Amb motiu del tancament d'estiu, la validació de documents es reprendrà a partir del 28 d'agost de 2026. Disculpeu les molèsties.
Con motivo del cierre de verano, la validación de documentos se reanudará a partir del 28 de agosto de 2026. Disculpad las molestias
Due to the summer closure, document validation will resume starting August 28, 2026. We apologize for any inconvenience.

Document type

Article

Version

Published version

Publication date

Publication license

cc by (c) Avila et al., 2020
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/170959

Process monitoring of moisture content and mass transfer rate in a fluidised bed with a low cost inline MEMS NIR sensor

Journal Title

Director/Tutor

Journal ISSN

Volume Title

Abstract

Purpose The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry-Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control. Methods Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules. A PLS moisture model was constructed resulting in a high resolution moisture signal, used to demonstrate (i) endpoint determination and (ii) evaluation of mass transfer performance. Results The sensors appear robust with respect to vibration and ambient temperature changes, and the accuracy of water content predictions (±13%) is similar to those reported for high specification NIR sensors. Fusion of temperature and moisture content signal allowed monitoring of water transport rates in the fluidised bed and highlighted the importance water transport within the solid phase at low moisture levels. The NIR data was also successfully used with PCA-based MSPC models for endpoint detection. Conclusions The spectral quality of the small form factor NIR sensor and its robustness is clearly sufficient for the construction and application of PLS models as well as PCA-based MSPC moisture models. The resulting high resolution moisture content signal was successfully used for endpoint detection and monitoring the mass transfer rate.

Subject (English)

Citation

Citation

AVILA, Claudio R., et al. Process monitoring of moisture content and mass transfer rate in a fluidised bed with a low cost inline MEMS NIR sensor. Pharmaceutical Research. 2020. Vol. 37. ISSN 0724-8741. [consulted: 11 of August of 2026]. Available at: https://hdl.handle.net/2445/170959

Export metadata

JSON - METS

Share record