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Identification of Subvisible Particles in Biopharmaceutical Formulations Using Raman Spectroscopy Provides Insight into Polysorbate 20 Degradation Pathway.

Saggu M, Liu J, Patel A - Pharm. Res. (2015)

Bottom Line: To study composition and heterogeneity of insoluble subvisible particles in Mab formulations resulting from degradation of polysorbate 20 and to develop a better understanding of the mechanisms of polysorbate degradation leading to particle formation.Most of the subvisible particles identified were comprised of mixtures of fatty acids with no observable signal from fatty acid esters consistent with hydrolysis being the predominant degradation mechanism leading to particulate formation under these storage conditions.Our methodology is generally applicable for identification of particles in antibody formulations and, in particular, has the potential to give detailed information about particle heterogeneity and insight into mechanistic aspects of particle formation.

View Article: PubMed Central - PubMed

Affiliation: Late Stage Pharmaceutical Development, Genentech Inc., South San Francisco, California, 94080, USA, saggu.miguel@gene.com.

ABSTRACT

Purpose: To study composition and heterogeneity of insoluble subvisible particles in Mab formulations resulting from degradation of polysorbate 20 and to develop a better understanding of the mechanisms of polysorbate degradation leading to particle formation.

Methods: In this study, we exploit the potential of Raman microscopy for chemical identification of particles in monoclonal antibody formulations. Through a combination of experiments and density functional theory (DFT) calculations, we identified unique spectral marker bands for insoluble degradation products of polysorbate 20. We first applied our methodology to identify particles in model systems containing complex mixtures of fatty acids and then to subvisible particles in antibody formulations stored at 5°C for several years.

Results: Most of the subvisible particles identified were comprised of mixtures of fatty acids with no observable signal from fatty acid esters consistent with hydrolysis being the predominant degradation mechanism leading to particulate formation under these storage conditions.

Conclusions: Our methodology is generally applicable for identification of particles in antibody formulations and, in particular, has the potential to give detailed information about particle heterogeneity and insight into mechanistic aspects of particle formation.

No MeSH data available.


Calculated Raman spectra of fatty acids using DFT. Spectra have been scaled using a wavenumber linear scaling procedure according to Yoshida et al. (19) (a) capric acid (b) lauric acid (c) myristic acid and (d) palmitic acid.
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Fig2: Calculated Raman spectra of fatty acids using DFT. Spectra have been scaled using a wavenumber linear scaling procedure according to Yoshida et al. (19) (a) capric acid (b) lauric acid (c) myristic acid and (d) palmitic acid.

Mentions: The calculated Raman spectra are shown in Fig. 2. In general the calculations are able to reproduce experimental vibrational frequencies and intensities reasonably well when compared to experimental spectra shown in Fig. 1 especially in the spectral region above 800 cm−1. Vibrational frequencies for δ(CH2) rocking modes, ν(C-C) stretch modes and δ(CH2) twisting mode are all within ±20 cm−1 compared to experimental values (see Table I). The biggest discrepancy can be seen for the carbonyl stretch ν(C = O), which is blue-shifted to 1774 cm−1 in the calculated spectra. The fact that these samples consist of solid-state particles on filters contributes significantly to the sharpness of the experimental spectra, in which band broadening due to solution dynamics is not observed. Further, band shifts are negligible due to the hydrophobic nature of fatty acids which create negligible electric field contributions. The discrepancy in the carbonyl stretch frequency is attributed to the fact that specific interactions such as hydrogen bonding are not included in the gas-phase calculations.Fig. 2


Identification of Subvisible Particles in Biopharmaceutical Formulations Using Raman Spectroscopy Provides Insight into Polysorbate 20 Degradation Pathway.

Saggu M, Liu J, Patel A - Pharm. Res. (2015)

Calculated Raman spectra of fatty acids using DFT. Spectra have been scaled using a wavenumber linear scaling procedure according to Yoshida et al. (19) (a) capric acid (b) lauric acid (c) myristic acid and (d) palmitic acid.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4526581&req=5

Fig2: Calculated Raman spectra of fatty acids using DFT. Spectra have been scaled using a wavenumber linear scaling procedure according to Yoshida et al. (19) (a) capric acid (b) lauric acid (c) myristic acid and (d) palmitic acid.
Mentions: The calculated Raman spectra are shown in Fig. 2. In general the calculations are able to reproduce experimental vibrational frequencies and intensities reasonably well when compared to experimental spectra shown in Fig. 1 especially in the spectral region above 800 cm−1. Vibrational frequencies for δ(CH2) rocking modes, ν(C-C) stretch modes and δ(CH2) twisting mode are all within ±20 cm−1 compared to experimental values (see Table I). The biggest discrepancy can be seen for the carbonyl stretch ν(C = O), which is blue-shifted to 1774 cm−1 in the calculated spectra. The fact that these samples consist of solid-state particles on filters contributes significantly to the sharpness of the experimental spectra, in which band broadening due to solution dynamics is not observed. Further, band shifts are negligible due to the hydrophobic nature of fatty acids which create negligible electric field contributions. The discrepancy in the carbonyl stretch frequency is attributed to the fact that specific interactions such as hydrogen bonding are not included in the gas-phase calculations.Fig. 2

Bottom Line: To study composition and heterogeneity of insoluble subvisible particles in Mab formulations resulting from degradation of polysorbate 20 and to develop a better understanding of the mechanisms of polysorbate degradation leading to particle formation.Most of the subvisible particles identified were comprised of mixtures of fatty acids with no observable signal from fatty acid esters consistent with hydrolysis being the predominant degradation mechanism leading to particulate formation under these storage conditions.Our methodology is generally applicable for identification of particles in antibody formulations and, in particular, has the potential to give detailed information about particle heterogeneity and insight into mechanistic aspects of particle formation.

View Article: PubMed Central - PubMed

Affiliation: Late Stage Pharmaceutical Development, Genentech Inc., South San Francisco, California, 94080, USA, saggu.miguel@gene.com.

ABSTRACT

Purpose: To study composition and heterogeneity of insoluble subvisible particles in Mab formulations resulting from degradation of polysorbate 20 and to develop a better understanding of the mechanisms of polysorbate degradation leading to particle formation.

Methods: In this study, we exploit the potential of Raman microscopy for chemical identification of particles in monoclonal antibody formulations. Through a combination of experiments and density functional theory (DFT) calculations, we identified unique spectral marker bands for insoluble degradation products of polysorbate 20. We first applied our methodology to identify particles in model systems containing complex mixtures of fatty acids and then to subvisible particles in antibody formulations stored at 5°C for several years.

Results: Most of the subvisible particles identified were comprised of mixtures of fatty acids with no observable signal from fatty acid esters consistent with hydrolysis being the predominant degradation mechanism leading to particulate formation under these storage conditions.

Conclusions: Our methodology is generally applicable for identification of particles in antibody formulations and, in particular, has the potential to give detailed information about particle heterogeneity and insight into mechanistic aspects of particle formation.

No MeSH data available.