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Written by one of the preeminent experts in the field, this book covers commonly encountered controversial statistical issues in clinical trials and, whenever possible, makes recommendations to resolve these problems. It focuses on issues occurring at various stages of clinical research and development, including early-phase clinical development

Exploring applications in medical research and clinical epidemiology, this text continues to cover important issues related to the design and analysis of reliability and agreement studies. This edition contains a new chapter that describes various models for methods comparison studies as well as a new chapter on the analysis of reproducibility u

Drawing from the authors' courses on the subject as well as the first author's more than 30 years working in the pharmaceutical industry, Clinical Trial Methodology emphasizes the importance of statistical thinking in clinical research and presents the methodology as a key component of clinical research. From ethical issues and

Illustrating how stability studies play an important role in drug safety and quality assurance, this book introduces the basic concepts of stability testing, focuses on short-term stability studies, and reviews several methods for estimating drug expiration dating periods. The author compares some commonly employed study designs and discusses both

Focuses on full analyses of real data sets based on the needs and requirements of end users. Fundamental theory is introduced with emphasis on the motivation by challenges coming from real problems with real data. Complete explanations of important concepts are provided, but the amount of mathematical derivation of formulation is minimized.

Drug development sponsors cannot run individual trials for all products in all indications. This results in missed opportunities. Clinical trial programs known as "basket" and "umbrella" have demonstrated that multi-product, multi-indication trials can be efficient and feasible.

This book focuses on clinical trial design and monitoring with time-to-event endpoints. Detail of subjects of the book are included in book contents. This book not only provides a comprehensive review of existing methods. The book also presents a general group sequential method for trial monitoring which has not been published in any book.

This book deals with randomization in clinical trials. Currently trials use permuted blocks randomization almost exclusively. Many researchers are aware of the drawbacks to this fatally flawed method, and while many are unaware of any better randomization methods, in fact several groups have proposed improvements, and also demonstrated the benef

This book provides the application of generalized linear mixed-effects models and its related models in the statistical design and analysis of repeated measures adopted in randomized controlled trials. With increasing concerns about intra-patient variability of treatment effects, the traditional ANCOVA-type methods can no longer cope with these

When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate endpoint that can be measured in a more convenient or cost-effective way. This book focuses on the use of surrogate endpoint evaluation methods in practice, using SAS and R.

Missing data in longitudinal clinical trials has justifiably been the target of considerable research. However, missing data is just one of the many considerations in the analysis of longitudinal data, and focus on the data we don't have should not distract from focus on the data we do have. The statistical theory relevant to analyses of longitu

The premise of Quality by Design (QbD) is that the quality of the pharmaceutical product should be based upon a thorough understanding of both the product and the manufacturing process. This state-of-the-art book provides a single source of information on emerging statistical approaches to QbD and risk-based pharmaceutical development. A compreh

This book shows how to apply biclustering methods to find local patterns in a big data matrix. It presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. All

This book provides guidance on selecting specific benefit-risk (B-R) frameworks and quantitative methods. Leading experts from industry, regulatory agencies, and academia present practical examples, lessons learned, and best practices that illustrate how to conduct structured B-R assessment in clinical development and regulatory submission. The

This book presents a comprehensive overview on the current status of conducting MRCTs in clinical development. It first provides a high-level introduction to the context, motivation, opportunities, and challenges in simultaneous global clinical development using MRCTs. It then focuses on the design, monitoring, and analysis/interpretation of MRC

This guide explains how to apply health economic evaluation techniques to both clinical trial and non-clinical trial data. Through a simple, applied approach using examples and SAS software, the book helps statisticians and researchers in health economics assess cost-effectiveness. It covers trial design, case report form design, quality of life

This book presents statistical models and methods for the analysis of longitudinal data. It focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. The book also explores the possibility of unifying these models through a stochastic process point of

A critical issue in the development of biologics, immunogenicity can cause early termination or limited use of the products if not managed well. This book shows how to use robust statistical methods for detecting, quantifying, assessing, and mitigating immunogenicity risk. Along with covering regulatory requirements, the authors discuss statisti

This book explores a wide range of topics in exposure-response modeling, from traditional PKPD modeling to other areas in drug development and beyond. It incorporates numerous examples and software programs for implementing novel methods. The book emphasizes dose adjustment and treatment adaptation based on dynamic exposure-response models, illu

This book offers statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics. The book explains how to identify molecular biomarkers using DNA microarrays, validate the developed biomarkers, and confirm

This comprehensive reference covers all aspects of drug combination research, from designing in vitro drug combination studies to analyzing clinical trial data. Featuring contributions from researchers in industry, academia, and regulatory agencies, this balanced text provides researchers with a solid understanding of the available statis

One of the hallmarks of the 21st century medicine is the emergence of digital therapeutics (DTx)-evidence-based, clinically validated digital technologies to prevent, diagnose, treat, and manage various diseases and medical conditions. DTx solutions have been gaining interest from patients, investors, healthcare providers, health authorities, and other stakeholders because of the potential of DTx to deliver equitable, massively scalable, personalized and transformative treatments for different unmet medical needs.Digital Therapeutics: Scientific, Statistical, Clinical, and Regulatory Aspects is an unparalleled summary of the current scientific, statistical, developmental, and regulatory aspects of DTx which is poised to become the fastest growing area of the biopharmaceutical and digital medicine product development. This edited volume intends to provide a systematic exposition to digital therapeutics through 19 peer-reviewed chapters written by subject matter experts in this emerging field.This edited volume is an invaluable resource for business leaders and researchers working in public health, healthcare, digital health, information technology, and biopharmaceutical industries. It will be also useful for regulatory scientists involved in the review of DTx products, and for faculty and students involved in an interdisciplinary research on digital health and digital medicine.Key Features:Provides the taxonomy of the concepts and a navigation tool for the field of DTx.Covers important strategic aspects of the DTx industry, thereby helping investors, developers, and regulators gain a better appreciation of the potential value of DTx.Expounds on many existing and emerging state-of-the art scientific and technological tools, as well as data privacy, ethical and regulatory considerations for DTx product development.Presents several case studies of successful development of some of the most remarkable DTx products.Provides some perspectives and forward-looking statements on the future of digital medicine.