Multivariate analysis in the pharmaceutical industry
Front Cover -- Multivariate Analysis in the Pharmaceutical Industry -- Copyright Page -- Dedication -- Contents -- List of Contributors -- About the Editors -- Foreword -- I. Background and Methodology -- 1 The Preeminence of Multivariate Data Analysis as a Statistical Data Analysis Technique in Pharmaceutical R& -- D and Manufact... -- 1.1 Data Size Glossary (Table 1.1) -- 1.2 Big Data-Overall View -- 1.3 Big Data-Pharmaceutical Context -- 1.4 Statistical Data Analysis Methods in the Pharmaceutical Industry -- 1.5 Development of Multivariate Data Analysis as a Data Analysis Technique within the Pharmaceutical Industry -- 1.6 Current Status of the Use of Multivariate Data Analysis in the Pharmaceutical Space -- 1.7 What MVA Can be Used For/What it Cannot be Used For -- 1.8 Current Limitations and Future Developments -- Acknowledgments -- References -- 2 The Philosophy and Fundamentals of Handling, Modeling, and Interpreting Large Data Sets-the Multivariate Chemometrics App... -- 2.1 Introduction -- 2.1.1 The Nature of this Chapter -- 2.1.2 The History of Metrics -- 2.2 Univariate Data and How it is Handled -- 2.2.1 Data Vectors and Some Definitions -- 2.2.2 Some Statistics on Vectors -- 2.2.3 Some General Thoughts about Univariate Thinking -- 2.3 Multivariate Data With Definitions -- 2.3.1 Data Matrices, Two-Way Arrays -- 2.3.2 Three- and More-Way Arrays -- 2.3.3 Multiblock Data -- 2.3.4 General Thoughts About Multivariate Thinking -- 2.4 Modeling -- 2.4.1 General Factor Models -- 2.4.2 Principal Component Analysis -- 2.4.3 Multivariate Curve Resolution -- 2.4.4 Clustering-Classification -- 2.4.5 Regression Models -- 2.4.6 Model Diagnostics -- 2.4.7 Some General Thoughts About Modeling -- 2.5 Conclusions -- References -- 3 Data Processing in Multivariate Analysis of Pharmaceutical Processes -- 3.1 Introduction.