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  "docSlug": "cdaaa50efb264b4a4093f665bafb20a4",
  "documentTitle": "Absci | Investor Presentation Deck | 111 slides",
  "authorId": "absci",
  "authorName": "Absci",
  "documentKindSlug": "conference-presentation",
  "documentKindLabel": "Conference presentation",
  "sourceTypeSlug": "investor_relations",
  "sourceTypeLabel": "Investor relations",
  "presentationDate": "2023-10-01 00:00:00",
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  "pageCount": 111,
  "prevPage": 44,
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  "notes": "The slide includes Python-like code snippets in the background, likely illustrating the company's computational biology workflow.",
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  "slideHref": "/slides/019de075-e061-72f9-baa2-90171b05eced/45",
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      "kind": "paragraph",
      "text": "from absci import lead_opt_model\nlead_optimizer = lead_opt_model.load_latest()\nlibrary.naturalness =\nlead_optimizer.naturalness(library)\nlead_optimizer.optimize(library).to_wet_lab(assay=\"SPR\")",
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      "text": "from absci import library import codon_optimizer\nlibrary\ncodon_optimizer.reverse_translate(library)\nlibrary.to_csv(\"covid-antibody-designs.csv\")\nlibrary.to_wet_lab(assay=\"ACE\")",
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