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Cited by 513

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Kinetics of insulin aggregation in aqueous solutions upon agitation in the presence of hydrophobic surfaces.

Open access
Sluzky, V, Tamada, J A, Klibanov, A M, Langer, R·1991·Proceedings of the National Academy of Sciences

Abstract

The stability of protein-based pharmaceuticals (e.g., insulin) is important for their production, storage, and delivery. To gain an understanding of insulin's aggregation mechanism in aqueous solutions, the effects of agitation rate, interfacial interactions, and insulin concentration on the overall aggregation rate were examined. Ultraviolet absorption spectroscopy, high-performance liquid chromatography, and quasielastic light scattering analyses were used to monitor the aggregation reaction and identify intermediate species. The reaction proceeded in two stages; insulin stability was enhanced at higher concentration. Mathematical modeling of proposed kinetic schemes was employed to identify possible reaction pathways and to explain greater stability at higher insulin concentration.

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Metadata

Authors
Sluzky, V, Tamada, J. A., Klibanov, A. M., & Langer, R.
Venue
Proceedings of the National Academy of Sciences
Published
1991-11
Volume
88
Issue
21
Pages
9377-9381
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1988089792
Cited by
513
References
0
FWCI
1.78
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Kinetics of insulin aggregation in aqueous solutions upon agitation in the presence of hydrophobic surfaces. https://app.cochat.ai/papers/10.1073/pnas.88.21.9377
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Sluzky, V, Tamada, J. A., Klibanov, A. M., & Langer, R. (1991). Kinetics of insulin aggregation in aqueous solutions upon agitation in the presence of hydrophobic surfaces. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.88.21.9377

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.