Protein-protein interactions and water activity coefficients can be used to aid a first excipient choice in protein formulations

Schleinitz, Miko; Sadowski, Gabriele; Brandenbusch, Christoph

doi:10.1016/j.ijpharm.2019.118608

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…1 Several improvements of DLVO were reported, including introduction of the multiple binding sites to other proteins 40 or addition of a salt-induced osmotic attraction potential. 41 The latter model was also extended to compute B 22 of protein solutions with excipients 42 in the presence of polymers. 43 Details of the extended DLVO (xDLVO) method are given in Section 2.2.…”

Section: Introductionmentioning

confidence: 99%

A coarse-grained xDLVO model for colloidal protein–protein interactions

Pusara

Yamin

Wenzel

et al. 2021

Phys. Chem. Chem. Phys.

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Section: Introductionmentioning

confidence: 99%

A coarse-grained xDLVO model for colloidal protein–protein interactions

Pusara

Yamin

Wenzel

et al. 2021

Phys. Chem. Chem. Phys.

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“…An extended version of DLVO (xDLVO) has also been developed to incorporate other types of interactions such as dispersion forces and osmotic potential. 206 , 207 Different reports have shown that both DLVO and xDLVO can predict the overall trends of for protein solutions as a function of ionic excipient concentration 208 and in the presence of polymers. 206 Nonetheless, these theories provide only qualitative representations for protein interactions, as they are unable to accurately capture how is affected by anisotropy in terms of both protein shape and surface heterogeneity.…”

Section: Protein-protein and Protein-excipient Interactionsmentioning

confidence: 99%

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Blanco

2022

mAbs

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Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

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