Accelerating antibody engineering with in silico solutions
In silico antibody engineering
Computational methods allow us to search and design antibodies effectively in a highly expanded space by combining Generative AI, Denoising Diffusion Probabilistic Models (DDPM) and Machine Learning models of downstream properties.Our proprietary algorithms and computational pipeline seamlessly integrate sequence and structure based design considerations, and incorporate multiple property criteria enabling the design of antibodies with improved antigen binding and developability.
Powered by Generative AI
We leverage cutting edge computational technologies including Generative AI, Denoising Diffusion Probabilistic Models and Machine Learning for therapeutic antibody engineering. Our algorithms combine antigen binding affinity, specificity, and stability to produce desired candidate antibodies. Seamlessly integrating sequence, structure, and multiple property criteria, our proprietary pipeline enhances antibody design for improved antigen binding and developability.