Augment Biologics

Using foundational discoveries in glycobiology to transform biologic drug development.

Augment is leveraging novel and foundational insights into glycobiology to build an AI-guided glycoprotein-drug design platform: GlycoTemplating. Unlike traditional glycoengineering, GlycoTemplating writes glycans into the primary sequence of biologics with site-specific accuracy, improving drug efficacy, safety, durability, and manufacturing. Augment created the first expression platform agnostic approach to site-specific glycoengineering. Augment is using GlycoTemplating to create best-in-class biologics, with near-term applications in antibody, protein, and peptide engineering and long-term applications in other biologic modalities including RNA therapeutics, delivery vehicle, and vaccine development GlycoTemplating is founded on discoveries in glycan biosynthesis from the Lewis Lab at UCSD/University of Georgia.

What is the problem?

Glycans are critical to human biology, mediating immune system regulation, cell-cell interactions, and protein stability and activity. In drug development, glycans are a major part of biotherapeutics and control biologic activity, efficacy, and safety. Glycan diversity and complexity are difficult to engineer due to the lack of a genetic code for glycan synthesis. Current glycoengineering methods, such as bioprocess engineering and synthetic glycosylation, face limitations like high costs, unpredictability, and poor scalability. Bioprocess engineering is expensive, slow, and specific to cell lines, complicating its integration into drug design. Meanwhile, synthetic glycosylation struggles to achieve necessary diversity, biologic complexity, and is not cost-effective for large-scale production.

What is their solution?

Augment discovered the genetic code for glycan biosynthesis and developed an artificial intelligence-driven platform, the GlycoTemplate, to enable drug developers to write glycans directly into the protein sequence. Augment dissected associations between protein and glycan structures and encoded those associations in a multi-view neural network. Using GlycoTemplating and single-cell glycan-phenotyping, Augment can predict, modify, and stabilize glycosylation on any biologic.