Process analytical technology sampling

CE instrumentation is quite simple (see Chapter 3). A core instrument utilizes a high-voltage power supply (capable of voltages in excess of 30,000 V), capillaries (approximately 25—lOOpm I.D.), buffers to complete the circuit (e.g., citrate, phosphate, or acetate), and a detector (e.g., UV-visible). CE provides simplicity of method development, reliability, speed, and versatility. It is a valuable technique because it can separate compounds that have traditionally been difficult to handle by HPLC. Furthermore, it can be automated for quantitative analysis. CE can play an important role in process analytical technology (PAT). For example, an on-line CE system can completely automate the sampling, sample preparation, and analysis of proteins or other species that can be separated by CE. 

Process Sampling Theory of Sampling the Missing Link in Process Analytical Technologies (PAT)... 

Process Analytical Technology 3.2.10 Total sampling error... 

Raman spectroscopy was discovered over 75 years ago but has only been a viable process tool for 10-15 years. However, there has been an astounding increase in process Raman spectroscopy examples in the last five years. The United States Food and Drag Administration s (US FDA) endorsement of process analytical technology clearly set off an explosion of activity. Problems that sometimes sidelined Raman in the past, such as fluorescence or highly variable quantitative predictions from samples that were too small to be representative, are being re-examined and leading to new technology. In turn, that helps open, or perhaps reopen, new application areas. The availabihty of easy to use Raman instrumentation at many prices also helps with that. 

Chemometrics in Process Analytical Technology (PAT) 393 Table 12.8 Summary of the polyurethane rigid foam samples used to illustrate various classification methods... 

In-process controls such as stratined sampling, process analytical technology (PAT) application, and blend homogeneity. Assess modincation of dissolution through optimization of API characteristics and then perform assessment of specialized technologies [hot-melt extrusion (HME), spray-dried dispersion, solid dispersion, etc.] for long-term resolution... 

Aside from univariate linear regression models, inverse MLR models are probably the simplest types of models to construct for a process analytical application. Simplicity is of very high value in PAC, where ease of automation and long-term reliability are critical. Another advantage of MLR models is that they are rather easy to communicate to the customers of the process analytical technology, since each individual X-variable used in the equation refers to a single wavelength (in the case of NIR) that can often be related to a specific chemical or physical property of the process sample. 

Presenting nearly 50% new and revised material, this thoroughly updated edition incorporates the latest advances in instrumentation, computerization, calibration, and method development in NIR spectroscopy. The book underscores current trends in sample preparation, calibration transfer, process control, data analysis, and commercial NIR instrumentation. New chapters highlight novel applications including the analysis of agro-forestry products, polymers, blood, and control serum. They also cover NIR spectra, process analytical technologies (PAT), quantitative and qualitative analyses for nutraceuticals, NIR photography uses in medicine, and counterfeit detection methods for various applications. 

The development of fiber optics technology, user-friendly displays, and enhanced data presentation capabihties have made on-line analysis acceptable within the plant manufactuting environment. However, it is apparent that a barrier stiU exists to some extent within many organizations between the process control engineers, the plant operations department, and the analytical function, and proper sampling is stiU the key to successful process analytical chemistry. The ultimate goal is not to handle the sample at ah. 

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