Vladimir Dragalin

Adaptive designs in clinical drug development--an Executive Summary of the PhRMA Working Group.

A PhRMA Working Group on adaptive clinical trial designs has been formed to investigate and facilitate opportunities for wider acceptance and usage of adaptive designs and related methodologies. A White Paper summarizing the findings of the group is in preparation; this article is an Executive Summary for that full White Paper, and summarizes the findings and recommendations of the group. Logistic, operational, procedural, and statistical challenges associated with adaptive designs are addressed. Three particular areas where it is felt that adaptive designs can be utilized beneficially are discussed: dose finding, seamless Phase II/III trials designs, and sample size reestimation.

Adaptive designs : Terminology and classification

In this article, we give a general definition of adaptive designs, describe their structure, and provide a classification of adaptive designs, mapping them against the drug development process.

Adaptive seamless Phase II/III designs : Background, operational aspects, and examples

Adaptive seamless designs have been considered as one possible way to shorten the time and patient exposure necessary to discover, develop, and demonstrate the benefits of a new drug. We introduce the concept of adaptive designs and describe the current statistical methodologies that relate to adaptive seamless designs. We also describe the decision process involved with seamless designs and present some illustrative examples.

A Simulation Study to Compare New Adaptive Dose–Ranging Designs

The main goals in an adaptive dose-ranging study are to detect dose response, to determine if any doses(s) meets clinical relevance, to estimate the dose-response, and then to decide on the dose(s) (if any) to take into the confirmatory Phase III. Adaptive dose-ranging study designs may result in power gains to detect dose response and higher precision in estimating the target dose and the dose response curve. In this article, we complement the library of available methods with five new adaptive dose-ranging designs. Due to their inherent complexity, the operating characteristics can be assessed only through intensive simulations. We present here results of a comprehensive simulation study that compares and contrasts these designs for a variety of different scenarios.

Adaptive Designs for Dose-Finding Studies Based on Sigmoid E max Model

We propose an adaptive procedure for dose-finding in clinical trials when the primary efficacy endpoint is continuous. We model the mean of the efficacy endpoint, given the dose, as a four-parameter logistic function. The efficacy endpoint at each dose is distributed according to either a normal or a gamma distribution. We consider the cases of fixed variance and fixed coefficient of variation assuming them to be both known and unknown. The analytic formulae for the Fisher information matrix are obtained, which are used to build the locally and adaptive D -optimal designs.

Adaptive and Model-Based Dose-Ranging Trials: Quantitative Evaluation and Recommendations. White Paper of the PhRMA Working Group on Adaptive Dose-Ranging Studies

Poor dose-regimen selection remains a key cause of the high attrition rate of investigational drugs in confirmatory trials, being directly related to the escalating costs of drug development. This article is a follow-up to the first white paper put forward by the PhRMA Working Group (WG) on Adaptive Dose-Ranging Studies (Bornkamp et al. 2007). It presents results and conclusions from a new round of simulation-based evaluations conducted by the WG, proposing a new set of recommendations to improve the accuracy and efficiency of dose-finding in clinical drug development.

Adaptive Designs in Clinical Drug Development: Opportunities, Challenges, and Scope Reflections Following PhRMA's November 2006 Workshop

This paper provides reflections on the opportunities, scope and challenges of adaptive design as discussed at PhRMAs workshop held in November 2006. We also provide a status report of workstreams within PhRMAs working group on adaptive designs, which were triggered by the November workshop. Rather than providing a comprehensive review of the presentations given, we limit ourselves to a selection of key statements. The authors reflect the position of PhRMAs working group on adaptive designs.

Planning and Executing Response-Adaptive Learn-Phase Clinical Trials: 1. The Process

The planning and execution of clinical trials utilizing response-adaptive allocation involves complexities beyond those encountered in the planning and execution of more traditional trial designs. How the adaptive design will optimize the drug development process must be clearly defined; an appropriate endpoint must be selected to drive the adaptive design engine; and steps must be taken to ensure that the data required for adaptive decision making will be available in a timely fashion during the trial. Trial simulations are essential during the planning stage to develop appropriate decision rules and the response-adaptive allocation algorithm. Structures such as data monitoring committees and independent statistical centers help to ensure the validity and integrity of the trial, while facilitating decision making during the trial.

Views on Emerging Issues Pertaining to Data Monitoring Committees for Adaptive Trials

In this paper, the authors express their views on a range of topics related to data monitoring committees (DMCs) for adaptive trials that have emerged recently. The topics pertain to DMC roles and responsibilities, membership, training, and communication. DMCs have been monitoring trials using the group sequential design (GSD) for over 30 years. While decisions may be more complicated with novel adaptive designs, the fundamental roles and responsibilities of a DMC will remain the same, namely, to protect patient safety and ensure the scientific integrity of the trial. It will be the DMC’s responsibility to recommend changes to the trial within the scope of a prespecified adaptation plan or decision criteria and not to otherwise recommend changes to the study design except for serious safety-related concerns. Nevertheless, compared with traditional data monitoring, some additional considerations are necessary when convening DMCs for novel adaptive designs. They include the need to identify DMC members who are familiar with adaptive design and to consider possible sponsor involvement in unique situations. The need for additional expertise in DMC members has prompted some researchers to propose alternative DMC models or alternative governance model. These various options and authors’ views on them are expressed in this article.

ESTIMATION OF THE COMBINED RESPONSE TO TREATMENT IN MULTICENTER TRIALS

Analyses of multicenter trials consider the estimated treatment effect differences of the individual centers and combine them into an estimate of the overall treatment effect. There has been much debate in the literature concerning the best way to combine these treatment effect differences. We emphasize that first of all one should define the combined response to treatment (CRT), the object that has to be estimated from the results of a multicenter clinical trial. It is shown that the choice of CRT determines not only the best estimator, but also the allocation of patients among the centers that minimizes the mean squared error. A new estimator of the CRT is proposed that is based on a preliminary clustering of the centers and the use of a weighted average of the Type I estimators obtained from within each cluster. The clustering aims to minimize the bias of the combined estimator. We show via a simulation study that the simple clustering procedure provides a reasonably improved estimator. The clustering can be done on blinded data, as long as the numbers of patients on each treatment arm in each center are known. The methodology is illustrated by analyzing a multicountry, multicenter trial to compare an active treatment with placebo for the treatment of a psychiatric disorder.