Emerging Non-Clinical Biostatistics in Biopharmaceutical Development and Manufacturing PDF Download
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Author: Harry Yang
Publisher: CRC Press
ISBN: 1315354454
Category : Mathematics
Languages : en
Pages : 278
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Book Description
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 comprehensive resource, it combines in-depth explanations of advanced statistical methods with real-life case studies that illustrate practical applications of these methods in QbD implementation.
Author: Harry Yang
Publisher: CRC Press
ISBN: 1315354454
Category : Mathematics
Languages : en
Pages : 278
Get Book Here
Book Description
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 comprehensive resource, it combines in-depth explanations of advanced statistical methods with real-life case studies that illustrate practical applications of these methods in QbD implementation.
Author: Harry Yang
Publisher: CRC Press
ISBN: 1498704166
Category : Mathematics
Languages : en
Pages : 387
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Book Description
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 comprehensive resource, it combines in-depth explanations of advanced statistical methods with real-life case studies that illustrate practical applications of these methods in QbD implementation.
Author: Kerry B. Barker
Publisher: CRC Press
ISBN: 1482231700
Category : Mathematics
Languages : en
Pages : 269
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Book Description
Biosimilars have the potential to change the way we think about, identify, and manage health problems. They are already impacting both clinical research and patient care, and this impact will only grow as our understanding and technologies improve. Written by a team of experienced specialists in clinical development, this book discusses various potential drug development strategies, the design and analysis of pharmacokinetics (PK) studies, and the design and analysis of efficacy studies.
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: 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: Abhaya Indrayan
Publisher: CRC Press
ISBN: 149879954X
Category : Mathematics
Languages : en
Pages : 1033
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Book Description
Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.
Author: Alex Dmitrienko
Publisher: CRC Press
ISBN: 1498735088
Category : Mathematics
Languages : en
Pages : 338
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Book Description
Clinical Trial Optimization Using R explores a unified and broadly applicable framework for optimizing decision making and strategy selection in clinical development, through a series of examples and case studies. It provides the clinical researcher with a powerful evaluation paradigm, as well as supportive R tools, to evaluate and select among simultaneous competing designs or analysis options. It is applicable broadly to statisticians and other quantitative clinical trialists, who have an interest in optimizing clinical trials, clinical trial programs, or associated analytics and decision making. This book presents in depth the Clinical Scenario Evaluation (CSE) framework, and discusses optimization strategies, including the quantitative assessment of tradeoffs. A variety of common development challenges are evaluated as case studies, and used to show how this framework both simplifies and optimizes strategy selection. Specific settings include optimizing adaptive designs, multiplicity and subgroup analysis strategies, and overall development decision-making criteria around Go/No-Go. After this book, the reader will be equipped to extend the CSE framework to their particular development challenges as well.
Author: Jay Herson
Publisher: CRC Press
ISBN: 1498784127
Category : Mathematics
Languages : en
Pages : 266
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Book Description
Praise for the first edition: "Given the author’s years of experience as a statistician and as a founder of the first DMC in pharmaceutical industry trials, I highly recommend this book—not only for experts because of its cogent and organized presentation, but more importantly for young investigators who are seeking information about the logistical and philosophical aspects of a DMC." -S. T. Ounpraseuth, The American Statistician In the first edition of this well-regarded book, the author provided a groundbreaking and definitive guide to best practices in pharmaceutical industry data monitoring committees (DMCs). Maintaining all the material from the first edition and adding substantial new material, Data and Safety Monitoring Committees in Clinical Trials, Second Edition is ideal for training professionals to serve on their first DMC as well as for experienced clinical and biostatistical DMC members, sponsor and regulatory agency staff. The second edition guides the reader through newly emerging DMC responsibilities brought about by regulations emphasizing risk vs benefit and the emergence of risk-based monitoring. It also provides the reader with many new statistical methods, clinical trial designs and clinical terminology that have emerged since the first edition. The references have been updated and the very popular end-of-chapter Q&A section has been supplemented with many new experiences since the first edition. New to the Second Edition: Presents statistical methods, tables, listings and graphs appropriate for safety review, efficacy analysis and risk vs benefit analysis, SPERT and PRISMA initiatives. Newly added interim analysis for efficacy and futility section. DMC responsibilities in SUSARs (Serious Unexpected Serious Adverse Reactions), basket trials, umbrella trials, dynamic treatment strategies /SMART trials, pragmatic trials, biosimilar trials, companion diagnostics, etc. DMC responsibilities for data quality and fraud detection (Fraud Recovery Plan) Use of patient reported outcomes of safety Use of meta analysis and data outside the trial New ideas for training and compensation of DMC members Jay Herson is Senior Associate, Biostatistics, Johns Hopkins Bloomberg School of Public Health where he teaches courses on clinical trials and drug development based on his many years experience in clinical trials in academia and the pharmaceutical industry.
Author: Ding-Geng (Din) Chen
Publisher: CRC Press
ISBN: 1498779530
Category : Mathematics
Languages : en
Pages : 411
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Book Description
Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."—Journal of Statistical Software Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book’s practical, detailed approach draws on the authors’ 30 years’ experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What’s New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.
Author: Demissie Alemayehu, PhD
Publisher: CRC Press
ISBN: 1498781888
Category : Mathematics
Languages : en
Pages : 210
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Book Description
With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.
