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The pharmaceutical industry is currently operating under a business model that is not sustainable for the future. Given the high costs associated with drug development, there is a vital need to reform this process in order to provide safe and effective drugs while still securing a profit. Re-Engineering Clinical Trials evaluates the trends and challenges associated with the current drug development process and presents solutions that integrate the use of modern communication technologies, innovations and novel enrichment designs. This book focuses on the need to simplify drug development and offers you well-established methodologies and best practices based on real-world experiences from expert authors across industry and academia. Written for all those involved in clinical research, development and clinical trial design, this book provides a unique and valuable resource for streamlining the process, containing costs and increasing drug safety and effectiveness. - Highlights the latest paradigm-shifts and innovation advances in clinical research - Offers easy-to-find best practice sections, lists of current literature and resources for further reading and useful solutions to day-to-day problems in current drug development - Discusses important topics such as safety profiling, data mining, site monitoring, change management, increasing development costs, key performance indicators and much more
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.
Innovation in Clinical Trial Methodologies: Lessons Learned during the Corona Pandemic presents a selection of updated chapters from Re-Engineering Clinical Trials that feature innovative options and methods in clinical trials. The Coronavirus pandemic is an accelerator for digitalization in many industries, including clinical trials. This book considers best practices, alternative study concepts requiring fewer patients, studies with less patient interaction, the design of "virtualized" protocols, and moving from data to decisions. This book will be helpful to pharmacologists, physicians and clinical researchers involved in the process of clinical development and clinical trial design.
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.
v. 1. Research findings -- v. 2. Concepts and methodology -- v. 3. Implementation issues -- v. 4. Programs, tools and products.
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.
Successful drug development relies on accurate and efficient clinical trials to deliver the best and most effective pharmaceuticals and clinical care to patients. However, the current model for clinical trials is outdated, inefficient and costly. Clinical trials are limited by small sample sizes that do not reflect variations among patients in the real world, financial burdens on participants, and slow processes, and these factors contribute to the disconnect between clinical research and clinical practice. On November 28-29, the National Academies of Sciences, Engineering, and Medicine convened a workshop to investigate the current clinical trials system and explore the potential benefits and challenges of implementing virtual clinical trials as an enhanced alternative for the future. This publication summarizes the presentations and discussions from the workshop.
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