AION Labs’ CombinAble.AI: AI-powered antibody design redefined

This startup, born out of AION Labs’ startup challenge, aims to enhance the development of biological therapeutics by using the latest AI technologies.

The company says CombinAble.AI represents a bold departure from traditional antibody optimization methods, which often involve laborious trial-and-error processes.

By embracing advanced machine learning models and computational simulations, AION says the platform promises to accelerate the discovery of more effective therapeutic antibodies, potentially revolutionizing the drug development pipeline.

Advanced machine learning learning models

Daria Kokh, co-founder and CEO of CombinAble, explained the company’s approach, she said: “Our emphasis is on combining various advanced machine learning models, including large protein language models, molecular dynamics simulations, and multi-objective optimization algorithms, integrating them into a single unified solution for targeted antibody discovery.”

The company says the traditional pathway to antibody optimization is notorious for its time-consuming nature and high costs, with success far from guaranteed. CombinAble’s inventive methodology, it says, seeks to circumvent these challenges by enabling a model to “learn” from data and physics-based principles to identify optimal solutions in a single iteration.

Antibody optimization is a critical stage in the drug development process, involving the transformation of preliminary antibody hits into viable clinical candidates. By automating the selection of mutations that enhance multiple biophysical characteristics of antibody candidates, CombinAble.AI aims to speed up this process, potentially shortening development timelines and reducing costs.

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