Process analysis in the pharmaceutical industry

Process analysis is defined simply as a measurement taken, and a result generated in time for the data to be used to impact on the process. This means process analysis is not exclusive to techniques that require that a sample is taken. In 1987, Callis [1] defined five categories of process analysis, defined as off-line, at-line, on-line, in-line and non-invasive, as is shown in Fig. 9.1. The simplest and the most widespread example of process analysis is when samples are taken from the process stream and analysed off-line in a remote laboratory. This process is slow, samples are taken with low frequency, and there are often substantial delays between sample submission and analysis. However, the off-line method does allow for analysis by expert analysts using many of the techniques described in previous chapters of this volume. 

The drawbacks to these types of process analysis mean that they are of limited use as in-process control tools. The first improvement is simply the movement of the testing from the laboratory to the manufacturing area. This is 

The remaining three categories form the basis of what is now commonly described as process analysis. In each case, no sample is taken, and analysis is carried out without any manual intervention. The subtle differences between Qn-hne, in-line and non-invasive are in reality academic - they are often thought of simply as on-line analysis. For the purposes of this chapter, any analysis carried out without the need to withdraw a sample is defined as online analysis. 

Even if these factors are taken into account in the validated process, occasionally pharmaceutical manufacturing processes result in a product that is regarded as an exception. Investigation or re-working of these exceptions has the biggest impact on productivity in the pharmaceutical industry. 

Process analysis can be used to provide extra insight into the nature of the processes and products, and as such should be part of a process control philosophy that will reduce variation. They even have the ability to produce a paradigm shift in the principles of pharmaceutical manufacturing, with validated measurements taken at Critical Control Points (CCP), controlling processes in such a way that product quality becomes guaranteed by measurement, and processes which are adjusted to optimise throughput. 

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One indication of the developing interest in PATs in the pharmaceutical area is the number of book chapters and review articles in this field that have appeared in the last few years. Several chapters in The Handbook of Vibrational Spectroscopy3 are related to the use of various optical spectroscopies in pharmaceutical development and manufacturing. Warman and Hammond also cover spectroscopic techniques extensively in their chapter titled Process Analysis in the Pharmaceutical Industry in the text Pharmaceutical Analysis.4 Pharmaceutical applications are included in an exhaustive review of near-infrared (NIR) and mid-infrared (mid-IR) by Workman,5 as well as the periodic applications reviews of Process Analytical Chemistry and Pharmaceutical Science in the journal Analytical Chemistry. The Encyclopedia of Pharmaceutical Technology has several chapters on spectroscopic methods of analysis, with the chapters on Diffuse Reflectance and Near-Infrared Spectrometry particularly highlighting on-line applications. There are an ever-expanding number of recent reviews on pharmaceutical applications, and a few examples are cited for Raman,7 8 NIR,9-11 and mid-IR.12... 

Finally, we could not ignore another area in which the regulatory authorities have had a major impact on pharmaceutical analysis in the pharmaceutical industry. Our concluding chapter deals with process validation as it applies to pharmaceutical analysis. 

Method development remains the most challenging aspect of chiral chromatographic analysis, and the need for rapid method development is particularly acute in the pharmaceutical industry. To complicate matters, even structurally similar compounds may not be resolved under the same chromatographic conditions, or even on the same CSP. Rapid column equilibration in SFC speeds the column screening process, and automated systems accommodating multiple CSPs and modifiers now permit unattended method optimization in SFC [36]. Because more compounds are likely to be resolved with a single set of parameters in SFC than in LC, the analyst stands a greater chance of success on the first try in SFC [37]. The increased resolution obtained in SFC may also reduce the number of columns that must be evaluated to achieve the desired separation. 

In the last few years, optimization techniques have become more widely used in the pharmaceutical industry. Some of these have appeared in the literature, but a far greater number remain as in-house information, using the same techniques indicated in this chapter, but with modifications and computer programs specific to the particular company. An excellent review of the application of optimization techniques in the pharmaceutical sciences was published in 1981 [20]. This covers not only formulation and processing, but also analysis, clinical chemistry, and medicinal chemistry. 

Q High-Throughput Analysis in Support of Process Chemistry and Formulation Research and Development in the Pharmaceutical Industry... 

This wider definition can be summarized as the analysis of the process and had been developing in the pharmaceutical industry since around 2004-2006 to encourage better use of the information content of classical process analytical methods for the improvement of process development and connol. Particularly in the pharmaceutical industry, the acronym PAT for Process Analytical Technology was often being used to describe this newer definition of process analytics. 

Houcine I, Plasari E, David R, Villermaux J. Feedstream jet intermittency phenomenon in a continuous stirred tank reactor. Chem Eng J 1999 72 19-29. Zlokarnik M. Dimensional analysis and scale-up in theory and industrial application. In Levin M, ed. Process Scale-Up in the Pharmaceutical Industry. New York Marcel Dekker, 2001. 

Keeping pace with the increased influence of PAT in the pharmaceutical industry, this completely updated reference spans the latest research and regulations, technologies, and expert solutions for every significant aspect of pharmaceutical process scale-up—clearly introducing readers to the theoretical concept of dimensional analysis to quantify similar processes on varying scales. 

Many of the quality improvement goals for implementation of PAT in the pharmaceutical industry have been achieved by companies in other industries, such as automobile production and consumer electronics, as a direct result of adopting principles of quality management. The lineage of modern quality management can be traced to the work of Walter Shewhart, a statistician for Bell Laboratories in the mid-1920s [17]. His observation that statistical analysis of the dimensions of industrial products over time could be used to control the quality of production laid the foundation for modern control charts. Shewhart is considered to be the father of statistical process control (SPC) his work provides the first evidence of the transition from product quality (by inspection) to the concept of quality processes [18,19]. 

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