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Statistical applications for chemist...

Burdick, Richard K.

Statistical applications for chemistry, manufacturing and controls (CMC) in the pharmaceutical industry

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical applications for chemistry, manufacturing and controls (CMC) in the pharmaceutical industryby Richard K. Burdick ... [et al.].
other author:	Burdick, Richard K.
Published:	Cham :Springer International Publishing :2017.
Description:	xi, 379 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	PharmacologyStatistical methods.
Online resource:	http://dx.doi.org/10.1007/978-3-319-50186-4
ISBN:	9783319501864$q(electronic bk.)

Statistical applications for chemistry, manufacturing and controls (CMC) in the pharmaceutical industry
Statistical applications for chemistry, manufacturing and controls (CMC) in the pharmaceutical industry[electronic resource] /by Richard K. Burdick ... [et al.]. - Cham :Springer International Publishing :2017. - xi, 379 p. :ill., digital ;24 cm. - Statistics for biology and health,1431-8776. - Statistics for biology and health..

Chapter 1. Introduction -- Chapter 2. Statistical Methods for CMC Applications -- Chapter 3. Process Design: Stage 1 of the FDA Process Validation Guidance -- Chapter 4. Process Qualification: Stage 2 of the FDA Process Validation Guidance -- Chapter 5. GMP Monitoring and Continuous Process Verification: Stage 3 of the FDA Process Validation Guidance -- Chapter 6. Analytical Procedures -- Chapter 7. Specifications -- Chapter 8. Stability -- Chapter 9. Analytical Comparability and Similarity.

This book examines statistical techniques that are critically important to Chemistry, Manufacturing, and Control (CMC) activities. Statistical methods are presented with a focus on applications unique to the CMC in the pharmaceutical industry. The target audience consists of statisticians and other scientists who are responsible for performing statistical analyses within a CMC environment. Basic statistical concepts are addressed in Chapter 2 followed by applications to specific topics related to development and manufacturing. The mathematical level assumes an elementary understanding of statistical methods. The ability to use Excel or statistical packages such as Minitab, JMP, SAS, or R will provide more value to the reader. The motivation for this book came from an American Association of Pharmaceutical Scientists (AAPS) short course on statistical methods applied to CMC applications presented by four of the authors. One of the course participants asked us for a good reference book, and the only book recommended was written over 20 years ago by Chow and Liu (1995) We agreed that a more recent book would serve a need in our industry. Since we began this project, an edited book has been published on the same topic by Zhang (2016) The chapters in Zhang discuss statistical methods for CMC as well as drug discovery and nonclinical development. We believe our book complements Zhang by providing more detailed statistical analyses and examples.

ISBN: 9783319501864$q(electronic bk.)

Standard No.: 10.1007/978-3-319-50186-4doiSubjects--Topical Terms:

267176
Pharmacology
--Statistical methods.

LC Class. No.: RM287

Dewey Class. No.: 615.10727

Statistical applications for chemistry, manufacturing and controls (CMC) in the pharmaceutical industry
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520 $a This book examines statistical techniques that are critically important to Chemistry, Manufacturing, and Control (CMC) activities. Statistical methods are presented with a focus on applications unique to the CMC in the pharmaceutical industry. The target audience consists of statisticians and other scientists who are responsible for performing statistical analyses within a CMC environment. Basic statistical concepts are addressed in Chapter 2 followed by applications to specific topics related to development and manufacturing. The mathematical level assumes an elementary understanding of statistical methods. The ability to use Excel or statistical packages such as Minitab, JMP, SAS, or R will provide more value to the reader. The motivation for this book came from an American Association of Pharmaceutical Scientists (AAPS) short course on statistical methods applied to CMC applications presented by four of the authors. One of the course participants asked us for a good reference book, and the only book recommended was written over 20 years ago by Chow and Liu (1995) We agreed that a more recent book would serve a need in our industry. Since we began this project, an edited book has been published on the same topic by Zhang (2016) The chapters in Zhang discuss statistical methods for CMC as well as drug discovery and nonclinical development. We believe our book complements Zhang by providing more detailed statistical analyses and examples.
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