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Potential of Near-Infrared Chemical Imaging as Process Analytical Technology Tool for Continuous Freeze-Drying

Brouckaert, Davinia, De Meyer, Laurens, Vanbillemont, Brecht, Van Bockstal, Pieter-Jan, Lammens, Joris, Mortier, Séverine, Corver, Jos, Vervaet, Chris, Nopens, Ingmar, De Beer, Thomas
Analytical chemistry 2018 v.90 no.7 pp. 4354-4362
cakes, freeze drying, freezing, image analysis, least squares, mannitol, near-infrared spectroscopy, principal component analysis, process monitoring, spatial data, sucrose, water content
Near-infrared chemical imaging (NIR-CI) is an emerging tool for process monitoring because it combines the chemical selectivity of vibrational spectroscopy with spatial information. Whereas traditional near-infrared spectroscopy is an attractive technique for water content determination and solid-state investigation of lyophilized products, chemical imaging opens up possibilities for assessing the homogeneity of these critical quality attributes (CQAs) throughout the entire product. In this contribution, we aim to evaluate NIR-CI as a process analytical technology (PAT) tool for at-line inspection of continuously freeze-dried pharmaceutical unit doses based on spin freezing. The chemical images of freeze-dried mannitol samples were resolved via multivariate curve resolution, allowing us to visualize the distribution of mannitol solid forms throughout the entire cake. Second, a mannitol-sucrose formulation was lyophilized with variable drying times for inducing changes in water content. Analyzing the corresponding chemical images via principal component analysis, vial-to-vial variations as well as within-vial inhomogeneity in water content could be detected. Furthermore, a partial least-squares regression model was constructed for quantifying the water content in each pixel of the chemical images. It was hence concluded that NIR-CI is inherently a most promising PAT tool for continuously monitoring freeze-dried samples. Although some practicalities are still to be solved, this analytical technique could be applied in-line for CQA evaluation and for detecting the drying end point.