Modeling and mitigation of high-concentration antibody viscosity through structure-based computer-aided protein...

Area of Science:

• Biopharmaceutical development
• Protein engineering
• Antibody therapeutics

Background:

• Therapeutic antibodies require optimization of binding affinity, biophysical properties, and immunogenicity.
• High antibody concentrations (>150 mg/ml) are needed for subcutaneous dosing, but can lead to high viscosity.
• High viscosity impedes manufacturing and necessitates impractical delivery methods.

Purpose of the Study:

• To optimize an anti-PDGF-BB antibody for reduced viscosity at high concentrations.
• To enable formulation of the antibody at >160 mg/ml for subcutaneous delivery.
• To investigate structure-guided rational design for viscosity reduction.

Main Methods:

• Two rounds of structure-guided rational design were employed.
• Surface electrostatic properties were optimized by introducing charge changes in Fv and CDR regions.
• Viscosity measurements were performed on 40 unique antibody variants.

Main Results:

• Antibody formulation concentration was increased from 80 mg/ml to >160 mg/ml.
• Binding affinity was maintained throughout the optimization process.
• Net-positive charge changes and disruption of negative charge patches correlated with decreased viscosity, dependent on local environment.

Conclusions:

• Rational design effectively reduced antibody viscosity, enabling higher concentration formulations.
• Surface electrostatics play a critical role in antibody viscosity.
• This study provides a comprehensive dataset for antibody viscosity reduction strategies.