Deliver the impact

Cutting-edge biologics AI suite for licensing

Turning Innovation into Impact
At the heart of our AI-driven platforms is a simple question: What is the biggest gap in biologics discovery that AI can or cannot fill?

 

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Focusing on 3 value-added topics to transform drug discovery paradigm:

  • Elucidating antibody-antigen interaction at a high accuracy:  No commercially available algorithms can deliver the precision required for reliable structure-based antibody engineering. We aim to change that by providing unprecedented accuracy and commercial availability.
  • Generative protein design: Traditional rule-based methods rely on exhaustive searches of vast sequence spaces, which are both inefficient and hard to scale. Our approach introduces smarter, more efficient ways to design proteins at scale.
  • Multi-parametric prediction and active learning:  Most predictive algorithms for antibody features—such as binding affinity and developability—are based on limited, curated datasets. As a result, they often underperform in real-world applications and fail to adapt to new antibody-antigen interaction patterns. We harness the power of proprietary training datasets and active learning to improve predictions and continuously refine our models based on project-specific data.

 

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