A Process Analytical Technology approach to near-infrared process control of pharmaceutical powder blending. Part III: Quantitative near-infrared calibration for prediction of blend homogeneity and characterization of powder mixing kinetics

The Process Analytical Technology (PAT) initiative, undertaken by the Food and Drug Administration (FDA), paves the way for improvement of drug manufacturing through real-time measurements that allow better process understanding. This study is the third and final Part in a series of studies that rep...

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Bibliographic Details
Published in:Journal of pharmaceutical sciences 2006-02, Vol.95 (2), p.422-434
Main Authors: El-Hagrasy, Arwa S., Drennen, James K.
Format: Article
Language:English
Subjects:
Biological and medical sciences
blend uniformity analysis
Calibration
Chemistry, Pharmaceutical - methods
General pharmacology
intra-shell and inter-shell mixing
Kinetics
Lactose - chemistry
Least-Squares Analysis
Linear Models
Medical sciences
Methanol - chemistry
mixing
multi-term linear regression (MLR)
Multivariate Analysis
near-infrared spectroscopy
partial least squares
Pharmaceutical technology. Pharmaceutical industry
Pharmacology. Drug treatments
Powders - chemistry
principal component analysis
principal component regression
Process Analytical Technology (PAT)
Salicylic Acid - chemistry
Spectroscopy, Near-Infrared - methods
Technology, Pharmaceutical
UV/VIS spectroscopy
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Summary:The Process Analytical Technology (PAT) initiative, undertaken by the Food and Drug Administration (FDA), paves the way for improvement of drug manufacturing through real-time measurements that allow better process understanding. This study is the third and final Part in a series of studies that represent an integrated approach for real-time blend uniformity assessment using near-infrared (NIR) technology. In this study, the development of a quantitative NIR model for prediction of blending end point is presented. Process signature was built into NIR calibration models by using blend samples that were collected from actual blend experiments under different processing conditions. Evaluation of various calibration algorithms including principal component regression (PCR), partial least squares (PLS), and multi-term linear regression (MLR) was performed. It was found that linear regression, using a single wavelength, yielded optimum calibration and prediction results. The blending profiles predicted by the NIR quantitative model correlated well to those determined by the UV reference analytical method. Characterization of intra-shell versus inter-shell powder mixing kinetics and its implication in sensor positioning was also performed and will be discussed. © 2005 Wiley-Liss, Inc. and the American Pharmacists Association
ISSN:0022-3549
1520-6017
DOI:10.1002/jps.20465