Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy

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Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy. / Maltesen, Morten Jonas; van de Weert, Marco; Grohganz, Holger.

In: A A P S PharmSciTech, Vol. 13, No. 3, 2012, p. 747-55.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Maltesen, MJ, van de Weert, M & Grohganz, H 2012, 'Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy', A A P S PharmSciTech, vol. 13, no. 3, pp. 747-55. https://doi.org/10.1208/s12249-012-9796-1

APA

Maltesen, M. J., van de Weert, M., & Grohganz, H. (2012). Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy. A A P S PharmSciTech, 13(3), 747-55. https://doi.org/10.1208/s12249-012-9796-1

Vancouver

Maltesen MJ, van de Weert M, Grohganz H. Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy. A A P S PharmSciTech. 2012;13(3):747-55. https://doi.org/10.1208/s12249-012-9796-1

Author

Maltesen, Morten Jonas ; van de Weert, Marco ; Grohganz, Holger. / Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy. In: A A P S PharmSciTech. 2012 ; Vol. 13, No. 3. pp. 747-55.

Bibtex

@article{20891e5c459e488f8b1af4d3051dcdc4,
title = "Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy",
abstract = "Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination with preprocessing and multivariate analysis in the form of partial least squares projections to latent structures (PLS) were used to correlate the spectral data with moisture content and aerodynamic particle size measured by a time of flight principle. PLS models predicting the moisture content were based on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39{\%} and 0.48{\%} with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded prediction errors between 0.27 and 0.48 µm. The morphology of the spray-dried particles had a significant impact on the predictive ability of the models. Good predictive models could be obtained for spherical particles with a calibration error (RMSECV) of 0.22 µm, whereas wrinkled particles resulted in much less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles.",
author = "Maltesen, {Morten Jonas} and {van de Weert}, Marco and Holger Grohganz",
year = "2012",
doi = "10.1208/s12249-012-9796-1",
language = "English",
volume = "13",
pages = "747--55",
journal = "A A P S PharmSciTech",
issn = "1530-9932",
publisher = "Springer",
number = "3",

}

RIS

TY - JOUR

T1 - Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy

AU - Maltesen, Morten Jonas

AU - van de Weert, Marco

AU - Grohganz, Holger

PY - 2012

Y1 - 2012

N2 - Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination with preprocessing and multivariate analysis in the form of partial least squares projections to latent structures (PLS) were used to correlate the spectral data with moisture content and aerodynamic particle size measured by a time of flight principle. PLS models predicting the moisture content were based on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39% and 0.48% with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded prediction errors between 0.27 and 0.48 µm. The morphology of the spray-dried particles had a significant impact on the predictive ability of the models. Good predictive models could be obtained for spherical particles with a calibration error (RMSECV) of 0.22 µm, whereas wrinkled particles resulted in much less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles.

AB - Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination with preprocessing and multivariate analysis in the form of partial least squares projections to latent structures (PLS) were used to correlate the spectral data with moisture content and aerodynamic particle size measured by a time of flight principle. PLS models predicting the moisture content were based on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39% and 0.48% with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded prediction errors between 0.27 and 0.48 µm. The morphology of the spray-dried particles had a significant impact on the predictive ability of the models. Good predictive models could be obtained for spherical particles with a calibration error (RMSECV) of 0.22 µm, whereas wrinkled particles resulted in much less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles.

U2 - 10.1208/s12249-012-9796-1

DO - 10.1208/s12249-012-9796-1

M3 - Journal article

C2 - 22585372

VL - 13

SP - 747

EP - 755

JO - A A P S PharmSciTech

JF - A A P S PharmSciTech

SN - 1530-9932

IS - 3

ER -

ID: 40438946