be rejected or accepted in Stage 1. The following example demonstrates a situation where, in order to detect a difference of 0.2 in proportion with 80% power using a 5% test, the Stage 1 needs 20 subjects and the Stage 2 needs 15 subjects. If in the Stage 1, more than 12 (R1) subjects show ‘success’, the null hypothesis (the true proportion is not greater than 0.2) can be rejected, whereas if less than 4 (A1) subjects show ‘success’, the alternative hypothesis can be rejected. If neither happens, the Stage 2 will be needed. The corresponding cut-off values for the Stage 2 are given as R2 and A2. Simon’s Multi-Arm Two Stage Adaptive Design The concept of this AD is similar to one-arm, two stage AD, but assesses several regimens simultaneously. This enables earlier identification of any ineffective treatments. Accumulated data is used to verify assumptions made about aspects of the study, which allows adjustments as appropriate. Multi-arm, two stage AD has been applied to treatment selection and determining the most advantageous sample size for the study (P. Thall, R. Simon, and S Ellenberg, Biometrics 45, June 1989). 3 Dose Finding Schemes Finding the best dose is a common goal in early clinical trials. • 3 + 3 Design: With this design and its variations, dose finding is approached incrementally. Initially, a cohort of three subjects is studied and then three additional subjects are added, and so forth. Each set of cohorts adds data which can be analyzed when determining optimal dose. • Continuous Re-Assessment Method (CRM): Incorporating prior information and observation, CRM enables researchers to select the model based toxicity dose response curve and define the target toxicity (e.g. 33%). Based on the toxicity outcome from a cohort, the posterior distribution of shape parameters of the model can be updated. The probability of dose-limiting toxicity (DLT) occurrence at each dose level can be revised for each dose level and a dose can then be selected for the next cohort. Fixed late phase adaptive designs for clinical trials Adaptive design can also be effective for late phase and confirmatory clinical trials. Group Sequential Adaptive Clinical Trial Designs Group sequential AD for clinical trials provides detailed specifications for a group sequential trial, number of looks, stopping boundaries and sample size. These designs can provide early unblinded looks at interim analyses and protect Type 1 error from inflation of multiple looks. Boundaries can be determined for early stopping for success and fertility. The conditional power for significant outcome at final analysis can be calculated and sample size can be re-estimated. The following graphs show the O’Brien Fleming stopping boundaries in terms of z value for the hypothesis testing for a sequential design with four looks. The z value is shown at the first, the second, and the third look, as well as the conditional power after each look. It can be seen that at the third look, the z value crosses the stopping boundary. The null hypothesis is rejected. 4 Example: Lower low-density lipoprotein (LDL) Group Sequential Design: 4 looks, Type I =5%, Type II = 10%, Effect Size = 10% std. dev = 20%, O’Brien Fleming boundary First Look Conditional Power (Alt H): 0.74 Second Look Conditional Power (Alt H): 0.91 5 Third Look: Boundary crossed, trial can be stopped Enrichment Adaptive Design for Clinical Trials Adaptive enrichment designs enable a clinical trial to target therapies with patients that can most benefit from the treatment.
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