Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations.

Area of Science:

• Biochemistry
• Computational Chemistry
• Pharmaceutical Sciences

Background:

• Excipients stabilize protein biotherapeutics but aren't optimized for anti-aggregation or cryoprotection.
• Understanding excipient structure-activity relationships is crucial for designing better protein formulations.

Purpose of the Study:

• To explore the link between excipient structure and anti-aggregation activity.
• To identify key structural features for effective protein stabilization.
• To propose a computational model for designing novel stabilizing excipients.

Main Methods:

• Coarse-grained molecular dynamics simulations of protein-excipient interactions.
• Studied 41 diverse excipients with human serum albumin as a model protein.
• Utilized physicochemical descriptors and partial least-squares regression for structure-property analysis.

Main Results:

• Polyoxyethylene sorbitan showed the highest interaction, reducing aggregation-prone region surface area by 40.1%.
• Longer molecules with numerous PEG units wrapped around the protein, while shorter ones formed clusters.
• A predictive model achieved a root-mean-square error of 4.1 nm² and mean relative error of 0.077.

Conclusions:

• Excipient design should incorporate multiple short PEG chains and hydrophobic segments for optimal protein stabilization.
• This computational approach is a foundational step towards protein-independent excipient design.
• The findings facilitate the computer-aided design of effective stabilizing excipients for biotherapeutics.