Download the poster to see how Al/ML technologies and workflows combined with a proprietary high-throughput screening method accelerate antibody discovery and lead optimization.
Therapeutic antibody discovery is becoming faster and more efficient with the integration of cutting-edge artificial intelligence (Al) and machine learning (ML) technologies into the workflow, enabling identification of high quality lead candidates with optimal affinity and developability.
Alloy Therapeutics takes a precision-driven approach to generating, retrieving, and evaluating antibodies with optimal therapeutic properties. Leveraging their proprietary ATX-GxTM humanized mice, advanced selection and characterization workflows, and a proprietary suite of Al and ML tools, Alloy delivers data-informed, efficient, and accelerated antibody discovery and development services.
Download the poster to discover how Alloy Therapeutics’ utilizes AI-enabled and ML-powered computational tools combined with their proprietary mAbForgeTM high-throughput antibody characterization platform to select optimal clones from in vivo repertoires or engineer antibodies with desired affinity and developability.
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Cutting-edge computational tools analyze immune repertoires from immunized ATX-Gx mice to select an optimal set of sequences that maximize diversity and hit rate while eliminating liabilities.
ML-trained models predict liabilities like hydrophobicity and polyreactivity to identify candidates with optimal drug-like properties.
AI-enabled design of antibody variants to predict mutations with enhanced affinity, specificity, or developability.
High throughput expression and characterization of hundreds to thousands of antibodies, going from in silico sequences to affinity, specificity, and purity data in as little as 3 weeks.
Large panels of computationally selected clones from in vivo repertoires are screened to maximize diversity and find rare clones with desired epitope and function.
Panels of computationally-designed variants are optimized via rapid and iterative design-build-test cycles using a high-throughput characterization platform.
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