AI/ML-ab™ de novo Antibody Discovery
Traditional methods—animal immunization and display technologies— can be limited by immunodominance and physical library size. This might mean missing rare, high-affinity binders. Similarly, the antigen may be difficult to produce, toxic or not available. AI/ML-ab™ breaks through these constraints with virtual screening of libraries millions of times larger than conventional platforms, delivering focused, high-potential candidates for wet-lab validation.
AI/ML-ab™ de novo Antibody Discovery
Traditional methods—animal immunization and display technologies— can be limited by immunodominance and physical library size. This might mean missing rare, high-affinity binders. Similarly, the antigen may be difficult to produce, toxic or not available. AI/ML-ab™ breaks through these constraints with virtual screening of libraries millions of times larger than conventional platforms, delivering focused, high-potential candidates for wet-lab validation.
Antibody Discovery Beyond Imagination
Fusion’s Solid Foundation for AI/ML Discovery
Fusion’s AI/ML-ab™ platform is built on a strong foundation of proprietary technologies that drive antibody discovery and engineering:
- Custom Library Design – Delivers tailored libraries for specific discovery goals.
- OptiMAL® Library Design – Powers intelligent, high-diversity library creation.
- Humanization CDRx® – Enables precise humanization of antibody sequences.
- RAMP® Affinity Maturation – Accelerates optimization of binding affinity.
These platforms provide the critical data, workflows, and design logic that fuel Fusion’s next-generation AI/ML-ab™ engine—bringing machine learning to the heart of antibody innovation.
Data-Driven Discovery
Fusion’s AI/ML-ab™ is built on the largest antibody datasets in the industry:
- 550M unique human antibody sequences
- 212K+ proprietary antibody–antigen interactions across 253 targets
- 2B+ AI-generated, developability-screened sequences
- 1B mature human antibodies from 80 studies, including OPIG OAS data
Powered by Deep Learning
Fusion’s proprietary AI/ML-ab™ platform integrates:
- Protein Large Language Models (PLLMs)
- Diffusion-based sequence generation
- Virtual molecular docking and free energy ranking
This enables precise epitope targeting, scaffold selection, and antibody design, down to the amino acid level.
From Sequence to Structure
The AI-driven workflow includes:
- Epitope mapping and binding site prediction
- Scaffold selection and motif incorporation
- Sequence optimization for stability and affinity
- Structure modeling and binder ranking
The result: a compact, high-quality library of 103–104 paired HC/LC sequences, ready for mammalian display.
Target the Right Epitope
Unlike conventional approaches, AI/ML-ab™ allows targeted antibody design at the amino acid level, focusing on functional epitopes and avoiding immunodominant regions that may lack therapeutic value.
Where AI Meets the Bench
Fusion’s mammalian display platform expresses full-length IgG in HEK293 cells, ensuring:
- Native-format antibodies—no reformatting required
- Early developability screening (expression, aggregation, stability)
- High-fidelity selection via BLI kinetic profiling
Lead candidates are delivered in just 4–5 months.
Platform Advantages
| Feature | Impact |
|---|---|
| Focused Library Design | In silico screening narrows billions to a targeted, testable subset |
| Epitope-Level Targeting | Antibodies designed for functional, therapeutic regions—not just immunogenic ones |
| Full-Length IgG Expression | Native format from the start—no post-screening reformatting |
| Built-In Developability Checks | Mammalian expression reveals stability and manufacturability early |
| Reduced Engineering Burden | Fewer downstream modifications needed |
| High-Affinity Binder Selection | Direct identification of potent, biophysically sound antibodies |
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