How does Creative Biolabs utilize AI to address drug resistance in antibody therapeutics?

Creative Biolabs employs a specialized AI platform to predict potential resistance mutations and design next-generation antibodies that maintain binding affinity despite target evolution. The AI analyzes large-scale genomic and structural datasets to identify "resistance-proof" epitopes that are less likely to mutate or are essential for the survival of the pathogen or cancer cell.

What are the primary mechanisms of drug resistance targeted by this service?
A2: The AI models are designed to anticipate and circumvent several resistance pathways:

Antigenic Drift/Mutation: Predicting amino acid substitutions in the target that lead to loss of antibody binding.

Alternative Pathway Activation: Identifying "bypass" signals that cancer cells use to escape single-target therapies.

Epitope Masking: Designing antibodies that can penetrate structural changes or glycosylation patterns used by targets to hide binding sites.

For more: AI-Driven Antibody Design Service: Overcoming Drug Resistance