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Colloidal precipitates01:09

Colloidal precipitates

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The high insolubility of some precipitates can result in an unfavorable relative supersaturation. This can lead to colloidal particles with a large surface-to-mass ratio, where adsorption is promoted. For instance, in the precipitation of silver chloride, silver ions are adsorbed on the surface of the colloidal particles, forming a primary layer. This layer attracts ions of opposite charge (such as nitrate ions), forming a diffuse secondary layer of adsorbed ions. This electric double layer...
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The formation of a colloidal system is exemplified by an aqueous solution containing Cl− ions is introduced to another containing Ag+ ions, resulting in the precipitation of solid AgCl as extremely tiny crystals. Instead of settling out as a filterable precipitate, these crystals remain suspended in the liquid, showcasing a colloidal system.A colloidal system involves colloidal particles within the approximate range of 1 to 1000 nm in at least one dimension, dispersed in a medium called...
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Computational Screening for mAb Colloidal Stability with Coarse-Grained, Molecular-Scale Simulations.

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Identifying stable monoclonal antibodies (mAbs) early is crucial for developing effective protein therapeutics. This study presents a computational model to predict colloidal stability, aiding in early drug candidate screening and formulation.

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Area of Science:

  • Protein therapeutics
  • Biopharmaceutical development
  • Computational biophysics

Background:

  • Monoclonal antibodies (mAbs) are vital protein therapeutics, but their development is often hindered by colloidal instabilities at high concentrations.
  • Developing stable, high-concentration liquid formulations is essential for patient-centric, device-mediated delivery of protein therapeutics.
  • Current experimental methods for assessing colloidal stability are time-consuming and resource-intensive, typically performed late in development.

Purpose of the Study:

  • To develop and validate an efficient computational approach for early screening of colloidal stability in monoclonal antibodies (mAbs).
  • To provide a framework for predicting mAb self-interactions and bulk solution behavior, aiding in the selection of developable candidates.
  • To support both early-stage candidate screening and later-stage formulation strategies for protein therapeutics.

Main Methods:

  • Fine-tuning of coarse-grained, molecular-scale models for screening colloidal stability at amino-acid resolution.
  • Development of a computational framework to analyze mAb self-interactions and predict bulk solution behavior.
  • Application of the computational model to a diverse set of mAbs across various buffer conditions.

Main Results:

  • The computational model successfully screened for colloidal stability of monoclonal antibodies (mAbs) at amino-acid resolution.
  • The model's parameterization provides a robust framework for assessing mAb self-interactions and predicting solution behavior.
  • The approach demonstrated utility in augmenting early candidate screening and informing formulation strategies for protein therapeutics.

Conclusions:

  • Computational screening of colloidal stability offers an efficient alternative to experimental methods for early-stage drug development.
  • The developed molecular-scale modeling approach can identify colloidally stable mAbs, facilitating the selection of promising therapeutic candidates.
  • This computational strategy enhances the development of stable, high-concentration liquid formulations for protein therapeutics.