"Offers a comprehensive, unified presentation of statistical designs and methods of analysis for all stages of pharmaceutical development--emphasizing biopharmaceutical applications and demonstrating statistical techniques with real-world examples."

Reviews withdrawn draft guidance on analytical similarity assessment. Evaluates various methods for analytical similarity evaluation based on FDA’s current guidelines. Provides a general approach for the use of n-of-1 trial design for assessment of interchangeability. Discusses the feasibility and validity of the non-medical switch studies. Provides innovative thinking for detection of possible reference product change over time.

Reviews critical issues (e.g., endpoint/margin selection, sample size requirement 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. Makes recommendations to accurately and reliably 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 such as platform trials. Provides insight regarding current regulatory guidance on rare diseases drug development such as gene therapy.

With new statistical and scientific issues arising in adaptive clinical trial design, including the U.S. FDA's recent draft guidance, a new edition of one of the first books on the topic is needed. Adaptive Design Methods in Clinical Trials, Second Edition reflects recent developments and regulatory positions on the use of adaptive designs in clinical trials. It unifies the vast and continuously growing literature and research activities on regulatory requirements, scientific and practical issues, and statistical methodology. New to the Second EditionAlong with revisions throughout the text, this edition significantly updates the chapters on protocol amendment and clinical trial simulation to incorporate the latest changes. It also includes five entirely new chapters on two-stage adaptive design, biomarker adaptive trials, target clinical trials, sample size and power estimation, and regulatory perspectives. Following in the tradition of its acclaimed predecessor, this second edition continues to offer an up-to-date resource for clinical scientists and researchers in academia, regulatory agencies, and the pharmaceutical industry. Written in an intuitive style at a basic mathematical and statistical level, the book maintains its practical approach with an emphasis on concepts via numerous examples and illustrations.

Reviews critical issues (e.g., endpoint/margin selection, sample size requirement 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. Makes recommendations to accurately and reliably 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 such as platform trials. Provides insight regarding current regulatory guidance on rare diseases drug development such as gene therapy.

Advanced Statistics in Regulatory Critical Clinical Initiatives is focused on the critical clinical initiatives introduced by the 21st Century Cure Act passed by the United States Congress in December 2016. The book covers everything from the outline of the initiatives to analysis on the effect on biopharmaceutical research and development. Advanced Statistics in Regulatory Critical Clinical Initiatives provides innovative ways to resolve common challenges in statistical research of rare diseases such small sample sizes and provides guidance for combined use of data. With analysis from regulatory and scientific perspectives this book is an ideal companion for researchers in biostatistics, pharmaceutical development, and policy makers in related fields. Key Features: Provides better understanding of innovative design and analysis of each critical clinical initiatives which may be used in regulatory review/approval of drug development. Makes recommendations to evaluate submissions accurately and reliably. Proposes innovative study designs and statistical methods for oncology and/or rare disease drug development. Provides insight regarding current regulatory guidance on drug development such as gene therapy and rare diseases.

Methodologies for Biosimilar Product Development covers the practical and challenging issues that are commonly encountered during the development, review, and approval of a proposed biosimilar product. These practical and challenging issues include, but are not limited to the mix-up use of interval hypotheses testing (i.e., the use of TOST) and confidence interval approach, a risk/benefit assessment for non-inferiority/similarity margin, PK/PD bridging studies with multiple references, the detection of possible reference product change over time, design and analysis of biosimilar switching studies, the assessment of sensitivity index for assessment of extrapolation across indications without collecting data from those indications not under study, and the feasibility and validation of non-medical switch post-approval. Key Features: Reviews withdrawn draft guidance on analytical similarity assessment. Evaluates various methods for analytical similarity evaluation based on FDA's current guidelines. Provides a general approach for the use of n-of-1 trial design for assessment of interchangeability. Discusses the feasibility and validity of the non-medical switch studies. Provides innovative thinking for detection of possible reference product change over time. This book embraces innovative thinking of design and analysis for biosimilar studies, which are required for review and approval of biosimilar regulatory submissions.

Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually referred to as statistics in regulatory science or regulatory statistics. In a broader sense, statistics in regulatory science can be defined as valid statistics that are employed in the review and approval process of regulatory submissions of pharmaceutical products. In addition, statistics in regulatory science are involved with the development of regulatory policy, guidance, and regulatory critical clinical initiatives related research. This book is devoted to the discussion of statistics in regulatory science for pharmaceutical development. It covers practical issues that are commonly encountered in regulatory science of pharmaceutical research and development including topics related to research activities, review of regulatory submissions, recent critical clinical initiatives, and policy/guidance development in regulatory science. Devoted entirely to discussing statistics in regulatory science for pharmaceutical development. Reviews critical issues (e.g., endpoint/margin selection and complex innovative design such as adaptive trial design) in the pharmaceutical development and regulatory approval process. Clarifies controversial statistical issues (e.g., hypothesis testing versus confidence interval approach, missing data/estimands, multiplicity, and Bayesian design and approach) in review/approval of regulatory submissions. Proposes innovative thinking regarding study designs and statistical methods (e.g., n-of-1 trial design, adaptive trial design, and probability monitoring procedure for sample size) for rare disease drug development. Provides insight regarding current regulatory clinical initiatives (e.g., precision/personalized medicine, biomarker-driven target clinical trials, model informed drug development, big data analytics, and real world data/evidence). This book provides key statistical concepts, innovative designs, and analysis methods that are useful in regulatory science. Also included are some practical, challenging, and controversial issues that are commonly seen in the review and approval process of regulatory submissions. About the author Shein-Chung Chow, Ph.D. is currently a Professor at Duke University School of Medicine, Durham, NC. He was previously the Associate Director at the Office of Biostatistics, Center for Drug Evaluation and Research, United States Food and Drug Administration (FDA). Dr. Chow has also held various positions in the pharmaceutical industry such as Vice President at Millennium, Cambridge, MA, Executive Director at Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers Squibb, Plainsboro, NJ. He was elected Fellow of the American Statistical Association and an elected member of the ISI (International Statistical Institute). Dr. Chow is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and Biostatistics Book Series, Chapman and Hall/CRC Press, Taylor & Francis, New York. Dr. Chow is the author or co-author of over 300 methodology papers and 30 books.

In clinical trial practice, controversial statistical issues inevitably occur regardless of the compliance with good statistical practice and good clinical practice. But by identifying the causes of the issues and correcting them, the study objectives of clinical trials can be better achieved. Controversial Statistical Issues in Clinical Trials covers commonly encountered controversial statistical issues in clinical trials and, whenever possible, makes recommendations to resolve these problems. The book focuses on issues occurring at various stages of clinical research and development, including early-phase clinical development (such as bioavailability/bioequivalence), bench-to-bedside translational research, and late-phase clinical development. Numerous examples illustrate the impact of these issues on the evaluation of the safety and efficacy of the test treatment under investigation. The author also offers recommendations regarding possible resolutions of the problems. Written by one of the preeminent experts in the field, this book provides a useful desk reference and state-of-the art examination of problematic issues in clinical trials for scientists in the pharmaceutical industry, medical/statistical reviewers in government regulatory agencies, and researchers and students in academia.

In response to the US FDA's Critical Path Initiative, innovative adaptive designs are being used more and more in clinical trials due to their flexibility and efficiency, especially during early phase development. Handbook of Adaptive Designs in Pharmaceutical and Clinical Development provides a comprehensive and unified presentation of the principles and latest statistical methodologies used when modifying trial procedures based on accrued data of ongoing clinical trials. The book also gives a well-balanced summary of current regulatory perspectives. The first several chapters focus on the fundamental theory behind adaptive trial design, the application of the Bayesian approach to adaptive designs, and the impact of potential population shift due to protocol amendments. The book then presents a variety of statistical methods for group sequential design, classical design, dose-finding trials, Phase I/II and Phase II/III seamless adaptive designs, multiple stage seamless adaptive trial design, adaptive randomization trials, hypotheses-adaptive design, and treatment-adaptive design. It also covers predictive biomarker diagnostics for new drug development, clinical strategies for endpoint selection in translational research, the role of independent data monitoring committees in adaptive clinical trials, the enrichment process in targeted clinical trials for personalized medicine, applications of adaptive designs that use genomic or genetic information, adaptive trial simulation, and the efficiency of adaptive design. The final chapters discuss case studies as well as standard operating procedures for good adaptive practices. With contributions from leading clinical researchers in the pharmaceutical industry, academia, and regulatory agencies, this handbook offers an up-to-date, complete treatment of the principles and methods of adaptive design and analysis. Along with reviewing recent developments, it examines issues commonly encountered when applying adaptive design methods in clinical trials.

The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates. Pharmaceutical companies conduct stability studies to characterize the degradation of drug products and to estimate drug shelf life. Illustrating how stability studies play an important role in drug safety and quality assurance, Statistical Design and Analysis of Stability Studies presents the principles and methodologies in the design and analysis of stability studies. After introducing the basic concepts of stability testing, the book focuses on short-term stability studies and reviews several methods for estimating drug expiration dating periods. It then compares some commonly employed study designs and discusses both fixed and random batch statistical analyses. Following a chapter on the statistical methods for stability analysis under a linear mixed effects model, the book examines stability analyses with discrete responses, multiple components, and frozen drug products. In addition, the author provides statistical methods for dissolution testing and explores current issues and recent developments in stability studies. To ensure the safety of consumers, professionals in the field must carry out stability studies to determine the reliability of drug products during their expiration period. This book provides the material necessary for you to perform stability designs and analyses in pharmaceutical research and development.

Emphasizing the role of good statistical practices (GSP) in drug research and formulation, this book outlines important statistics applications for each stage of pharmaceutical development to ensure the valid design, analysis, and assessment of drug products under investigation and establish the safety and efficacy of pharmaceutical compounds. Coverage include statistical techniques for assay validation and evaluation of drug performance characteristics, testing population/individual bioequivalence and in vitro bioequivalence according to the most recent FDA guidelines, basic considerations for the design and analysis of therapeutic equivalence and noninferiority trials.

"Offers a comprehensive, unified presentation of statistical designs and methods of analysis for all stages of pharmaceutical development--emphasizing biopharmaceutical applications and demonstrating statistical techniques with real-world examples."

Preeminent Experts Update a Well-Respected Book Taking into account the regulatory and scientific developments that have occurred since the second edition, Design and Analysis of Bioavailability and Bioequivalence Studies, Third Edition provides a complete presentation of the latest progress of activities and results in bioavailability and bioequivalence on regulatory requirements, scientific and practical issues, and statistical methodology. New to the Third Edition Four new chapters that present a thorough account of novel developments in the field New and updated sections that reflect recent advances in the statistical methodology in the design and analysis of bioavailability and bioequivalence studies Reorganization of the material into five parts, making it easier to access related information together Over 100 new references from the literature Like its bestselling predecessors, this edition covers all of the statistical problems that may occur in the various stages of design and data analysis. Keeping the mathematics and statistics at a fundamental level, it continues to focus on practical concepts rather than technical details.

The growth of the pharmaceutical industry over the past decade is astounding, but the impact of this growth on statistics is somewhat confusing. While software has made analysis easier and more efficient, regulatory bodies now demand deeper and more complex analyses, and pharmacogenetic/genomic studies serve up an entirely new set of challenges. For more than two decades, Statistics in the Pharmaceutical Industry has been the definitive guide to sorting through the challenges in the industry, and this Third Edition continues that tradition. Updated and expanded to reflect the most recent trends and developments in the field, Statistics in the Pharmaceutical Industry, Third Edition presents chapters written by experts from both regulatory agencies and pharmaceutical companies who discuss everything from experimental design to post-marketing studies. This approach sheds light on what regulators consider acceptable methodologies and what methods have proven successful for industrial statisticians. Both new and revised chapters reflect the increasingly global nature of the industry as represented by authors from Japan and Europe, the increasing trend toward non-inferiority/equivalence testing, adaptive design in clinical trials, global harmonization of regulatory standards, and multiple comparison studies. The book also examines the latest considerations in anti-cancer studies. Statistics in the Pharmaceutical Industry, Third Edition demystifies the approval process by combining regulatory and industrial points of view, making it a must-read for anyone performing statistical analysis at any point in the drug approval process.

With new statistical and scientific issues arising in adaptive clinical trial design, including the U.S. FDA's recent draft guidance, a new edition of one of the first books on the topic is needed. Adaptive Design Methods in Clinical Trials, Second Edition reflects recent developments and regulatory positions on the use of adaptive designs in clinical trials. It unifies the vast and continuously growing literature and research activities on regulatory requirements, scientific and practical issues, and statistical methodology. New to the Second EditionAlong with revisions throughout the text, this edition significantly updates the chapters on protocol amendment and clinical trial simulation to incorporate the latest changes. It also includes five entirely new chapters on two-stage adaptive design, biomarker adaptive trials, target clinical trials, sample size and power estimation, and regulatory perspectives. Following in the tradition of its acclaimed predecessor, this second edition continues to offer an up-to-date resource for clinical scientists and researchers in academia, regulatory agencies, and the pharmaceutical industry. Written in an intuitive style at a basic mathematical and statistical level, the book maintains its practical approach with an emphasis on concepts via numerous examples and illustrations.

When a biological drug patent expires, alternative biosimilar products are developed. The development of biosimilar products is complicated and involves numerous considerations and steps. The assessment of biosimilarity and interchangeability is also complicated and difficult. Biosimilar Drug Product Development presents current issues for the development of biosimilars and gives detailed reviews of its various stages and contributing factors as well as relevant regulatory pathways and pre- and post-approval issues.

Praise for the Second Edition: "... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics "This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." - Journal of the Royal Statistical Society Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation. Features: Compares the relative merits and disadvantages of statistical methods for sample size calculations Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women's health Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation.

As many biological products face losing their patents in the next decade, the pharmaceutical industry needs an abbreviated regulatory pathway for approval of biosimilar drug products, which are cost-effective, follow-on/subsequent versions of the innovator's biologic products. But scientific challenges remain due to the complexity of both the manufacturing process and the structures of biosimilar products. Written by a top biostatistics researcher, Biosimilars: Design and Analysis of Follow-on Biologics is the first book entirely devoted to the statistical design and analysis of biosimilarity and interchangeability of biosimilar products. It includes comparability tests of important quality attributes at critical stages of the manufacturing processes of biologic products. Connecting the pharmaceutical/biotechnology industry, government regulatory agencies, and academia, this state-of-the-art book focuses on the scientific factors and practical issues related to the design and analysis of biosimilar studies. It covers most of the statistical questions encountered in various study designs at different stages of research and development of biological products.

As the development of medicines has become more globalized, the geographic variations in the efficacy and safety of pharmaceutical products need to be addressed. To accelerate the product development process and shorten approval time, researchers are beginning to design multiregional trials that incorporate subjects from many countries around the world under the same protocol. Design and Analysis of Bridging Studies addresses the issues arising from bridging studies and multiregional clinical trials. For bridging studies, the book explores ethnic sensitivity, the necessity of bridging studies, types of bridging studies, and the assessment of similarity between regions based on bridging evidence. For multiregional clinical trials, the text considers regional differences, assesses the consistency of treatment effect across regions, and discusses sample size determination for each region. Taking into account the International Conference Harmonisation (ICH) E5 framework for bridging studies, the book provides a unified summary of the growing literature and research activities in this area. It covers the regulatory requirements, scientific and practical issues, and statistical methodology for designing and evaluating bridging studies and multiregional clinical trials, with the goal of inspiring new research activities in the field.

This book focuses on analytical similarity assessment in biosimilar product development following the FDA's recommended stepwise approach for obtaining totality-of-the-evidence for approval of biosimilar products. It covers concepts such as the tiered approach for assessment of similarity of critical quality attributes in the manufacturing process of biosimilar products, models/methods like the statistical model for classification of critical quality attributes, equivalence tests for critical quality attributes in Tier 1 and the corresponding sample size requirements, current issues, and recent developments in analytical similarity assessment.

As the development of medicines has become more globalized, the geographic variations in the efficacy and safety of pharmaceutical products need to be addressed. To accelerate the product development process and shorten approval time, researchers are beginning to design multiregional trials that incorporate subjects from many countries around the world under the same protocol. Design and Analysis of Bridging Studies addresses the issues arising from bridging studies and multiregional clinical trials. For bridging studies, the book explores ethnic sensitivity, the necessity of bridging studies, types of bridging studies, and the assessment of similarity between regions based on bridging evidence. For multiregional clinical trials, the text considers regional differences, assesses the consistency of treatment effect across regions, and discusses sample size determination for each region. Taking into account the International Conference Harmonisation (ICH) E5 framework for bridging studies, the book provides a unified summary of the growing literature and research activities in this area. It covers the regulatory requirements, scientific and practical issues, and statistical methodology for designing and evaluating bridging studies and multiregional clinical trials, with the goal of inspiring new research activities in the field.

"Provides well-integrated, comprehensive coverage of all the major statistical designs and methods used for animal studies in pharmaceutical research and development. Demonstrates the correct way to interpret the results of animal studies in the risk assessment of biopharmaceutical products and clarifies detailed presentations with real-world examples. "

When a biological drug patent expires, alternative biosimilar products are developed. The development of biosimilar products is complicated and involves numerous considerations and steps. The assessment of biosimilarity and interchangeability is also complicated and difficult. Biosimilar Drug Product Development presents current issues for the development of biosimilars and gives detailed reviews of its various stages and contributing factors as well as relevant regulatory pathways and pre- and post-approval issues.

Quantitative Methods in HIV/AIDS Research provides a comprehensive discussion of modern statistical approaches for the analysis of HIV/AIDS data. The first section focuses on statistical issues in clinical trials and epidemiology that are unique to or particularly challenging in HIV/AIDS research; the second section focuses on the analysis of laboratory data used for immune monitoring, biomarker discovery and vaccine development; the final section focuses on statistical issues in the mathematical modeling of HIV/AIDS pathogenesis, treatment and epidemiology. This book brings together a broad perspective of new quantitative methods in HIV/AIDS research, contributed by statisticians and mathematicians immersed in HIV research, many of whom are current or previous leaders of CFAR quantitative cores. It is the editors' hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of understanding and addressing the AIDS pandemic.