And we continue reviewing pharmaceutical "essentials" books. With unbroken enthusiasm, I jumped at the book "Trending in the pharmaceutical industry" by Patric U.B. Vogel this time, published in 2020 by Springer Spektrum, Wiesbaden (ISBN: 978-3-658-32206-9) and spent a cozy evening in front of the chimney.
About the content
In usual slim manner (54 pages) and with proven concept (“pre-introduction” and exit with bullet points as well as a short introduction and concluding summary, as always well illustrated and with bold keywords), the topic of trending is presented in a comprehensible manner. The reader is slowly introduced to the topic and first learns about different types of data and different types of trends. After tabular and visual trending, the reader is then introduced to statistical methods such as quality control charts, regression/correlation analysis and trend tests. Throughout the book, an example presented at the beginning showing the progression of drug product batches with increasing drug substance content, including the occurrence of out of specification (OOS) results, is revisited again and again. In addition to the introduction, which introduces us to the pharmaceutical world and thus provides the context for what trend analyses can be good for, the practical use of trending becomes particularly clear in the chapter on out of trend (OOT) analyses in stability studies. Further applicability is given in statistical process control. A brief introduction to regulatory requirements is also not missing. When I review the entire book, the contents of the individual chapters with their backgrounds paint what I consider to be a good overall picture of trending and clarify the "why" and "how“.
First of all, I would like to emphasize that this book is, as always, written in a super-comprehensible way and especially the explanations with everyday examples such as train delays, different hair colors or body sizes make such a rather statistical topic tangible and understandable for everyone, but also the examples chosen from the pharmaceutical environment (such as pH value, refrigerator temperature, content determination) are simple and, in my opinion, well understandable for everybody.
Prior to the introduction to the statistical methods, the underlying mathematical basics are explained, really starting from zero. For example, the normal distribution is explained for the purpose of understanding the calculation / determination of warning and action limits of quality control charts as well as e.g., the straight-line equation for regression analysis, although a straight-line equation should be well known to most readers (still from school times), as well as the fact that squaring negative numbers leads to positive results... For my taste, this is a bit too much started at zero, but this might just be a matter of taste or depend on the individual level of knowledge. But this makes it suitable for absolute newcomers to statistics.
In terms of content, I particularly liked the fact that the presentation of the individual trend methods also briefly discusses advantages and disadvantages and critically examines the scenarios presented. Furthermore, hints abouts potential causes do not leave the reader out in the cold regarding the respective problem and show how to continue (keyword: root cause analysis). It is also great that difficult things going beyond the scope, such as trend analyses for non-normally distributed data, are not dealt with in detail; instead, a reference is given allowing the reader to inform himself if necessary. I like that a lot. I also like the inclusion of the reader to think about the data shown. Overall, the reader is taken along very well and doesn't need to be afraid that the topic is too dry. Furthermore, the author makes the reader curious for more, for example by outlining risk analyses (to determine the parameters to be considered) or by referring to statistical process control with certain key performance indicators.
In contrast to other reviews in which I have chalked up a slightly imprecise use of different terms, I’ve got to emphasize the good comparison of OOS versus OOT here.
However, this book, like the two previous ones, has unfortunately many spelling errors, although perhaps subjectively a little bit less... Furthermore, a lack of thoroughness on the part of the editor is also evident in this book, since, among other things, an abbreviation was used that was not introduced and its explanation occurs much later, a reference has an incorrect title, a missing citation is addressed, and a figure is incorrectly labeled (which might result in a slight irritation of inexperienced readers). In addition, a passage with the same wording as in the previous book "Quality control of vaccines" can be found in one chapter, what I personally find a bit negative...
Perhaps temperature recording and evaluation with data loggers after a certain period may no longer be completely up to date, but maybe this feeling is just due to different ways of handling of different companies, if continuous recording and transmission to a monitoring system is already taking place in real time elsewhere…
In terms of content, there are three small things that also caught my eye. First, the author talks about trend analyses becoming more and more important, but does not provide any evidence for this. Thus, we don’t know whether this is just his opinion or what’s the basis for this thesis. Second, it could have been mentioned how to test a data set for normal distribution (for example, with a reference to a Kolmogorov Smirnov test for small sample size) and third, the "mean square of successive differences" in Neumann's trend test has been used correctly in the text, but confusingly in the associated table. But these points are certainly complaining at a high level 😉.
And as final conclusion...
Trending, especially the application of control charts, has crossed my way from time to time - but only marginally - so that this book was for me a very good introduction to a topic that unfortunately had only been touched peripherally before. Apart from the minor points mentioned above, I generally liked this book very much and would recommend it to all those who want to look beyond their own area of expertise as well as to newcomers in the pharmaceutical industry.
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