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Author: S. W. Bergman
Publisher: CRC Press
ISBN: 1000148734
Category : Mathematics
Languages : en
Pages : 273
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Book Description
This book focuses on statistical methods which impinge more or less directly on the decisions that are made during the course of pharmaceutical and agro-chemical research, considering the four decision-making areas.
Author: S. W. Bergman
Publisher: CRC Press
ISBN: 1000148734
Category : Mathematics
Languages : en
Pages : 273
Get Book
Book Description
This book focuses on statistical methods which impinge more or less directly on the decisions that are made during the course of pharmaceutical and agro-chemical research, considering the four decision-making areas.
Author: S. W. Bergman
Publisher: CRC Press
ISBN: 1000105520
Category : Mathematics
Languages : en
Pages : 270
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Book Description
This book focuses on statistical methods which impinge more or less directly on the decisions that are made during the course of pharmaceutical and agro-chemical research, considering the four decision-making areas.
Author: Steven P. Millard
Publisher: Springer Science & Business Media
ISBN: 1475734662
Category : Medical
Languages : en
Pages : 518
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Book Description
Providing a general guide to statistical methods used in the pharmaceutical industry, and illustrating how to use S-PLUS to implement these methods, the book explains why S-PLUS is a useful software package and discusses the results and implications of each particular application. It is targeted at graduates in biostatistics, statisticians involved in the industry as research scientists, regulators, academics, and/or consultants who want to know more about how to use S-PLUS and learn about other sub-fields within the industry, as well as statisticians in other fields who want to know more about statistical applications in the pharmaceutical industry.
Author: William M. Wooding
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 568
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Book Description
Imparts a working understanding of the statistical principles and procedures essential to conducting successful clinical studies. Features a detailed catalog of experimental designs most commonly used in clinical work. Includes two chapters on elementary applied statistics and one on sample size estimation (the number of patients required).
Author: D. A. Berry
Publisher: CRC Press
ISBN: 1482276860
Category : Mathematics
Languages : en
Pages : 592
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Book Description
A state-of-the-art handbook of statistical analysis for use in the pharmaceutical industry. Areas covered in this reference/text include: bioavailability, repeated-measures designs, dose-response, population models, multicenter trials, handling dropouts, survival analysis, robust data analysis, cate
Author: Todd A. Durham
Publisher:
ISBN: 9780853697145
Category : Mathematics
Languages : en
Pages : 226
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Book Description
All students of pharmaceutical sciences and clinical research need a solid knowledge and understanding of the nature, methods, application, and importance of statistics. Introduction to Statistics in Pharmaceutical Clinical Trials is an ideal introduction to statistics presented in the context of clinical trials conducted during pharmaceutical drug development. This novel approach both teaches the computational steps needed to conduct analyses and provides a conceptual understanding of how these analyses provide information that forms the rational basis for decision making throughout the drug development process.
Author: Shein-Chung Chow
Publisher: CRC Press
ISBN: 1482273136
Category : Mathematics
Languages : en
Pages : 581
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Book Description
"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."
Author: Emmanuel Lesaffre
Publisher: CRC Press
ISBN: 1351718673
Category : Medical
Languages : en
Pages : 516
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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: Institute of Medicine
Publisher: National Academies Press
ISBN: 9780309171144
Category : Medical
Languages : en
Pages : 222
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Book Description
Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
Author: Mark Chang
Publisher: CRC Press
ISBN: 1351214535
Category : Mathematics
Languages : en
Pages : 362
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Book Description
"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.
