Noninvasive Determination of Protein Conformation in the Solid State Using Near Infrared (NIR) Spectroscopy

Bai, Shujun; Nayar, Rajiv; Carpenter, John F.; Manning, Mark C.

doi:10.1002/jps.20416

Cited by 49 publications

(38 citation statements)

References 27 publications

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“…The spectrum is dominated by combination bands in the region 5,200-4,000 cm −1 , similar to bands found for other proteins (37). Most of these bands have been tentatively assigned to combinations of amide I, amide II, amide III, amide A, amide B and C-H stretching bands (38,39). The band at 5,150 cm −1 originates from the combination band of water and can be used for the quantification of water in the dried samples (40,41).…”

Section: Near Infrared Spectroscopysupporting

confidence: 67%

“…Furthermore, it can be conducted online, which is important for the PAT initiative. While the structural information obtained is not as good as with FTIR spectroscopy, studies have correlated changes in the NIR spectra with changes in the amide I band in the FTIR region (38). In addition, NIR spectroscopy can yield information about particle size and water content of the powder (41,42).…”

Section: Comparison Of Methodsmentioning

confidence: 99%

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Multivariate Analysis of Phenol in Freeze-Dried and Spray-Dried Insulin Formulations by NIR and FTIR

et al. 2011

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Dehydration is a commonly used method to stabilise protein formulations. Upon dehydration, there is a significant risk the composition of the formulation will change especially if the protein formulation contains volatile compounds. Phenol is often used as excipient in insulin formulations, stabilising the insulin hexamer by changing the secondary structure. We have previously shown that it is possible to maintain this structural change after drying. The aim of this study was to evaluate the residual phenol content in spray-dried and freeze-dried insulin formulations by Fourier transform infrared (FTIR) spectroscopy and near infrared (NIR) spectroscopy using multivariate data analysis. A principal component analysis (PCA) and partial least squares (PLS) projections were used to analyse spectral data. After drying, there was a difference between the two drying methods in the phenol/insulin ratio and the water content of the dried samples. The spray-dried samples contained more water and less phenol compared with the freeze-dried samples. For the FTIR spectra, the best model used one PLS component to describe the phenol/insulin ratio in the powders, and was based on the second derivative pre-treated spectra in the 850-650 cm −1 region. The best PLS model based on the NIR spectra utilised three PLS components to describe the phenol/insulin ratio and was based on the standard normal variate transformed spectra in the 6,200-5,800 cm −1 region. The root mean square error of cross validation was 0.69% and 0.60% (w/w) for the models based on the FTIR and NIR spectra, respectively. In general, both methods were suitable for phenol quantification in dried phenol/insulin samples.

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Section: Near Infrared Spectroscopysupporting

confidence: 67%

Section: Comparison Of Methodsmentioning

confidence: 99%

Multivariate Analysis of Phenol in Freeze-Dried and Spray-Dried Insulin Formulations by NIR and FTIR

et al. 2011

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show abstract

“…The spectrum is dominated by combination bands in the 5,200-4,000 cm −1 region, similar to bands found for other proteins. Most of these bands have been tentatively assigned to combinations of amide I, amide II, amide III, amide A, amide B and C-H stretching bands (43,44). For the spray-dried insulin powders, two bands are observed around 6,900 and 5,150 cm −1 in the NIR spectra.…”

Section: Resultsmentioning

confidence: 98%

Design of Experiments-Based Monitoring of Critical Quality Attributes for the Spray-Drying Process of Insulin by NIR Spectroscopy

Maltesen

Weert

2012

AAPS PharmSciTech

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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.

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“…Case Study: Use of Near Infra-Red (NIR) and Raman Spectroscopy for Freeze-Drying Unit Operation Design NIR spectroscopy has been used to determine real-time moisture content (Bai et al, 2005;Liu, 2006;Lin and Hsu, 2002). For the on-line and real-time measurement, spectroscopic monitoring by NIR and Raman noncontact probes built into the chamber of the freeze-dryer can be used.…”

Section: Introductionmentioning

confidence: 99%

Process analytical technology (PAT) for biopharmaceutical products: Part II. Concepts and applications

Read¹,

Shah²,

Riley³

et al. 2009

Biotech & Bioengineering

148

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Implementing real-time product quality control meets one or both of the key goals outlined in FDA's PAT guidance: "variability is managed by the process" and "product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions." The first part of the paper presented an overview of PAT concepts and applications in the areas of upstream and downstream processing. In this second part, we present principles and case studies to illustrate implementation of PAT for drug product manufacturing, rapid microbiology, and chemometrics. We further present our thoughts on how PAT will be applied to biotech processes going forward. The role of PAT as an enabling component of the Quality by Design framework is highlighted. Integration of PAT with the principles stated in the ICH Q8, Q9, and Q10 guidance documents is also discussed.

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Noninvasive Determination of Protein Conformation in the Solid State Using Near Infrared (NIR) Spectroscopy

Cited by 49 publications

References 27 publications

Multivariate Analysis of Phenol in Freeze-Dried and Spray-Dried Insulin Formulations by NIR and FTIR

Multivariate Analysis of Phenol in Freeze-Dried and Spray-Dried Insulin Formulations by NIR and FTIR

Design of Experiments-Based Monitoring of Critical Quality Attributes for the Spray-Drying Process of Insulin by NIR Spectroscopy

Process analytical technology (PAT) for biopharmaceutical products: Part II. Concepts and applications

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