Nonclinical Statistics for Pharmaceutical and Biotechnology Industries. 1st ed. 2016

種類:

電子ブック

責任表示:

edited by Lanju Zhang

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2016

著者名:

• Zhang, Lanju.
• SpringerLink (Online service)

シリーズ名:

Statistics for Biology and Health ;

ISBN:

9783319235585 [3319235583]    

注記:

Introduction to Nonclinical Statistics for Pharmaceutical and Biotechnology Industries -- Regulatory Nonclinical Statistics -- How to be a good nonclinical statistician -- Statistical Methods for Drug Discovery -- High-throughput Screening Data Analysis -- Quantitative-Structure Activity Relationship Modeling and  Cheminformatics -- GWAS for Drug Discovery -- Statistical applications in Design and Analysis of In-Vitro Safety Screening Assays -- Nonclinical safety assessment: an introduction for statisticians -- General Toxicology, Safety Pharmacology, Reproductive Toxicology and Juvenile Toxicology Studies -- Clinical Assays for Biological Macromolecules -- Recent Research Projects by FDA's Pharmacology and Toxicology Statistics Team -- Design and evaluation of drug combination studies -- Biomarkers -- Overview of Drug Development and Statistical Tools for Manufacturing and Testing -- Assay Validation -- Lifecycle Approach to Bioassay -- Quality by Design: Building Quality into Products and Processes -- Proce
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 cha

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