Authors
Carla Ferreira, Javier Cardona, Okpeafoh Agimelen, Christos Tachtatzis, Ivan Andonovic, Jan Sefcik, Yi-Chieh Chen
Published in
Analytical and bioanalytical chemistry. Jul 29, 2026. Epub Jul 29, 2026.
Abstract
Accurate in-line monitoring of particle size and solid concentration in turbid, multiphase systems remains a significant challenge in pharmaceutical manufacturing. Most particle measurement techniques are developed for off-line analysis, while recent in-line methods mainly rely on imaging and chord length distribution (CLD) measurement. Complementing these approaches, the spatially and angularly resolved diffuse reflectance measurement (SAR-DRM) system serves as a process analytical technology analyzer, capturing detailed, configuration-dependent spectral responses of particle suspensions. This study systematically evaluates SAR-DRM's effectiveness in analyzing a wide range of particle diameters (≤90-800 µm) and concentrations (1-10 wt%) for polystyrene suspensions. The visible-NIR and NIR measurements from its multiple spatial-angular fiber configurations are further analyzed to assess their potential in complementing other in-line techniques, improving interpretability and analytical performance. The results show that combining specific SAR-DRM configurations through data augmentation markedly enhances model performance compared to individual configurations or co-adding methods, reducing error by over 50% in some cases. Moreover, data fusion of SAR-DRM with CLD measurements yields the most accurate models, particularly for mid-sized particles, decreasing the prediction error to 10-12 µm. The study highlights SAR-DRM as a promising process analytical technology analyzer for particulate process monitoring, paving the way for advanced hybrid modelling in pharmaceutical and chemical manufacturing. It also underscores the complementary sensing capabilities of SAR-DRM and CLD measurements, providing a robust multisensory platform for real-time, quantitative analysis in complex, high-turbidity systems.
PMID:
42525265
Bibliographic data and abstract were imported from PubMed on 29 Jul 2026.
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