THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.

/pdf/multivariate-statistical-process-control-charts-an-overview-1vbmsl9ae7.pdf

Multivariate statistical process control charts: an overview

Multivariate Statistical Process Control Charts: An Overview

Multivariate data analysis in pharmaceutics: a tutorial review.

Background
Cell culture technology has spread prolifically within a century, a variety of culture media has been designed. This review goes through the history, characteristics and current issues of animal-cell culture media.

Methods
A literature search was performed on PubMed and Google Scholar between 1880 and May 2016 using appropriate keywords.

Results
At the dawn of cell culture technology, the major components of media were naturally derived products such as serum. The field then gradually shifted to the use of chemical-based synthetic media because naturally derived ingredients have their disadvantages such as large batch-to-batch variation. Today, industrially important cells can be cultured in synthetic media. Nevertheless, the combinations and concentrations of the components in these media remain to be optimized. In addition, serum-containing media are still in general use in the field of basic research. In the fields of assisted reproductive technologies and regenerative medicine, some of the medium components are naturally derived in nearly all instances.

Conclusions
Further improvements of culture media are desirable, which will certainly contribute to a reduction in the experimental variation, enhance productivity among biopharmaceuticals, improve treatment outcomes of assisted reproductive technologies, and facilitate implementation and popularization of regenerative medicine.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rmb2.12024

Animal-cell culture media: History, characteristics, and current issues

This review surveys recent applications of design-of-experiments (DoE) methodology in the development of biotechnological processes. Methods such as factorial design, response surface methodology, and (DoE) provide powerful and efficient ways to optimize cultivations and other unit operations and procedures using a reduced number of experiments. The multitude of interdependent parameters involved within a unit operation or between units in a bioprocess sequence may be substantially refined and improved by the use of such methods. Other bioprocess-related applications include strain screening evaluation and cultivation media balancing. In view of the emerging regulatory demands on pharmaceutical manufacturing processes, exemplified by the process analytical technology (PAT) initiative of the United States Food and Drug Administration, the use of experimental design approaches to improve process development for safer and more reproducible production is becoming increasingly important. Here, these options are highlighted and discussed with a few selected examples from antibiotic fermentation, expanded bed optimization, virus vector transfection of insect cell cultivation, feed profile adaptation, embryonic stem cell expansion protocols, and mammalian cell harvesting.

Bioprocess optimization using design-of-experiments methodology.

REVIEW: BIOCATALYSTS AND BIOREACTOR DESIGN Bioprocess Optimization Using Design-of-Experiments Methodology

On-line spectroscopic measurements of wood chips before a continuous digester

Today's methods for measuring odours from paperboard intended for packaging materials are often time consuming, so producers of packaging materials need to find a quick reliable method that can describe not only the volatile compounds, but also the odour from the packaging. Odour analysis and an 'electronic nose' have been used to measure the volatile compounds from paperboard. The results from the measurements have been statistically evaluated by partial least squares regression (PLS). The signals from some electronic sensors correlated well with a selected number of descriptors while some sensors have no descriptors that fit.

Anders Brundin

Papers

Bioprocess optimization using design-of-experiments methodology.

REVIEW: BIOCATALYSTS AND BIOREACTOR DESIGN Bioprocess Optimization Using Design-of-Experiments Methodology

On-line spectroscopic measurements of wood chips before a continuous digester

Odour analysis of paperboard, the correlation between human senses and electronic sensors using multivariate analysis

Monitoring a paperboard machine using multivariate statistical process control