How can we discover developable antibody-based biotherapeutics?

Area of Science:

• Biopharmaceutical Informatics
• Antibody Drug Discovery
• Computational Biology

Background:

• Antibody-based biotherapeutics represent a successful but challenging pharmaceutical class.
• Significant hurdles exist in the research and development (R&D) of these complex drugs.

Purpose of the Study:

• To propose biopharmaceutical informatics as a framework to address R&D challenges.
• To advocate for integrating computation and experimentation throughout biologic drug discovery.
• To consider drug developability early in the discovery phase.

Main Methods:

• Review of computational approaches for antigen optimization and immune response.
• Analysis of in silico antibody sequence generation and virtual screening.
• Assessment of computational methods for lead candidate identification and affinity maturation.

Main Results:

• Computational advances enable precise disease concept formulation and target identification.
• Emerging computational methods facilitate de novo and epitope-specific antibody design.
• Virtual screening and computational assessment aid in discovering and optimizing antibody binders.

Conclusions:

• Biopharmaceutical informatics offers opportunities to overcome limitations in antibody R&D.
• Integrating computational strategies enhances candidate selection and developability.
• Adoption of this framework can accelerate the delivery of affordable, effective biotherapeutics.