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  • Cited by 7
Cambridge University Press
Online publication date:
May 2012
Print publication year:
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Book description

Translating laboratory discoveries into successful therapeutics can be difficult. Clinical Trials in Neurology aims to improve the efficiency of clinical trials and the development of interventions in order to enhance the development of new treatments for neurologic diseases. It introduces the reader to the key concepts underpinning trials in the neurosciences. This volume tackles the challenges of developing therapies for neurologic disorders from measurement of agents in the nervous system to the progression of clinical signs and symptoms through illustrating specific study designs and their applications to different therapeutic areas. Clinical Trials in Neurology covers key issues in Phase I, II and III clinical trials, as well as post-marketing safety surveillance. Topics addressed include regulatory and implementation issues, outcome measures and common problems in drug development. Written by a multidisciplinary team, this comprehensive guide is essential reading for neurologists, psychiatrists, neurosurgeons, neuroscientists, statisticians and clinical researchers in the pharmaceutical industry.

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  • 10 - Crossover Designs
    pp 101-112
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    Scientific discovery and clinical investigation are critical for developing and evaluating new treatments and can have substantial public health benefits. A detailed analysis of clinical trials funded by the National Institute of Neurological Disorders and Stroke found that the public return on investment in clinical trials has been substantial. In addition to the inherent risks involved in clinical trials, the challenges of translating scientific advances into new therapeutic advances are increasing. Many of the challenges of drug development are particularly acute for treatments of neurological conditions. The scope of clinical trials for neurological conditions is rapidly expanding to address orphan indications, biologics, medical devices, surgeries, and comparative effectiveness studies. In addition to drugs, clinical trials frequently evaluate devices for neurological conditions. High quality data on surgical interventions, such as temporal lobe resections for epilepsy are critical to understanding their relative risks and benefits in the target populations.
  • 12 - Enrichment Designs
    pp 127-134
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    This chapter focuses specifically on the activities and questions that are involved in the generation of data to support the registration and approval of a drug candidate. The data generated in early stage studies provide confidence for deciding whether to advance a drug into more complicated and expensive trials in specific patient populations. During middle stage development it is critical to begin to characterize the dose-response relationship for efficacy and safety endpoints in the selected population. Late stage confirmatory clinical trials often utilize a broader study population than was studied during early development. Besides the general scientific and medical literature, there are several important sources of information that can help with the strategy for clinical development programs and the design of specific trials and their questions. The FDA provides access to guidance documents that outline regulatory requirements related to the development of drugs and devices.
  • 13 - Non-Inferiority Trials
    pp 135-146
  • View abstract


    This chapter focuses on the challenges presented by therapeutic targets in the central nervous system (CNS), the manner in which animal models have and can be used to support the translation of therapeutic biologies to the human CNS, the blood brain barrier (BBB), and the uncertainties of CNS drug exposures. It also addresses how these challenges can be met and the associated risks of CNS therapeutic development mitigated. Animal CNS disease models are unique tools that have led to a significant increase in the number of potential new therapeutic targets and an improved understanding of the biologies underlying disease processes. Development of pharmacodynamic (Pd) biomarkers for CNS drug development should be a high priority. Pd biomarkers are used in Phase 1, 2, and 3 studies, although most commonly in Phase 1 and 2 studies.
  • 14 - Monitoring of Clinical Trials:
    pp 147-159
  • Interim Monitoring, Data Monitoring Committees, and Group Sequential Methods
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    This chapter highlights some important aspects of the design and analysis of clinical trials, and sketches a number of relevant statistical concepts. A controlled clinical trial of a medical intervention should have at least one primary hypothesis that drives its design. Well-designed and well-executed trials include an unambiguous protocol approved by the Institutional Review Boards (IRBs) or Ethics Committees of the participating clinics, laboratories, and data centers. The chapter also describes the basic frequentist statistical testing paradigm used by the typical randomized clinical trial with particular reference to ideas necessary in selecting sample size. Most clinical trials study more than one outcome of interest. Many neurological clinical trials compare therapies with respect to time to occurrence of the primary outcome. In the past, few clinical trials were performed in the Bayesian framework, but Bayesian methods have become more widely used recently.
  • Section 4 - Part
    pp 173-196
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    The goal of a controlled clinical trial is to compare the effects of interventions on outcomes of interest. This chapter considers the methods to limit bias and random error at each stage of a clinical trial-design, conduct, analysis and interpretation of results. Many aspects of study design relate to control of bias. The one of greatest importance is the method of assignment to treatment. Study assessments that incorporate some element of subjectivity can also be centralized. Many trials rely on a central adjudication group to make outcome assessments for all subjects in a study. In most studies, the treatments are compared with regard to multiple outcomes. From sample size considerations to central pathology review, from eligibility reviews to interim monitoring plans, all methodological considerations relate in one way or other to minimizing the potential for bias and reducing random error.
  • 17 - The Informed Consent Process:
    pp 187-196
  • Compliance and Beyond
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    This chapter provides an introduction to several fundamental methods for analyzing data from clinical trials, including an overview of two very important and related concepts: confidence intervals and tests of hypotheses. In making statistical inference, one draws a sample from a population and computes one or more statistics. Most confidence intervals use similar methods. In general, a confidence interval is made up of a point estimate, the standard error of that estimate, and a tabular value. The method of intention to treat has become the standard for analyzing data from clinical trials. Regulatory organizations such as FDA and the International Conference on Harmonisation (ICH) recommend that the primary efficacy analysis be based on the intention to treat principle. Multiple methods have been used to impute missing data. A method that was very commonly used in the past is called 'last observation carried forward' (LOCF).
  • Section 5 - Part
    pp 197-214
  • View abstract


    This chapter provides an overview of outcome measures in neurology clinical trials, including developing a conceptual endpoint model, role and use of biomarkers, and considerations on how to select, use and interpret them in the context of early-stage clinical trial design. Early stage clinical trials (phase 1-2) often employ biomarker targets for proof of concept or therapeutic validation. Therapeutic development programs can be viewed as in the learn zone and confirm zone, with confirmation occurring in the phase 3 trial designed to test clinical efficacy against a standard or placebo. Structural imaging with MRI or computed tomography (CT) has been used as both an entry criteria into clinical trials and as an outcome measure. MRI has frequently been used as a measure of treatment response of multiple sclerosis (MS) patients. Researchers should define the role each endpoint is intended to play in the clinical trial.

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