NIR Spectroscopy as an Online PAT Tool for a Narrow Therapeutic Index Drug: Toward a Platform Approach Across Lab and Pilot Scales for Development of a Powder Blending Monitoring Method and Endpoint Determination.

Autor: Talwar S; Duquesne University Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA, 15282, USA.; MST-BPDS-Biopharm Product Dev & Supply, GSK, 709 Swedeland Road, King of Prussia, PA, 19406, USA., Pawar P; Department of Chemical and Biochemical Engineering, Rutgers University, 98 Brett Road, Piscataway, NJ, 08854, USA.; Gilead, Foster City, CA, 94404, USA., Wu H; Office of Pharmaceutical Quality, CDER, FDA, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA. Huiquan.wu@fda.hhs.gov., Sowrirajan K; Office of Pharmaceutical Quality, CDER, FDA, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA., Wu S; Office of Pharmaceutical Quality, CDER, FDA, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA., Igne B; Duquesne University Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA, 15282, USA., Friedman R; Office of Manufacturing Quality, Office of Compliance, CDER, FDA, Silver Spring, MD, 20993, USA., Muzzio FJ; Department of Chemical and Biochemical Engineering, Rutgers University, 98 Brett Road, Piscataway, NJ, 08854, USA., Drennen JK 3rd; Duquesne University Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA, 15282, USA. Drennen@duq.edu.
Jazyk: angličtina
Zdroj: The AAPS journal [AAPS J] 2022 Sep 28; Vol. 24 (6), pp. 103. Date of Electronic Publication: 2022 Sep 28.
DOI: 10.1208/s12248-022-00748-4
Abstrakt: An online near-infrared (NIR) spectroscopy platform system for real-time powder blending monitoring and blend endpoint determination was tested for a phenytoin sodium formulation. The study utilized robust experimental design and multiple sensors to investigate multivariate data acquisition, model development, and model scale-up from lab to manufacturing. The impact of the selection of various blend endpoint algorithms on predicted blend endpoint (i.e., mixing time) was explored. Spectral data collected at two process scales using two NIR spectrometers was incorporated in a single (global) calibration model. Unique endpoints were obtained with different algorithms based on standard deviation, average, and distributions of concentration prediction for major components of the formulation. Control over phenytoin sodium's distribution was considered critical due to its narrow therapeutic index nature. It was found that algorithms sensitive to deviation from target concentration offered the simplest interpretation and consistent trends. In contrast, algorithms sensitive to global homogeneity of active and excipients yielded the longest mixing time to achieve blending endpoint. However, they were potentially more sensitive to subtle uniformity variations. Qualitative algorithms using principal component analysis (PCA) of spectral data yielded the prediction of shortest mixing time for blending endpoint. The hybrid approach of combining NIR data from different scales presents several advantages. It enables simplifying the chemometrics model building process and reduces the cost of model building compared to the approach of using data solely from commercial scale. Success of such a hybrid approach depends on the spectroscopic variability captured at different scales and their relative contributions in the final NIR model.
(© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
Databáze: MEDLINE
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