{
  "docId": "019de076-2351-76a2-9dc5-1c75bf1dd158",
  "docSlug": "905d9ceaf5cb608feb86b583a8401e54",
  "documentTitle": "AstraZeneca | Results Presentation Deck | 45 slides",
  "authorId": "astrazeneca",
  "authorName": "AstraZeneca",
  "documentKindSlug": "conference-presentation",
  "documentKindLabel": "Conference presentation",
  "sourceTypeSlug": "investor_relations",
  "sourceTypeLabel": "Investor relations",
  "presentationDate": "2023-11-01 00:00:00",
  "orientation": "landscape",
  "aspectRatio": 1.7777778,
  "pageNumber": 13,
  "pageCount": 45,
  "prevPage": 12,
  "nextPage": 14,
  "slideType": "key_messages",
  "function": "present_solution",
  "density": "dense",
  "nDataPoints": 2,
  "notes": "The slide uses a two-column layout to contrast data integration (AZBrain) with specific application use cases.",
  "elementsJson": null,
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019de076-2351-76a2-9dc5-1c75bf1dd158/13",
  "deckHref": "/decks/019de076-2351-76a2-9dc5-1c75bf1dd158",
  "deckJsonHref": "/decks/019de076-2351-76a2-9dc5-1c75bf1dd158.json",
  "deckAnchorHref": "/decks/019de076-2351-76a2-9dc5-1c75bf1dd158#slide-13",
  "components": [
    {
      "bbox": {
        "h": 0.35,
        "w": 0.25,
        "x": 0.15,
        "y": 0.045
      },
      "kind": "diagram",
      "text": "AZBrain data integration flow",
      "attrs": null,
      "subkind": "process",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "658752ee-c74d-457b-b9fd-854ad63f7dbe",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.52,
        "x": 0.42,
        "y": 0.45
      },
      "kind": "list",
      "text": "Optimising identification of at-risk patients; Applying AI and deep multimodal data to identify high responders; Predicting treatment eligible patient presentation in clinic",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "79cc0a60-4732-4006-8827-e7585759601a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.1,
        "w": 0.15,
        "x": 0.78,
        "y": 0.45
      },
      "kind": "metric",
      "text": ">6m analysed handwritten EMR notes in 24hrs",
      "attrs": null,
      "subkind": "big-number",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "d677201d-d917-43a4-a2df-06001228f745",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.94,
        "x": 0.03,
        "y": 0.24
      },
      "kind": "title",
      "text": "DRIVING FASTER, BETTER DECISION MAKING | harnessing technology to deliver better patient outcomes",
      "attrs": null,
      "subkind": "action-title",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7237cb58-7572-4c75-867e-2ae18865fa99",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.35,
        "x": 0.03,
        "y": 0.06
      },
      "kind": "title",
      "text": "AstraZeneca – AI in Commercial",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "af8717f7-5503-4c5c-98ac-aea8d9625c48",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Story Moments",
      "slug": "story-moments",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "f0cfd348-e214-4bad-8fb8-a3f299f483ec",
      "evidence": "The use of bullet points and short sentences creates story moments that convey key information.",
      "confidence": 0.5
    },
    {
      "name": "Three-Act Structure",
      "slug": "three-act-structure",
      "agent": "Storyteller",
      "layer": "slide",
      "matchId": "088b893c-d9f2-432f-9241-c5443ddf71ab",
      "evidence": "The slide presents a clear structure with key messages, data, and a call to action, following a three-act structure.",
      "confidence": 0.7
    }
  ],
  "frameworks": [],
  "arcBeats": [],
  "loops": [
    {
      "to": 20,
      "from": 5,
      "name": "Logic Chain",
      "slug": "01-logic-chain",
      "bestFor": "Skeptical audiences, controversial recommendations, rigorous analysis",
      "matchId": "4272c71f-edd6-48f7-a353-789a42575177",
      "evidence": "The document walks through a logical chain of financial performance, portfolio evolution, and R&D highlights",
      "position": 0,
      "objective": "How AstraZeneca's diversified portfolio drives growth",
      "structure": "Premise 1 (Accepted truth) -> Premise 2 (Observed fact) -> Therefore... (Inevitable conclusion)",
      "confidence": 0.7,
      "description": "Build an airtight chain of logic where each premise leads inevitably to the conclusion"
    },
    {
      "to": 20,
      "from": 13,
      "name": "Cost Of Inaction",
      "slug": "27-cost-of-inaction",
      "bestFor": "Urgent budget requests, compliance, risk mitigation",
      "matchId": "f01e337f-a074-4bb0-a0a6-8afab8af6ed6",
      "evidence": "The document highlights the potential consequences of inaction in not leveraging technology for better patient outcomes",
      "position": 1,
      "objective": "The importance of harnessing technology to deliver better patient outcomes",
      "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
}