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Pharmaceutical Research

, Volume 34, Issue 9, pp 1831–1839 | Cite as

High Throughput Prediction Approach for Monoclonal Antibody Aggregation at High Concentration

  • Mitja Zidar
  • Ana Šušterič
  • Miha Ravnik
  • Drago KuzmanEmail author
Research Paper

Abstract

Purpose

Characterization of the monoclonal antibody aggregation process and identification of stability factors that could be used as indicators of aggregation propensity with an emphasis on a large number of samples and low protein material consumption.

Methods

Differential scanning calorimetry, dynamic light scattering and size exclusion chromatography were used as the main methodological approaches. Conformational stability, colloidal stability and aggregation kinetics were assessed for two different IgG monoclonal antibody (mAbs) subclasses. Aggregation was induced by exposing the mAbs to 55°C for 3 weeks. mAb samples were prepared in different formulations and concentrations from 1 mg/mL to 50 mg/mL.

Results

High temperature stress of mAb samples revealed that monoclonal antibodies followed first order aggregation kinetics, which suggests that the rate-limiting step of monomer loss was unimolecular. Conformational stability of mAbs was estimated with denaturation temperature measurements. Colloidal stability was assessed with dynamic interaction parameter k D . The correlation between aggregation kinetics and colloidal and conformational stability factors was evaluated and the dynamic interaction parameter was found to be a promising predictor of aggregation propensity of monoclonal antibodies. The meaning of using an intermolecular interaction parameter for prediction of what is essentially a unimolecular process is also discussed.

Conclusions

This work estimates the significance of different predictors of aggregation propensity at high concentrations as a part of a high throughput, low resource screening method and is a contribution towards determining protein aggregation phenomena in actual systems used for the development and production of biopharmaceuticals.

Key words

aggregation modelling aggregation predictors biopharmaceuticals intermolecular interactions protein aggregation 

Abbreviations

DLS

Dynamic light scattering

DSC

Differential scanning calorimetry

mAb

Monoclonal antibody

SEC

Size exclusion chromatography

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Faculty of Mathematics and PhysicsUniversity of LjubljanaLjubljanaSlovenia
  2. 2.Novartis Technical Operations, BTDMLek Pharmaceuticals d.d.MengešSlovenia
  3. 3.Jozef Stefan InstituteLjubljanaSlovenia

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