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  "notes": "The slide uses a histogram to visualize the distribution of binding affinity (-log10(KD)) for designed variants compared to the wild-type Trastuzumab baseline.",
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      "text": "AI predicts the affinity of unseen variants from libraries generated using diverse mutational strategies and combinatorial sequence space. AI models make predictions with actionable performance using <0.1% of the combinatorial sequence space as training set. Naturalness is associated with developability metrics and expression titer. Enables one-shot multiparametric lead optimization potentially accelerating time to clinic",
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      "text": "CASE STUDY: AI-DRIVEN LEAD OPTIMIZATION",
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