Our Technology
AIonios leverages cutting-edge artificial intelligence and machine learning techniques to revolutionize antibody engineering. Our proprietary platform integrates multiple advanced technologies to optimize antibody design, affinity, and functionality.
Core AI Models
Our platform utilizes state-of-the-art deep learning models, including transformer-based architectures and graph neural networks, to predict protein structures, optimize antibody-antigen interactions, and generate novel antibody sequences. These models are trained on vast datasets of known antibody structures and their corresponding properties.
Computational Methods
AIonios employs advanced computational methods such as molecular dynamics simulations, free energy calculations, and in silico affinity maturation to refine and validate antibody designs. These methods allow us to accurately predict the behavior of engineered antibodies in physiological conditions.
Integration of Experimental Data
Our platform continuously integrates new experimental data through active learning algorithms, allowing for real-time improvement of our predictive models. This feedback loop ensures that our AI models stay at the forefront of antibody engineering technology.