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Author: Todd Coffey
Publisher: CRC Press
ISBN: 1498721419
Category : Mathematics
Languages : en
Pages : 358
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Book Description
Written specifically for biotechnology scientists, engineers, and quality professionals, this book describes and demonstrates the proper application of statistical methods throughout Chemistry, Manufacturing, and Controls (CMC). Filled with case studies, examples, and easy-to-follow explanations of how to perform statistics in modern software, it is the first book on CMC statistics written primarily for practitioners. While statisticians will also benefit from this book, it is written particularly for industry professionals who don’t have access to a CMC statistician or who want to be more independent in the design and analysis of their experiments. Provides an introduction to the statistical concepts important in the biotechnology industry Focuses on concepts with theoretical details kept to a minimum Includes lots of real examples and case studies to illustrate the methods Uses JMP software for implementation of the methods Offers a text suitable for scientists in the industry with some quantitative training Written and edited by seasoned veterans of the biotechnology industry, this book will prove useful to a wide variety of biotechnology professionals. The book brings together individual chapters that showcase the use of statistics in the most salient areas of CMC.
Author: Todd Coffey
Publisher: CRC Press
ISBN: 1498721419
Category : Mathematics
Languages : en
Pages : 358
Get Book Here
Book Description
Written specifically for biotechnology scientists, engineers, and quality professionals, this book describes and demonstrates the proper application of statistical methods throughout Chemistry, Manufacturing, and Controls (CMC). Filled with case studies, examples, and easy-to-follow explanations of how to perform statistics in modern software, it is the first book on CMC statistics written primarily for practitioners. While statisticians will also benefit from this book, it is written particularly for industry professionals who don’t have access to a CMC statistician or who want to be more independent in the design and analysis of their experiments. Provides an introduction to the statistical concepts important in the biotechnology industry Focuses on concepts with theoretical details kept to a minimum Includes lots of real examples and case studies to illustrate the methods Uses JMP software for implementation of the methods Offers a text suitable for scientists in the industry with some quantitative training Written and edited by seasoned veterans of the biotechnology industry, this book will prove useful to a wide variety of biotechnology professionals. The book brings together individual chapters that showcase the use of statistics in the most salient areas of CMC.
Author: Todd Coffey
Publisher: CRC Press
ISBN: 1351646346
Category : Mathematics
Languages : en
Pages : 428
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Book Description
Written specifically for biotechnology scientists, engineers, and quality professionals, this book describes and demonstrates the proper application of statistical methods throughout Chemistry, Manufacturing, and Controls (CMC). Filled with case studies, examples, and easy-to-follow explanations of how to perform statistics in modern software, it is the first book on CMC statistics written primarily for practitioners. While statisticians will also benefit from this book, it is written particularly for industry professionals who don’t have access to a CMC statistician or who want to be more independent in the design and analysis of their experiments. Provides an introduction to the statistical concepts important in the biotechnology industry Focuses on concepts with theoretical details kept to a minimum Includes lots of real examples and case studies to illustrate the methods Uses JMP software for implementation of the methods Offers a text suitable for scientists in the industry with some quantitative training Written and edited by seasoned veterans of the biotechnology industry, this book will prove useful to a wide variety of biotechnology professionals. The book brings together individual chapters that showcase the use of statistics in the most salient areas of CMC.
Author: Harry Yang
Publisher: CRC Press
ISBN: 1351585940
Category : Mathematics
Languages : en
Pages : 310
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Book Description
Drug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development. Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems. Features Provides a single source of information on Bayesian statistics for drug development Covers a wide spectrum of pre-clinical, clinical, and CMC topics Demonstrates proper Bayesian applications using real-life examples Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.
Author: Lanju Zhang
Publisher: Springer
ISBN: 3319235583
Category : Medical
Languages : en
Pages : 705
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Book Description
This book serves as a reference text for regulatory, industry and academic statisticians and also a handy manual for entry level Statisticians. Additionally it aims to stimulate academic interest in the field of Nonclinical Statistics and promote this as an important discipline in its own right. This text brings together for the first time in a single volume a comprehensive survey of methods important to the nonclinical science areas within the pharmaceutical and biotechnology industries. Specifically the Discovery and Translational sciences, the Safety/Toxiology sciences, and the Chemistry, Manufacturing and Controls sciences. Drug discovery and development is a long and costly process. Most decisions in the drug development process are made with incomplete information. The data is rife with uncertainties and hence risky by nature. This is therefore the purview of Statistics. As such, this book aims to introduce readers to important statistical thinking and its application in these nonclinical areas. The chapters provide as appropriate, a scientific background to the topic, relevant regulatory guidance, current statistical practice, and further research directions.
Author: Harry Yang
Publisher: CRC Press
ISBN: 100065267X
Category : Business & Economics
Languages : en
Pages : 335
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Book Description
The confluence of big data, artificial intelligence (AI), and machine learning (ML) has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R & D, emerging applications of big data, AI and ML in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations. Features Provides a comprehensive review of challenges and opportunities as related to the applications of big data, AI, and ML in the entire spectrum of drug R & D Discusses regulatory developments in leveraging big data and advanced analytics in drug review and approval Offers a balanced approach to data science organization build Presents real-world examples of AI-powered solutions to a host of issues in the lifecycle of drug development Affords sufficient context for each problem and provides a detailed description of solutions suitable for practitioners with limited data science expertise
Author: Paul Faya
Publisher: CRC Press
ISBN: 1000824772
Category : Mathematics
Languages : en
Pages : 354
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Book Description
The subject of this book is applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies in the biopharmaceutical industry. The book has multiple authors from industry and academia, each contributing a case study (chapter). The collection of case studies covers a broad array of CMC topics, including stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and comparability studies. The analysis of each case study includes a presentation of code and reproducible output. This book is written with an academic level aimed at practicing nonclinical biostatisticians, most of whom have graduate degrees in statistics. • First book of its kind focusing strictly on CMC Bayesian case studies • Case studies with code and output • Representation from several companies across the industry as well as academia • Authors are leading and well-known Bayesian statisticians in the CMC field • Accompanying website with code for reproducibility • Reflective of real-life industry applications/problems
Author: Emmanuel Lesaffre
Publisher: CRC Press
ISBN: 1351718665
Category : Medical
Languages : en
Pages : 583
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Book Description
Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.
Author: Christopher M. Riley
Publisher: Elsevier
ISBN: 0081028253
Category : Science
Languages : en
Pages : 696
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Book Description
Specification of Drug Substances and Products: Development and Validation of Analytical Methods, Second Edition, presents a comprehensive and critical analysis of the requirements and approaches to setting specifications for new pharmaceutical products, with an emphasis on phase-appropriate development, validation of analytical methods, and their application in practice. This thoroughly revised second edition covers topics not covered or not substantially covered in the first edition, including method development and validation in the clinical phase, method transfer, process analytical technology, analytical life cycle management, special challenges with generic drugs, genotoxic impurities, topical products, nasal sprays and inhalation products, and biotechnology products. The book's authors have been carefully selected as former members of the ICH Expert Working Groups charged with developing the ICH guidelines, and/or subject-matter experts in the industry, academia and in government laboratories. - Presents a critical assessment of the application of ICH guidelines on method validation and specification setting - Written by subject-matter experts involved in the development and application of the guidelines - Provides a comprehensive treatment of the analytical methodologies used in the analysis, control and specification of new drug substances and products - Covers the latest statistical approaches (including analytical quality by design) in the development of specifications, method validation and shelf-life prediction
Author: Gerhard Schleining
Publisher: Springer Nature
ISBN: 3031515684
Category :
Languages : en
Pages : 478
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Book Description
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309316553
Category : Science
Languages : en
Pages : 158
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Book Description
The tremendous progress in biology over the last half century - from Watson and Crick's elucidation of the structure of DNA to today's astonishing, rapid progress in the field of synthetic biology - has positioned us for significant innovation in chemical production. New bio-based chemicals, improved public health through improved drugs and diagnostics, and biofuels that reduce our dependency on oil are all results of research and innovation in the biological sciences. In the past decade, we have witnessed major advances made possible by biotechnology in areas such as rapid, low-cost DNA sequencing, metabolic engineering, and high-throughput screening. The manufacturing of chemicals using biological synthesis and engineering could expand even faster. A proactive strategy - implemented through the development of a technical roadmap similar to those that enabled sustained growth in the semiconductor industry and our explorations of space - is needed if we are to realize the widespread benefits of accelerating the industrialization of biology. Industrialization of Biology presents such a roadmap to achieve key technical milestones for chemical manufacturing through biological routes. This report examines the technical, economic, and societal factors that limit the adoption of bioprocessing in the chemical industry today and which, if surmounted, would markedly accelerate the advanced manufacturing of chemicals via industrial biotechnology. Working at the interface of synthetic chemistry, metabolic engineering, molecular biology, and synthetic biology, Industrialization of Biology identifies key technical goals for next-generation chemical manufacturing, then identifies the gaps in knowledge, tools, techniques, and systems required to meet those goals, and targets and timelines for achieving them. This report also considers the skills necessary to accomplish the roadmap goals, and what training opportunities are required to produce the cadre of skilled scientists and engineers needed.
