Drug development is a strictly regulated area. As such, marketing approval of a new drug depends heavily, if not exclusively, on evidence generated from clinical trials. Drug development has seen tremendous innovation in science and technology that has revolutionized the treatment of some diseases. And yet, the statistical design and practical conduct of the clinical trials used to test new therapeutics for safety and efficacy have changed very little over the decades. Our approach to clinical trials is steeped in convention and tradition. The large, fixed, randomized controlled trial methods that have been the gold standard are well understood and expected by many trial stakeholders. However, this approach is not well suited to all aspects of modern drug development and the current competitive landscape. We now see new therapies that target a small fraction of the patient population, rare diseases with high unmet medical needs, and pediatric populations that must wait for years for new drug approvals from the time that therapies are approved in adults. Large randomized clinical trials are at best inefficient and at worst completely infeasible in many modern clinical settings. Advances in technology and data infrastructure call for innovations in clinical trial design. Despite advances in statistical methods, the availability of information, and computing power, the actual experience with innovative design in clinical trials across industry and academia is limited. This book will be an important showcase of the potential for these innovative designs in modern drug development and will be an important resource to guide those who wish to undertake them for themselves. This book is ideal for professionals in the pharmaceutical industry and regulatory agencies, but it will also be useful to academic researchers, faculty members, and graduate students in statistics, biostatistics, public health, and epidemiology due to its focus on innovation. Key Features: Is written by pharmaceutical industry experts, academic researchers, and regulatory reviewers; this is the first book providing a comprehensive set of case studies related to statistical methodology, implementation, regulatory considerations, and communication of complex innovative trial design Has a broad appeal to a multitude of readers across academia, industry, and regulatory agencies Each contribution is a practical case study that can speak to the benefits of an innovative approach but also balance that with the real-life challenges encountered A complete understanding of what is actually being done in modern clinical trials will broaden the reader’s capabilities and provide examples to first mimic and then customize and expand upon when exploring these ideas on their own

Drug development is a strictly regulated area. As such, marketing approval of a new drug depends heavily, if not exclusively, on evidence generated from clinical trials. Drug development has seen tremendous innovation in science and technology that has revolutionized the treatment of some diseases. And yet, the statistical design and practical conduct of the clinical trials used to test new therapeutics for safety and efficacy have changed very little over the decades. Our approach to clinical trials is steeped in convention and tradition. The large, fixed, randomized controlled trial methods that have been the gold standard are well understood and expected by many trial stakeholders. However, this approach is not well suited to all aspects of modern drug development and the current competitive landscape. We now see new therapies that target a small fraction of the patient population, rare diseases with high unmet medical needs, and pediatric populations that must wait for years for new drug approvals from the time that therapies are approved in adults. Large randomized clinical trials are at best inefficient and at worst completely infeasible in many modern clinical settings. Advances in technology and data infrastructure call for innovations in clinical trial design. Despite advances in statistical methods, the availability of information, and computing power, the actual experience with innovative design in clinical trials across industry and academia is limited. This book will be an important showcase of the potential for these innovative designs in modern drug development and will be an important resource to guide those who wish to undertake them for themselves. This book is ideal for professionals in the pharmaceutical industry and regulatory agencies, but it will also be useful to academic researchers, faculty members, and graduate students in statistics, biostatistics, public health, and epidemiology due to its focus on innovation. Key Features: Is written by pharmaceutical industry experts, academic researchers, and regulatory reviewers; this is the first book providing a comprehensive set of case studies related to statistical methodology, implementation, regulatory considerations, and communication of complex innovative trial design Has a broad appeal to a multitude of readers across academia, industry, and regulatory agencies Each contribution is a practical case study that can speak to the benefits of an innovative approach but also balance that with the real-life challenges encountered A complete understanding of what is actually being done in modern clinical trials will broaden the reader's capabilities and provide examples to first mimic and then customize and expand upon when exploring these ideas on their own

"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

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.

Case Studies in Public Health contains selected case studies of some of the most important and influential moments in medicine and epidemiology. The cases chosen for this collection represent a wide array of public health issues that go into the makeup of what can be termed the New Public Health (NPH), which includes traditional public health, such as sanitation, hygiene and infectious disease control, but widens its perspective to include the organization, financing and quality of health care services in a much broader sense. Each case study is presented in a systematic fashion to facilitate learning, with the case, background, current relevance, economic issues, ethical issues, conclusions, recommendation and references discussed for each case. The book is a valuable resource for advanced students and researchers with specialized knowledge who need further information on the general background and history of public health and important scientific discoveries within the field. It is an ideal resource for students in public health, epidemiology, medicine, anthropology, and sociology, and for those interested in how to apply lessons from the past to present and future research. - Explores the history of public health through important scientific events and flashpoints - Presents case studies in a clear, direct style that is easy to follow - Uses a systematic approach to help learn lessons from the past and apply them to the present

This book explores the ways in which socio-technical settings in medical contexts find varying articulations in a specific locale. Focusing on Japan, it consists of nine case studies on topics concerning: experiences with radiation in Hiroshima, Nagasaki, and Fukushima; patient security, end-of-life and high-tech medicine in hospitals; innovation and diffusion of medical technology; and the engineering and evaluating of novel devices in clinical trials. The individual chapters situate humans and devices in medical settings in their given semantic, pragmatic, institutional and historical context. A novel interdisciplinary approach offers deep insights beyond the manifold findings of each case study, thereby enriching academic discussions on socio-technical settings in medical contexts amongst affiliated disciplines. This volume will be of broad interest to scholars, practitioners, policy makers and students from various disciplines, including Science and Technology Studies (STS), medical humanities, social sciences, ethics and law, business and innovation studies, as well as biomedical engineering, medicine and public health.

In the United States, a rare disease is defined by the Orphan Drug Act as a disorder or condition that affects fewer than 200,000 persons. For the approval of "orphan" drug products for rare diseases, the traditional approach of power analysis for sample size calculation is not feasible because there are only limited number of subjects available for clinical trials. In this case, innovative approaches are needed for providing substantial evidence meeting the same standards for statistical assurance as drugs used to treat common conditions. Innovative Methods for Rare Disease Drug Development focuses on biostatistical applications in terms of design and analysis in pharmaceutical research and development from both regulatory and scientific (statistical) perspectives. Key Features: Reviews critical issues (e.g., endpoint/margin selection, sample size requirements, and complex innovative design). Provides better understanding of statistical concepts and methods which may be used in regulatory review and approval. Clarifies controversial statistical issues in regulatory review and approval accurately and reliably. Makes recommendations to evaluate rare diseases regulatory submissions. Proposes innovative study designs and statistical methods for rare diseases drug development, including n-of-1 trial design, adaptive trial design, and master protocols like platform trials. Provides insight regarding current regulatory guidance on rare diseases drug development like gene therapy.

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.

The National Cancer Institute's (NCI) Clinical Trials Cooperative Group Program has played a key role in developing new and improved cancer therapies. However, the program is falling short of its potential, and the IOM recommends changes that aim to transform the Cooperative Group Program into a dynamic system that efficiently responds to emerging scientific knowledge; involves broad cooperation of stakeholders; and leverages evolving technologies to provide high-quality, practice-changing research.

To explore the role of the National Institutes of Health (NIH) in innovative drug development and its impact on patient access, the Board on Health Care Services and the Board on Health Sciences Policy of the National Academies jointly hosted a public workshop on July 24â€"25, 2019, in Washington, DC. Workshop speakers and participants discussed the ways in which federal investments in biomedical research are translated into innovative therapies and considered approaches to ensure that the public has affordable access to the resulting new drugs. This publication summarizes the presentations and discussions from the workshop.