{
  "docId": "019de073-f0bf-7547-8ad6-12100ed22e83",
  "docSlug": "a88a01f7711a3a01e2c4b1dc80e80f39",
  "documentTitle": "BenevolentAI | Investor Conference Presentation Deck | 17 slides",
  "authorId": "benevolentai",
  "authorName": "BenevolentAI",
  "documentKindSlug": "conference-presentation",
  "documentKindLabel": "Conference presentation",
  "sourceTypeSlug": "investor_relations",
  "sourceTypeLabel": "Investor relations",
  "presentationDate": "2022-11-01 00:00:00",
  "orientation": "landscape",
  "aspectRatio": 1.7777778,
  "pageNumber": 6,
  "pageCount": 17,
  "prevPage": 5,
  "nextPage": 7,
  "slideType": "before_after",
  "function": "quantify_opportunity",
  "density": "dense",
  "nDataPoints": 12,
  "notes": "The slide uses a split-screen approach to contrast pre-clinical efficiency with clinical efficacy improvements.",
  "elementsJson": null,
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019de073-f0bf-7547-8ad6-12100ed22e83/6",
  "deckHref": "/decks/019de073-f0bf-7547-8ad6-12100ed22e83",
  "deckJsonHref": "/decks/019de073-f0bf-7547-8ad6-12100ed22e83.json",
  "deckAnchorHref": "/decks/019de073-f0bf-7547-8ad6-12100ed22e83#slide-6",
  "components": [
    {
      "bbox": {
        "h": 0.1,
        "w": 0.9,
        "x": 0.05,
        "y": 0.15
      },
      "kind": "diagram",
      "text": "Direct R&D Cost Savings (Discovery & Pre-Clinical) vs Increasing Probability of Success (Clinical Development)",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "20d9ec56-68fe-44be-996f-dd61743a6498",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.08,
        "w": 0.35,
        "x": 0.05,
        "y": 0.62
      },
      "kind": "paragraph",
      "text": "Reduce pre-clinical cost by >50% and time to market by 2-2.5 years",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "cbba55ed-5f9b-465b-b134-14c822895f9b",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.4,
        "x": 0.05,
        "y": 0.92
      },
      "kind": "source-note",
      "text": "Notes and Sources: For illustrative purposes only; (1) Illustrative NPV... (5) Based on Odyssey Due Diligence report.",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "4804f6f7-b491-40cd-8826-37c48f0908dd",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.25,
        "w": 0.35,
        "x": 0.05,
        "y": 0.35
      },
      "kind": "table",
      "text": "Industry standard vs AI-enhanced pre-clinical metrics",
      "attrs": null,
      "subkind": "data",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "25749ff5-185f-4ee1-8d3c-e13fc5543ffe",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.35,
        "w": 0.35,
        "x": 0.45,
        "y": 0.55
      },
      "kind": "table",
      "text": "Industry standard vs AI-enhanced clinical metrics",
      "attrs": null,
      "subkind": "data",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "8d6bb2fc-ba92-4c5b-9317-c471be519f86",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.5,
        "x": 0.05,
        "y": 0.05
      },
      "kind": "title",
      "text": "The AI value proposition for pharma R&D",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "b4e04319-4b3e-4ab7-9915-7dc43c73982e",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [],
  "frameworks": [
    {
      "name": "before-after-framing",
      "slug": null,
      "matchId": "3df5b14e-8d5c-438d-a88c-744fcf92ac67",
      "evidence": "Contrasts 'Industry Standard' with 'AI-Enhanced' metrics across two R&D stages.",
      "confidence": 1
    }
  ],
  "arcBeats": [
    {
      "to": 8,
      "from": 5,
      "beatId": "a8c01471-1f45-4f55-a1ab-9186d382e923",
      "arcName": "Problem-Agitate-Solution",
      "arcSlug": "problem-agitate-solution",
      "beatName": "Agitate (Make it worse)",
      "beatSlug": "problem-agitate-solution-agitate-make-it-worse",
      "evidence": "Slides 5-8 agitate the problem, showcasing the limitations of current approaches and the potential benefits of AI-enabled drug discovery.",
      "position": 1,
      "confidence": 0.8,
      "parentBeatName": "Development",
      "parentBeatSlug": "development"
    }
  ],
  "loops": [
    {
      "to": 8,
      "from": 5,
      "name": "Cost Of Inaction",
      "slug": "27-cost-of-inaction",
      "bestFor": "Urgent budget requests, compliance, risk mitigation",
      "matchId": "3a064e81-9455-49a9-95b4-cb453f8513d0",
      "evidence": "The document highlights the inefficiencies and costs associated with current pharma R&D approaches, implying the costs of inaction.",
      "position": 0,
      "objective": "What are the costs of not adopting AI-enabled drug discovery?",
      "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"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}