Clinical Trial Design

Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.

Gives advice on how to design a clinical trial and compares the different designs.

Poor clinical trial designs result in failed studies wasting research funds and limiting the advancement of cures for disorders. Clinical Trial Design Challenges in Mood Disorders outlines classic problems researchers face in designing clinical trials and discusses how best to address them for the most definitive and generalizable results. Traditional trial designs are included as well as novel analytic techniques. The book examines information on high placebo response, the generalizability of studies conducted in the developing world, the duration of maintenance studies, and the application of findings into clinical practice. With representation from contributors throughout the world and from academia, industry, regulatory agencies, and advocacy groups, this book will contribute toward improved clinical trial design and valid, precise, and reliable answers about what works better and faster for patients. Summarizes common trial design problems and their solutions Encompasses funding, subject selection, regulatory issues and more Identifies best practices for definitive and generalizable results Includes traditional trial designs and novel analytic techniques Represents academia, industry, regulatory agencies, and advocacy groups

Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment. Statistical design provides a means to achieve both these aims, while statistical data analysis provides methods for extracting useful information from the trial data. Recent advances in statistical computing have enabled statisticians to implement very rapidly a broad array of methods which previously were either impractical or impossible. Biostatisticians are now able to provide much greater support to medical researchers working in both clinical and laboratory settings. As our collective toolkit of techniques for analyzing data has grown, it has become increasingly difficult for biostatisticians to keep up with all the developments in our own field. Recent Advances in Clinical Trial Design and Analysis brings together biostatisticians doing cutting-edge research and explains some of the more recent developments in biostatistics to clinicians and scientists who work in clinical trials.

Clinical Trials, Second Edition, offers those engaged in clinical trial design a valuable and practical guide. This book takes an integrated approach to incorporate biomedical science, laboratory data of human study, endpoint specification, legal and regulatory aspects and much more with the fundamentals of clinical trial design. It provides an overview of the design options along with the specific details of trial design and offers guidance on how to make appropriate choices. Full of numerous examples and now containing actual decisions from FDA reviewers to better inform trial design, the 2nd edition of Clinical Trials is a must-have resource for early and mid-career researchers and clinicians who design and conduct clinical trials. Contains new and fully revised material on key topics such as biostatistics, biomarkers, orphan drugs, biosimilars, drug regulations in Europe, drug safety, regulatory approval and more Extensively covers the "study schema" and related features of study design Incorporates laboratory data from studies on human patients to provide a concrete tool for understanding the concepts in the design and conduct of clinical trials Includes decisions made by FDA reviewers when granting approval of a drug as real world learning examples for readers

Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

Clinical Trials: Study Design, Endpoints and Biomarkers, Drug Safety, and FDA and ICH Guidelines is a practical guidebook for those engaged in clinical trial design. This book details the organizations and content of clinical trials, including trial design, safety, endpoints, subgroups, HRQoL, consent forms and package inserts. It provides extensive information on both US and international regulatory guidelines and features concrete examples of study design from the medical literature. This book is intended to orient those new to clinical trial design and provide them with a better understanding of how to conduct clinical trials. It will also act as a guide for the more experienced by detailing endpoint selection and illustrating how to avoid unnecessary pitfalls. This book is a straightforward and valuable reference for all those involved in clinical trial design. Provides extensive coverage of the "study schema" and related features of study design Offers a "hands-on" reference that contains an overview of the process, but more importantly details a step-by-step account of clinical trial design Features examples from the medical literature to highlight how investigators choose the most suitable endpoint(s) for clinical trial and includes graphs from real clinical trials to help explain each concept in study design Integrates clinical trial design, pharmacology, biochemistry, cell biology and legal aspects to provide readers with a comprehensive look at all aspects of clinical trials Includes chapters on core material and important ancillary topics, such as package inserts, consent forms, and safety reporting forms used in the United States, England and Europe For complimentary access to our sample chapter (chapter 24), please copy and paste this link into your browser: http://tinyurl.com/awwutvn

On March 3-4, 2016, the National Academies of Sciences, Engineering, and Medicine's Forum on Neuroscience and Nervous System Disorders held a workshop in Washington, DC, bringing together key stakeholders to discuss opportunities for improving the integrity, efficiency, and validity of clinical trials for nervous system disorders. Participants in the workshop represented a range of diverse perspectives, including individuals not normally associated with traditional clinical trials. The purpose of this workshop was to generate discussion about not only what is feasible now, but what may be possible with the implementation of cutting-edge technologies in the future.