Titlebook: Nonclinical Statistics for Pharmaceutical and Biotechnology Industries; Lanju Zhang Book 2016 Springer International Publishing Switzerlan

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Statistics for Biology and Healthhttp://image.papertrans.cn/n/image/667182.jpg

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https://doi.org/10.1007/978-3-319-23558-5Animal studies; Biomarker; Chemistry, manufacturing and controls (CMC); Drug research and development; N

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Lanju ZhangProvides the first volume dedicated to nonclinical statistics.Brings together relevant statistical methods for nonclinical research in pharma/biotech industries with a mission promoting nonclinical st

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How To Be a Good Nonclinical Statisticians the scope of this book, there are many accounts in the field of statistics of what it takes to be a good statistician. The goal of this chapter is to focus on specific characteristics for nonclinical statisticians which we believe are essential to be viewed as “good” professionals, either as individual contributors or managers.

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Statistical Methods for Drug Discoveryw key areas: target discovery, compound screening/optimization, and the characterization of important properties. Special attention is paid to working with assay data and phenotypic screens. A discussion of important skills for a nonclinical statistician supporting drug discovery concludes the chapter.

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1431-8776 a/biotech industries with a mission promoting nonclinical st.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

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Clinical Assays for Biological Macromoleculess unique challenges. In this chapter, we review the scientific background of clinical assay development and validation, as well as the common statistical methods used during the life-cycle of assay development.

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Design and Evaluation of Drug Combination Studiesy evaluation. A new index based on Bliss independence is introduced, comparable to the interaction index based on Loewe Additivity. An example data set is used to demonstrate the implementation of these analysis methods. In the final discussion, we point out some future research areas.

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Biomarkersilised. In this chapter we shall discuss what biomarkers are, the types of data that they generate and the impact on the subsequent statistical analysis, paying particular attention to the avoidance of false positives in biomarker discovery and confirming the technical performance of assays measuring biomarkers.

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Introduction to Nonclinical Statistics for Pharmaceutical and Biotechnology Industries nonclinical statistics in pharmaceutical and biotechnology companies. Then we try to define nonclinical statistics, discuss the nonclinical statistical profession, identify possible causes of predicaments in nonclinical statistics, and point out potential directions to change the status quo.