Multiregional Clinical Trials For Simultaneous Global New Drug Development

Global simultaneous development is becoming more necessary as the cost of developing medical products continues to grow. The strategy of using multiregional clinical trials (MRCTs) has become the preferred method for developing new medicines. Implementing the same protocol to include subjects from many geographical regions around the world, MRCTs can speed up the patient enrolment, thus resulting in quicker drug development and obtaining faster approval of the drug globally. After the publication of the editors’ first volume on this topic, there have been new developments on MRCTs. The International Council for Harmonisation (ICH) issued ICH E17, a guideline document on MRCTs, in November 2017, laying out principles on MRCTs. Beyond E17, new methodologies have been developed as well. Simultaneous Global New Drug Development: Multi-Regional Clinical Trials after ICH E17 collects chapters providing interpretations of principles in ICH E17 and new ideas of implementing MRCTs. Authors are from different regions, and from academia and industry. In addition, in contrast to the first book, new perspectives are brought to MRCT from regulatory agencies. This book will be of particular interest to biostatisticians working in late stage clinical development of medical products. It will also be especially helpful for statisticians in regulatory agencies, and medical research institutes. This book is comprehensive across the MRCT topic spectrum, including Issues regarding ICH E17 Implementation MRCT Design and Analysis Methodologies Perspectives from authorities in regulatory agencies, as well as statisticians practicing in the medical product industry Many examples of real-life applications based on actual MRCTs.

In a global clinical development strategy, multiregional clinical trials (MRCTs) are vital in the development of innovative medicines. Multiregional Clinical Trials for Simultaneous Global New Drug Development presents a comprehensive overview on the current status of conducting MRCTs in clinical development. International experts from academia, in

New Drug Development: Second Edition provides an overview of the design concepts and statistical practices involved in therapeutic drug development. This wide spectrum of activities begins with identifying a potentially useful drug candidate that can perhaps be used in the treatment or prevention of a condition of clinical concern, and ends with marketing approval being granted by one or more regulatory agencies. In between, it includes drug molecule optimization, nonclinical and clinical evaluations of the drug’s safety and efficacy profiles, and manufacturing considerations. The more inclusive term lifecycle drug development can be used to encompass the postmarketing surveillance that is conducted all the time that a drug is on the market and being prescribed to patients with the relevant clinical condition. Information gathered during this time can be used to modify the drug (for example, dose prescribed, formulation, and mode of administration) in terms of its safety and its effectiveness. The central focus of the first edition of this book is captured by its subtitle, 'Design, Methodology, and Analysis'. Optimum quality study design and experimental research methodology must be employed if the data collected—numerical representations of biological information—are to be of optimum quality. Optimum quality data facilitate optimum quality statistical analysis and interpretation of the results obtained, which in turn permit optimum quality decisions to be made: Rational decision making is predicated on appropriate research questions and optimum quality numerical information. The book took a non-computational approach to statistics, presenting instead a conceptual framework and providing readers with a sound working knowledge of the importance of design, methodology, and analysis. Not everyone needs to be an expert in statistical analysis, but it is very helpful for work (or aspire to work) in the pharmaceutical and biologics industries to be aware of the fundamental importance of a sound scientific and clinical approach to the planning, conduct, and analysis of clinical trials.

Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995.

This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug. It takes a holistic approach towards drug development by incorporating explicitly knowledge learned from the earlier part of the development and available historical information into decisions at later stages. In addition, the book shares lessons learned from several select examples published in the literature since the publication of the first edition. The second edition reiterates the need for making evidence-based Go/No Go decisions in drug development discussed in the first edition. It substantially expands several topics that have seen great advances since the publication of the first edition. The most noticeable additions include three adaptive trials conducted in recent years that offer excellent learning opportunities, the use of historical data in the design and analysis of clinical trials, and extending decision criteria to the cases when the primary endpoint is binary. The examples used to illustrate the additional materials all come from real trials with some post-trial reflections offered by the authors. The book begins with an overview of product development and regulatory approval pathways. It then discusses how to incorporate prior knowledge into study design and decision making at different stages of drug development. Prior knowledge includes information pertaining to historical controls. To assist decision making, the book discusses appropriate metrics and the formulation of go/no-go decisions for progressing a drug candidate to the next development stage. Using the concept of the positive predictive value in the field of diagnostics, the book leads readers to the assessment of the probability that an investigational product is effective given positive study outcomes. Lastly, the book points out common mistakes made by drug developers under the current drug-development paradigm. The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have a basic understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization. The authors provide software codes for select analytical approaches discussed in the book. The book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making themselves.

This book provides an overview of the theories and applications on subgroups in the biopharmaceutical industry. Drawing from a range of expert perspectives in academia and industry, this collection offers an overarching dialogue about recent advances in biopharmaceutical applications, novel statistical and methodological developments, and potential future directions. The volume covers topics in subgroups in clinical trial design; subgroup identification and personalized medicine; and general issues in subgroup analyses, including regulatory ones. Included chapters present current methods, theories, and case applications in the diverse field of subgroup application and analysis. Offering timely perspectives from a range of authoritative sources, the volume is designed to have wide appeal to professionals in the pharmaceutical industry and to graduate students and researchers in academe and government.

The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.

This contributed volume presents an overview of concepts, methods, and applications used in several quantitative areas of drug research, development, and marketing. Chapters bring together the theories and applications of various disciplines, allowing readers to learn more about quantitative fields, and to better recognize the differences between them. Because it provides a thorough overview, this will serve as a self-contained resource for readers interested in the pharmaceutical industry, and the quantitative methods that serve as its foundation. Specific disciplines covered include: Biostatistics Pharmacometrics Genomics Bioinformatics Pharmacoepidemiology Commercial analytics Operational analytics Quantitative Methods in Pharmaceutical Research and Development is ideal for undergraduate students interested in learning about real-world applications of quantitative methods, and the potential career options open to them. It will also be of interest to experts working in these areas.