By integrating high-throughput, single-cell-based functional screening and AI-based drug design and development, each experiment can interrogate millions of therapeutic candidates and generate large-scale, multi-metric data associated with each candidate with respect to function, binding, and developability. The efficient iteration among design, build, test and learn enables us to develop a pipeline that can exponentially accelerate therapeutic design.
By unlocking the design principles of immunity, we can transform the immunotherapeutic design from an empirical and trial-and-error approach to truly rational engineering practice.
Single-cell digital biology
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functional screening
drug design
Decode nature’s design principle
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Our proprietary high-resolution and high-throughput single-cell functional screening platform enables us to significantly increase discovery efficiency while generating indexable, content rich data for each cell. This results in abundant, high-quality training sets for our deep reinforcement learning techniques.
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We employed geometric-aware protein language model and reinforcement learning to drive the design, build, test and learn cycle. As the explosion of structural and functional in-house data increases, our engines become more accurate and rational.
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We are developing technologies that can mine the functional sequence space using libraries with unprecedented high diversity to enable discovery and data generation. Our pipeline also integrates high-throughput protein synthesis and characterization to evaluate the AI-designed therapeutic candidates at scale.
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