ABSTRACT The adoption of spectroscopy as a process analytical technology (PAT) modality in the pharmaceutical industry and related sectors has enabled advanced monitoring and control of manufacturing processes. Most applications of spectroscopic PAT instruments are dependent on chemometric multivariate data analysis (MVDA) methods to extract the relevant process data from the spectral measurements. However, calibrating and maintaining conventional MVDA methods is often burdensome, as it requires extensive time, material, and financial costs to generate the necessary representative samples and corresponding reference data. This calibration burden can be a barrier to the adoption of spectroscopic PAT in the pharmaceutical industry. Within this article, a classification of MVDA methods referred to as “lean chemometrics” is proposed and formalized. Lean chemometrics are time‐saving, material‐sparing, and cost‐cutting MVDA methods that reduce the calibration burden relative to conventional chemometric methods of choice for spectroscopic PAT. Categories of various MVDA methods that are classifiable as lean chemometric techniques and practical considerations for integration of these techniques with PAT in common pharmaceutical PAT applications are discussed. The intention of lean chemometrics is to raise awareness of solutions that minimize the challenge of calibration burden toward improving spectroscopic PAT adoption.
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Adam J. Rish
Samuel R. Henson
Owen G. Rehrauer
Journal of Chemometrics
At Bristol
Sentient Science (United States)
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Rish et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69a75cdbc6e9836116a26113 — DOI: https://doi.org/10.1002/cem.70105