{
  "report_id": "theme_ai_enabled_biology_and_scientific_discovery",
  "report_type": "theme_signal",
  "site_path": "themes/ai-enabled-biology-and-scientific-discovery/index.html",
  "title": "AI-Enabled Biology And Scientific Discovery",
  "as_of": "2026-06-13",
  "generated_at": "2026-06-14T07:16:11Z",
  "categories": [
    "AI-enabled biology",
    "Scientific discovery",
    "Drug discovery",
    "Biotechnology",
    "Life Sciences Tools",
    "Artificial intelligence",
    "Clinical translation",
    "Funding-sensitive biotech",
    "Discovery-backed"
  ],
  "links": {
    "parents": [
      "themes_index"
    ],
    "related": [
      "reports_home",
      "themes_index",
      "theme_ai_enabled_biology_and_scientific_discovery_node_ai_ready_biology_data_and_omics",
      "theme_ai_enabled_biology_and_scientific_discovery_node_closed_loop_labs_and_instruments",
      "theme_ai_enabled_biology_and_scientific_discovery_node_computational_design_and_techbio_platforms",
      "theme_ai_enabled_biology_node_clinical_translation_and_evidence_rails",
      "theme_ai_enabled_biology_and_scientific_discovery_node_scientific_compute_and_foundation_models",
      "theme_ai_enabled_biology_node_pharma_buyers_and_data_owners",
      "theme_ai_biology_platform_validation",
      "theme_ai_capex_cycle",
      "theme_health_care_policy_reimbursement_dispersion",
      "theme_funding_dependency_and_duration_tolerance",
      "risk_selective_credit_broadening",
      "sector_health_care",
      "sector_information_technology",
      "portfolio_index"
    ],
    "backlinks": [
      "themes_index"
    ]
  },
  "discovery_sources": [
    {
      "kind": "report-api",
      "label": "AI-enabled biology parent node return buckets",
      "query_ref": "report-api:/api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets?as_of=latest;resolved_as_of:2026-06-12;source_table:reports.daily_security_return_buckets;windows:5/21/63/252 trading sessions;coverage:41/41;missing:none;note:PACB security row viable_daily=false"
    },
    {
      "kind": "report-api",
      "label": "Representative selected-security right-rail chart route",
      "query_ref": "report-api:/api/securities/RXRX/chart?frequency=daily&window=9m&as_of=latest;resolved_as_of:2026-06-12;source_table:discovery.daily_ohlc"
    },
    {
      "kind": "status",
      "label": "Representative local coverage checks inherited from prior metadata",
      "query_ref": "discovery:status:RXRX|ILMN|NVDA"
    }
  ],
  "knowledge_sources": [
    "../../../knowledge/wiki/concepts/themes/ai-biology-platform-validation.md",
    "../../../knowledge/wiki/concepts/themes/ai-capex-cycle.md",
    "../../../knowledge/wiki/concepts/themes/health-care-policy-reimbursement-dispersion.md",
    "../../../knowledge/wiki/concepts/themes/funding-dependency-and-duration-tolerance.md",
    "../../../knowledge/wiki/concepts/risks/selective-credit-broadening.md",
    "../../../knowledge/wiki/lanes/sector/health-care.md",
    "../../../knowledge/wiki/lanes/sector/information-technology.md",
    "../../../knowledge/wiki/lanes/security/ilmn.md",
    "../../../knowledge/wiki/lanes/security/tem.md",
    "../../../knowledge/wiki/lanes/security/ntra.md",
    "../../../knowledge/wiki/lanes/security/txg.md",
    "../../../knowledge/wiki/lanes/security/gh.md",
    "../../../knowledge/wiki/lanes/security/qgen.md",
    "../../../knowledge/wiki/lanes/security/pacb.md",
    "../../../knowledge/wiki/lanes/security/tmo.md",
    "../../../knowledge/wiki/lanes/security/a.md",
    "../../../knowledge/wiki/lanes/security/dhr.md",
    "../../../knowledge/wiki/lanes/security/wat.md",
    "../../../knowledge/wiki/lanes/security/brkr.md",
    "../../../knowledge/wiki/lanes/security/tech.md",
    "../../../knowledge/wiki/lanes/security/twst.md",
    "../../../knowledge/wiki/lanes/security/dna.md",
    "../../../knowledge/wiki/lanes/security/sdgr.md",
    "../../../knowledge/wiki/lanes/security/rxrx.md",
    "../../../knowledge/wiki/lanes/security/cert.md",
    "../../../knowledge/wiki/lanes/security/abcl.md",
    "../../../knowledge/wiki/lanes/security/rlay.md",
    "../../../knowledge/wiki/lanes/security/absi.md",
    "../../../knowledge/wiki/lanes/security/iqv.md",
    "../../../knowledge/wiki/lanes/security/veev.md",
    "../../../knowledge/wiki/lanes/security/medp.md",
    "../../../knowledge/wiki/lanes/security/iclr.md",
    "../../../knowledge/wiki/lanes/security/crl.md",
    "../../../knowledge/wiki/lanes/security/nvda.md",
    "../../../knowledge/wiki/lanes/security/googl.md",
    "../../../knowledge/wiki/lanes/security/msft.md",
    "../../../knowledge/wiki/lanes/security/amzn.md",
    "../../../knowledge/wiki/lanes/security/orcl.md",
    "../../../knowledge/wiki/lanes/security/amd.md",
    "../../../knowledge/wiki/lanes/security/avgo.md",
    "../../../knowledge/wiki/lanes/security/lly.md",
    "../../../knowledge/wiki/lanes/security/regn.md",
    "../../../knowledge/wiki/lanes/security/azn.md",
    "../../../knowledge/wiki/lanes/security/mrk.md",
    "../../../knowledge/wiki/lanes/security/pfe.md",
    "../../../knowledge/wiki/lanes/security/gild.md",
    "../../../knowledge/wiki/lanes/security/jnj.md",
    "../../../knowledge/wiki/lanes/security/incy.md"
  ],
  "value_chain_screen": {
    "method": "Local report API reads reports.daily_security_return_buckets and discovery.daily_ohlc. Latest close compared with closes 5, 21, 63, and 252 trading sessions earlier.",
    "minimum_daily_bars": 64,
    "price_data_as_of": "2026-06-12",
    "api_route": "/api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets?as_of=latest",
    "source_table": "reports.daily_security_return_buckets",
    "source_ohlc_table": "discovery.daily_ohlc",
    "coverage": {
      "total_tickers": 41,
      "week_covered": 41,
      "month_covered": 41,
      "quarter_covered": 41,
      "year_covered": 41,
      "missing_tickers": [],
      "stale_tickers": [],
      "coverage_notes": [
        "PACB is included in return windows but API security row flagged viable_daily=false."
      ]
    },
    "groups": [
      {
        "rank": 1,
        "name": "AI-Ready Biology Data And Omics",
        "slug": "ai-ready-biology-data-and-omics",
        "tickers": [
          "ILMN",
          "TEM",
          "NTRA",
          "TXG",
          "GH",
          "QGEN",
          "PACB"
        ],
        "total_tickers": 7,
        "week_covered": 7,
        "month_covered": 7,
        "quarter_covered": 7,
        "year_covered": 7,
        "weekly_5d": {
          "sessions": 5,
          "average_pct": -1.4664,
          "median_pct": -0.8317
        },
        "monthly_21d": {
          "sessions": 21,
          "average_pct": 15.8282,
          "median_pct": 11.0138
        },
        "quarterly_63d": {
          "sessions": 63,
          "average_pct": 20.1616,
          "median_pct": 12.8933
        },
        "yearly_252d": {
          "sessions": 252,
          "average_pct": 58.1213,
          "median_pct": 27.1708
        }
      },
      {
        "rank": 2,
        "name": "Closed-Loop Labs And Instruments",
        "slug": "closed-loop-labs-and-instruments",
        "tickers": [
          "TMO",
          "A",
          "DHR",
          "WAT",
          "BRKR",
          "TECH",
          "TWST",
          "DNA"
        ],
        "total_tickers": 8,
        "week_covered": 8,
        "month_covered": 8,
        "quarter_covered": 8,
        "year_covered": 8,
        "weekly_5d": {
          "sessions": 5,
          "average_pct": -0.4718,
          "median_pct": -2.4847
        },
        "monthly_21d": {
          "sessions": 21,
          "average_pct": 13.8632,
          "median_pct": 11.8341
        },
        "quarterly_63d": {
          "sessions": 63,
          "average_pct": 24.5771,
          "median_pct": 16.2337
        },
        "yearly_252d": {
          "sessions": 252,
          "average_pct": 18.8622,
          "median_pct": 6.613
        }
      },
      {
        "rank": 3,
        "name": "Computational Design And TechBio Platforms",
        "slug": "computational-design-and-techbio-platforms",
        "tickers": [
          "SDGR",
          "RXRX",
          "CERT",
          "ABCL",
          "RLAY",
          "ABSI"
        ],
        "total_tickers": 6,
        "week_covered": 6,
        "month_covered": 6,
        "quarter_covered": 6,
        "year_covered": 6,
        "weekly_5d": {
          "sessions": 5,
          "average_pct": 0.2289,
          "median_pct": -1.3395
        },
        "monthly_21d": {
          "sessions": 21,
          "average_pct": 12.559,
          "median_pct": 10.9402
        },
        "quarterly_63d": {
          "sessions": 63,
          "average_pct": 43.904,
          "median_pct": 29.2306
        },
        "yearly_252d": {
          "sessions": 252,
          "average_pct": 64.4537,
          "median_pct": 10.2812
        }
      },
      {
        "rank": 4,
        "name": "Clinical Translation And Evidence Rails",
        "slug": "clinical-translation-and-evidence-rails",
        "tickers": [
          "IQV",
          "VEEV",
          "MEDP",
          "ICLR",
          "CERT",
          "TEM",
          "CRL"
        ],
        "total_tickers": 7,
        "week_covered": 7,
        "month_covered": 7,
        "quarter_covered": 7,
        "year_covered": 7,
        "weekly_5d": {
          "sessions": 5,
          "average_pct": -0.6761,
          "median_pct": -1.0848
        },
        "monthly_21d": {
          "sessions": 21,
          "average_pct": 10.0599,
          "median_pct": 8.5595
        },
        "quarterly_63d": {
          "sessions": 63,
          "average_pct": 6.6089,
          "median_pct": 3.7588
        },
        "yearly_252d": {
          "sessions": 252,
          "average_pct": -5.8699,
          "median_pct": 0.4397
        }
      },
      {
        "rank": 5,
        "name": "Scientific Compute And Foundation Models",
        "slug": "scientific-compute-and-foundation-models",
        "tickers": [
          "NVDA",
          "GOOGL",
          "MSFT",
          "AMZN",
          "ORCL",
          "AMD",
          "AVGO"
        ],
        "total_tickers": 7,
        "week_covered": 7,
        "month_covered": 7,
        "quarter_covered": 7,
        "year_covered": 7,
        "weekly_5d": {
          "sessions": 5,
          "average_pct": -2.3871,
          "median_pct": -2.4014
        },
        "monthly_21d": {
          "sessions": 21,
          "average_pct": -4.5047,
          "median_pct": -8.3303
        },
        "quarterly_63d": {
          "sessions": 63,
          "average_pct": 35.4732,
          "median_pct": 18.5963
        },
        "yearly_252d": {
          "sessions": 252,
          "average_pct": 74.1134,
          "median_pct": 43.6603
        }
      },
      {
        "rank": 6,
        "name": "Pharma Buyers And Data Owners",
        "slug": "pharma-buyers-and-data-owners",
        "tickers": [
          "LLY",
          "REGN",
          "AZN",
          "MRK",
          "PFE",
          "GILD",
          "JNJ",
          "INCY"
        ],
        "total_tickers": 8,
        "week_covered": 8,
        "month_covered": 8,
        "quarter_covered": 8,
        "year_covered": 8,
        "weekly_5d": {
          "sessions": 5,
          "average_pct": -0.1832,
          "median_pct": -0.6504
        },
        "monthly_21d": {
          "sessions": 21,
          "average_pct": 0.8065,
          "median_pct": 2.7491
        },
        "quarterly_63d": {
          "sessions": 63,
          "average_pct": -0.4451,
          "median_pct": -0.8306
        },
        "yearly_252d": {
          "sessions": 252,
          "average_pct": 47.9403,
          "median_pct": 44.1683
        }
      }
    ],
    "missing_or_text_only": [
      "EXAI",
      "2228.HK",
      "3696.HK",
      "NVO",
      "NVS",
      "SNY",
      "GSK",
      "RHHBY",
      "BNTX",
      "MRNA",
      "SOPH",
      "LTRN",
      "SEER",
      "QSI",
      "NAUT",
      "RELX",
      "WLY",
      "CLVT"
    ]
  },
  "ticker_basket": [
    "A",
    "ABCL",
    "ABSI",
    "AMD",
    "AMZN",
    "AVGO",
    "AZN",
    "BRKR",
    "CERT",
    "CRL",
    "DHR",
    "DNA",
    "GH",
    "GILD",
    "GOOGL",
    "ICLR",
    "ILMN",
    "INCY",
    "IQV",
    "JNJ",
    "LLY",
    "MEDP",
    "MRK",
    "MSFT",
    "NTRA",
    "NVDA",
    "ORCL",
    "PACB",
    "PFE",
    "QGEN",
    "REGN",
    "RLAY",
    "RXRX",
    "SDGR",
    "TECH",
    "TEM",
    "TMO",
    "TWST",
    "TXG",
    "VEEV",
    "WAT"
  ],
  "freshness": {
    "price_data_as_of": "2026-06-12",
    "knowledge_reviewed_as_of": "2026-06-13",
    "web_research_as_of": "2026-06-13",
    "daily_chart_horizon": "9M",
    "weekly_chart_horizon": "3Y",
    "canonical_knowledge_route": "../../../knowledge/wiki/concepts/themes/ai-biology-platform-validation.md",
    "api_required": true,
    "runtime_price_data": "Resolved by local report API at request time; parent API validation resolved to 2026-06-12 on 2026-06-14.",
    "chartable_names": 41,
    "selected_security_chart_source": "/api/securities/{ticker}/chart?frequency=daily&window=9m&as_of=latest",
    "theme_return_source": "/api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets?as_of=latest"
  },
  "revision": {
    "updated_label": "Parent theme format refresh with mental model, ranked value-chain cards, evidence board, source trail, and API provenance",
    "metadata_path": "themes/ai-enabled-biology-and-scientific-discovery/report.json",
    "version": 3,
    "metadata_coordinator": true,
    "metadata_coordinator_as_of": "2026-06-14"
  },
  "value_chain_nodes": [
    {
      "id": "theme_ai_enabled_biology_and_scientific_discovery_node_ai_ready_biology_data_and_omics",
      "title": "AI-Ready Biology Data And Omics",
      "slug": "ai-ready-biology-data-and-omics",
      "site_path": "themes/ai-enabled-biology-and-scientific-discovery/nodes/ai-ready-biology-data-and-omics/index.html",
      "level": "L3 core underwriting node",
      "tickers": [
        "ILMN",
        "TEM",
        "NTRA",
        "TXG",
        "GH",
        "QGEN",
        "PACB"
      ],
      "chart_count": 7,
      "ticker_basket": [
        "ILMN",
        "TEM",
        "NTRA",
        "TXG",
        "GH",
        "QGEN",
        "PACB"
      ],
      "chart_tickers": [
        "ILMN",
        "TEM",
        "NTRA",
        "TXG",
        "GH",
        "QGEN",
        "PACB"
      ],
      "runtime_market_data": "API-required: /api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets and /api/securities/{ticker}/chart",
      "role": "Turns biological samples into model-ready sequencing, single-cell, spatial, molecular diagnostic, clinical-genomic, and long-read datasets.",
      "description": "This page covers the data layer that turns blood, tissue, cells, genomes, proteins, and clinical records into machine-readable biology. Revenue converts when customers buy instruments, run consumables, pay for tests, license data, renew workflow products, or use validated datasets in drug discovery and clinical programs.",
      "core_count": 4,
      "option_count": 2,
      "watch_count": 1,
      "price_data_as_of": "2026-06-12",
      "status": "active",
      "parent_rank": 1,
      "parent_rank_basis": "Ranked by biology bottleneck importance, economic conversion, evidence quality, investability, and watchability; not ranked by recent price return."
    },
    {
      "id": "theme_ai_enabled_biology_and_scientific_discovery_node_closed_loop_labs_and_instruments",
      "title": "Closed-Loop Labs And Instruments",
      "slug": "closed-loop-labs-and-instruments",
      "site_path": "themes/ai-enabled-biology-and-scientific-discovery/nodes/closed-loop-labs-and-instruments/index.html",
      "level": "L2 wet-lab execution node",
      "tickers": [
        "TMO",
        "A",
        "DHR",
        "WAT",
        "BRKR",
        "TECH",
        "TWST",
        "DNA"
      ],
      "chart_count": 8,
      "ticker_basket": [
        "TMO",
        "A",
        "DHR",
        "WAT",
        "BRKR",
        "TECH",
        "TWST",
        "DNA"
      ],
      "chart_tickers": [
        "TMO",
        "A",
        "DHR",
        "WAT",
        "BRKR",
        "TECH",
        "TWST",
        "DNA"
      ],
      "runtime_market_data": "API-required: /api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets and /api/securities/{ticker}/chart",
      "role": "Turns AI-generated hypotheses into physical experiments, lab measurements, and feedback data.",
      "description": "This page covers the lab execution layer that turns model predictions into physical experiments and new training data. Companies get paid through instrument placements, service contracts, software and informatics, consumables, reagents, synthetic DNA, assay volume, and outsourced lab capacity.",
      "core_count": 7,
      "option_count": 0,
      "watch_count": 1,
      "price_data_as_of": "2026-06-12",
      "status": "active",
      "parent_rank": 2,
      "parent_rank_basis": "Ranked by biology bottleneck importance, economic conversion, evidence quality, investability, and watchability; not ranked by recent price return."
    },
    {
      "id": "theme_ai_enabled_biology_and_scientific_discovery_node_computational_design_and_techbio_platforms",
      "title": "Computational Design And TechBio Platforms",
      "slug": "computational-design-and-techbio-platforms",
      "site_path": "themes/ai-enabled-biology-and-scientific-discovery/nodes/computational-design-and-techbio-platforms/index.html",
      "level": "L3 high-purity platform node",
      "tickers": [
        "SDGR",
        "RXRX",
        "CERT",
        "ABCL",
        "RLAY",
        "ABSI"
      ],
      "chart_count": 6,
      "ticker_basket": [
        "SDGR",
        "RXRX",
        "CERT",
        "ABCL",
        "RLAY",
        "ABSI"
      ],
      "chart_tickers": [
        "SDGR",
        "RXRX",
        "CERT",
        "ABCL",
        "RLAY",
        "ABSI"
      ],
      "runtime_market_data": "API-required: /api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets and /api/securities/{ticker}/chart",
      "role": "Turns computational chemistry, AI biology, biosimulation, antibody design, and owned discovery programs into paid workflow evidence, partner cash, milestones, royalties, or clinical assets.",
      "description": "This page covers public computational design and TechBio companies whose value depends on software adoption, partner acceptance, model-informed development workflows, or platform-originated human evidence. Revenue converts through ACV, collaboration revenue, upfronts, milestones, option exercises, royalties, services, adjusted EBITDA, or owned-pipeline economics.",
      "core_count": 6,
      "option_count": 0,
      "watch_count": 0,
      "price_data_as_of": "2026-06-12",
      "status": "active",
      "parent_rank": 3,
      "parent_rank_basis": "Ranked by biology bottleneck importance, economic conversion, evidence quality, investability, and watchability; not ranked by recent price return."
    },
    {
      "id": "theme_ai_enabled_biology_and_scientific_discovery_node_clinical_translation_and_evidence_rails",
      "title": "Clinical Translation And Evidence Rails",
      "slug": "clinical-translation-and-evidence-rails",
      "site_path": "themes/ai-enabled-biology-and-scientific-discovery/nodes/clinical-translation-and-evidence-rails/index.html",
      "level": "L3 clinical evidence node",
      "tickers": [
        "IQV",
        "VEEV",
        "MEDP",
        "ICLR",
        "CERT",
        "TEM",
        "CRL"
      ],
      "chart_count": 7,
      "ticker_basket": [
        "IQV",
        "VEEV",
        "MEDP",
        "ICLR",
        "CERT",
        "TEM",
        "CRL"
      ],
      "chart_tickers": [
        "IQV",
        "VEEV",
        "MEDP",
        "ICLR",
        "CERT",
        "TEM",
        "CRL"
      ],
      "runtime_market_data": "API-required: /api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets and /api/securities/{ticker}/chart",
      "role": "Turns AI-enabled discovery output into trials, regulated data, model credibility, safety evidence, real-world evidence, and submission workflows.",
      "description": "Clinical translation and evidence rails are the contract research organizations, regulated software systems, biosimulation platforms, real-world-data vendors, diagnostics data assets, and safety workflows that turn an AI-generated biology idea into trial evidence a sponsor, physician, payer, or regulator can inspect. Sponsors pay through clinical study contracts, software subscriptions, data licenses, diagnostic testing, and model-informed development work. The current basket read is that IQV and VEEV have the broadest source-backed clinical and workflow exposure; MEDP and ICLR are the main trial-execution checks; CERT and TEM add specialized model-informed and clinical-genomic evidence; CRL is useful but more upstream and currently has weaker organic evidence.",
      "core_count": 7,
      "option_count": 0,
      "watch_count": 0,
      "price_data_as_of": "2026-06-12",
      "status": "active",
      "parent_rank": 4,
      "parent_rank_basis": "Ranked by biology bottleneck importance, economic conversion, evidence quality, investability, and watchability; not ranked by recent price return."
    },
    {
      "id": "theme_ai_enabled_biology_and_scientific_discovery_node_scientific_compute_and_foundation_models",
      "title": "Scientific Compute And Foundation Models",
      "slug": "scientific-compute-and-foundation-models",
      "site_path": "themes/ai-enabled-biology-and-scientific-discovery/nodes/scientific-compute-and-foundation-models/index.html",
      "level": "L2 infrastructure and model platform node",
      "tickers": [
        "NVDA",
        "GOOGL",
        "MSFT",
        "AMZN",
        "ORCL",
        "AMD",
        "AVGO"
      ],
      "chart_count": 7,
      "ticker_basket": [
        "NVDA",
        "GOOGL",
        "MSFT",
        "AMZN",
        "ORCL",
        "AMD",
        "AVGO"
      ],
      "chart_tickers": [
        "NVDA",
        "GOOGL",
        "MSFT",
        "AMZN",
        "ORCL",
        "AMD",
        "AVGO"
      ],
      "runtime_market_data": "API-required: /api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets and /api/securities/{ticker}/chart",
      "role": "Runs protein, chemistry, genomics, simulation, and agentic lab workflows through compute, cloud, model, and enterprise R&D infrastructure.",
      "description": "This page covers the scientific compute and foundation-model layer that lets researchers train, host, and use large biological models. The stack includes GPU and accelerator servers, cloud high-performance computing, custom silicon, model APIs, managed omics workflows, scientific databases, and enterprise research tools.",
      "core_count": 7,
      "option_count": 0,
      "watch_count": 0,
      "price_data_as_of": "2026-06-12",
      "status": "active",
      "parent_rank": 5,
      "parent_rank_basis": "Ranked by biology bottleneck importance, economic conversion, evidence quality, investability, and watchability; not ranked by recent price return."
    },
    {
      "id": "theme_ai_enabled_biology_and_scientific_discovery_node_pharma_buyers_and_data_owners",
      "title": "Pharma Buyers And Data Owners",
      "slug": "pharma-buyers-and-data-owners",
      "site_path": "themes/ai-enabled-biology-and-scientific-discovery/nodes/pharma-buyers-and-data-owners/index.html",
      "level": "L2 final-IP and data-owner node",
      "tickers": [
        "LLY",
        "REGN",
        "AZN",
        "MRK",
        "PFE",
        "GILD",
        "JNJ",
        "INCY"
      ],
      "chart_count": 8,
      "ticker_basket": [
        "LLY",
        "REGN",
        "AZN",
        "MRK",
        "PFE",
        "GILD",
        "JNJ",
        "INCY"
      ],
      "chart_tickers": [
        "LLY",
        "REGN",
        "AZN",
        "MRK",
        "PFE",
        "GILD",
        "JNJ",
        "INCY"
      ],
      "runtime_market_data": "API-required: /api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets and /api/securities/{ticker}/chart",
      "role": "Maps large drug developers that supply budgets, proprietary data, clinical execution, and final commercial ownership for AI-enabled biology.",
      "description": "Pharma buyers and data owners are drug developers that pay for AI-enabled discovery, supply proprietary biology or clinical data, run regulated trials, and own the final commercial drug rights. This node ranks the companies where AI can matter only if it changes target selection, molecule design, biomarker work, trial design, or pipeline capital allocation enough to improve revenue, margin, cash flow, or replacement-asset durability.",
      "core_count": 8,
      "option_count": 0,
      "watch_count": 0,
      "price_data_as_of": "2026-06-12",
      "status": "active",
      "parent_rank": 6,
      "parent_rank_basis": "Ranked by biology bottleneck importance, economic conversion, evidence quality, investability, and watchability; not ranked by recent price return."
    }
  ],
  "runtime_market_data": {
    "required": true,
    "theme_return_endpoint": "/api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets?as_of=latest",
    "security_chart_endpoint": "/api/securities/{ticker}/chart?frequency=daily&window=9m&as_of=latest",
    "return_source_table": "reports.daily_security_return_buckets",
    "chart_source": "report API security chart endpoint backed by discovery.daily_ohlc",
    "validated_routes": [
      "/api/themes/ai-enabled-biology-and-scientific-discovery/node-return-buckets?as_of=latest",
      "/api/securities/RXRX/chart?frequency=daily&window=9m&as_of=latest"
    ],
    "validated_as_of": "2026-06-12",
    "failure_mode": "Node card return grids and right-rail selected-security charts show API-unavailable states when the local report API is not running."
  }
}
