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space). Chemometrics is also a key enabler of new software applications for trending analysis for process monitoring and/or control. To reach the desired state of pharmaceutical manufacturing (mechanistically- and scientifi cally-driven development with multivariate experimental designs, science-driven operation and validation, continuous process verifi cation and in-, at- or on-line analyses), proper chemometrics and PAT tools need to be in place.
RC:
In order to implement and maintain a successful PAT program, the role of design of experiment can never be understated.
As a result, chemometric analysis is an invaluable tool in the process analytical chemist’s toolbox when used within a well-defi ned analytical method. By utilizing multivariate statistical techniques, chemometrics allow for the collection and analysis of vast amounts of chemical data and quickly process it to fi nd hidden trends in the data. Some common PAT applications for chemometric analysis are monitoring particle size and drying using NIR, polymorphic and other molecular transitions with Raman, and complex analyte concentration using UV/Vis.
One very interesting trend gaining momentum in PAT is the use of orthogonal testing techniques which can be fed into a single chemometric method. This increases the robustness of the process, such as combining broadband refl ectance with Raman spectroscopy to get a more complete picture of the chemical changes in the process. Additionally, groups such as Maddux et. al. from the University of Kansas
have conducted encouraging research in the exploration of methods of combining data acquired from techniques as diverse as calorimetry and intrinsic fl uorescence into a unifi ed multivariate model.
Describe ways in which NIR and Raman help to ensure regulatory compliance.
GR:
Ensuring regulatory compliance is such a huge job requirement for tools that are primarily intended to assess
quality, so what I will respond to is: “How do NIR and Raman help to ensure quality?”
The agency itself has struggled with trying to
defi ne what they mean by ‘quality’, so attempting to defi ne a role that these tools play in ensuring quality is a bit of a slippery slope as well. Surveillance seems to be on many minds right now. Assessing what quality metrics should be used and at what step they should be used in is a question that has been at the forefront. As previously mentioned, NIR and Raman can help to ensure quality by providing data rapidly, non-invasively, non-destructively, and allow users to bring the instrument to a larger number of samples and not rely on smaller sample sets. Since it is now possible to take many more measurements of samples, the idea of providing surveillance data on fi nished product, rather than providing prediction data, may have a greater impact on ensuring quality of the fi nished product in the future.
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