{
  "docId": "019de073-9d67-725f-975b-68e2ea1578ba",
  "docSlug": "df4019524c1d62b73cca6d59915e8eef",
  "documentTitle": "Absci | Investor Presentation Deck | 30 slides",
  "authorId": "absci",
  "authorName": "Absci",
  "documentKindSlug": "pitchdeck",
  "documentKindLabel": "Pitch deck",
  "sourceTypeSlug": "investor_relations",
  "sourceTypeLabel": "Investor relations",
  "presentationDate": "2022-10-01 00:00:00",
  "orientation": "landscape",
  "aspectRatio": 1.7777778,
  "pageNumber": 26,
  "pageCount": 30,
  "prevPage": 25,
  "nextPage": 27,
  "slideType": "appendix_data",
  "function": "analyze_data",
  "density": "dense",
  "nDataPoints": 2,
  "notes": "The slide uses box plots and density plots to demonstrate that higher naturalness correlates with better expression and lower mutational burden.",
  "elementsJson": null,
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019de073-9d67-725f-975b-68e2ea1578ba/26",
  "deckHref": "/decks/019de073-9d67-725f-975b-68e2ea1578ba",
  "deckJsonHref": "/decks/019de073-9d67-725f-975b-68e2ea1578ba.json",
  "deckAnchorHref": "/decks/019de073-9d67-725f-975b-68e2ea1578ba#slide-26",
  "components": [
    {
      "bbox": {
        "h": 0.12,
        "w": 0.45,
        "x": 0.52,
        "y": 0.75
      },
      "kind": "callout",
      "text": "Naturalness has an inverse relationship to mutational load illustrating the need to actively optimize for naturalness",
      "attrs": null,
      "subkind": "primary",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "0dde90a4-1566-4f37-bc1f-95fecbcf11d0",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.12,
        "w": 0.45,
        "x": 0.03,
        "y": 0.75
      },
      "kind": "callout",
      "text": "Antibodies with high naturalness scores were expressed at higher levels than antibodies with low scores",
      "attrs": null,
      "subkind": "primary",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "960dccd5-5898-464b-b3b1-65823b0a15d8",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.6,
        "w": 0.4,
        "x": 0.05,
        "y": 0.175
      },
      "kind": "chart",
      "text": "Box plot showing Median HEK-293 Titer vs Naturalness",
      "attrs": null,
      "subkind": "box",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "6c9bc934-cc19-4b8d-b873-ffeb3d7703db",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.6,
        "w": 0.4,
        "x": 0.55,
        "y": 0.175
      },
      "kind": "chart",
      "text": "Density plot showing Mutational load vs Naturalness",
      "attrs": null,
      "subkind": "line",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "9f119cf7-4bf8-4758-a2f9-b93da38c38d2",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.06,
        "w": 0.6,
        "x": 0.03,
        "y": 0.92
      },
      "kind": "source-note",
      "text": "HEK-293 titers of clinical-stage antibodies (Ph2+) from Jain et al., PNAS 114:944 (2017). Bachas, S., Rakocevic, G. et al. Antibody optimization enabled by artificial intelligence predictions of binding affinity and naturalness (2022) pre-print in bioRxiv.",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "59ba42bf-20ca-421d-a910-cbcd3984b5d5",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.12,
        "w": 0.94,
        "x": 0.03,
        "y": 0.03
      },
      "kind": "title",
      "text": "Naturalness is also associated with a higher level of expression in HEK-293 cells and lower mutational load",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "3f028536-2e18-4a7e-b82f-32cf8192e73b",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Chart Selection Guide",
      "slug": "chart-selection-guide",
      "agent": "Designer",
      "layer": "slide",
      "matchId": "92b0ead8-5fe4-403c-b70a-e4ef568033c6",
      "evidence": "Box plot showing Median ADA (%) vs Naturalness (Two-chain Average)",
      "confidence": 0.7
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 29,
      "from": 6,
      "beatId": "8717afca-670f-4c53-9154-841d8d01c54d",
      "arcName": "Problem-Agitate-Solution",
      "arcSlug": "problem-agitate-solution",
      "beatName": "Solution",
      "beatSlug": "problem-agitate-solution-solution-provide-relief",
      "evidence": "The deck presents Absci's AI-enabled platform and active learning cycle as a solution to the challenges of biologic drug discovery.",
      "position": 2,
      "confidence": 0.8,
      "parentBeatName": "Resolution",
      "parentBeatSlug": "resolution"
    }
  ],
  "loops": [
    {
      "to": 26,
      "from": 24,
      "name": "Cost Of Inaction",
      "slug": "27-cost-of-inaction",
      "bestFor": "Urgent budget requests, compliance, risk mitigation",
      "matchId": "299a17ec-2bdc-4f4a-8f9c-f98f13d86ff5",
      "evidence": "The deck highlights the risks and challenges of current methods and the benefits of Absci's solution.",
      "position": 0,
      "objective": "Highlight the risks and challenges of current methods and the benefits of Absci's solution",
      "structure": "The Status Quo -> The Hidden Costs Accumulating -> The Future State of Inaction -> The Tipping Point",
      "confidence": 0.6,
      "description": "Quantify what happens if the audience does nothing"
    },
    {
      "to": 29,
      "from": 6,
      "name": "Jobs To Be Done",
      "slug": "53-jobs-to-be-done",
      "bestFor": "Product innovation, market entry, competitive positioning",
      "matchId": "9ee18f27-0598-416a-8927-048571ff09f9",
      "evidence": "The deck presents Absci's AI-enabled platform and active learning cycle as a solution to the challenges of biologic drug discovery.",
      "position": 1,
      "objective": "Show how Absci's solution can accelerate the discovery and generation of optimized protein biologics",
      "structure": "The Customer's Job -> Current Solutions (Hired/Fired) -> Unmet Needs -> Our Solution Fit",
      "confidence": 0.6,
      "description": "Reframe the problem around what the customer is trying to accomplish, not what they're buying"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}