OnCo

Data dictionary

The corpus is a graph of typed records validated on every build. This page is generated from the schema itself: the base fields every record shares, then each of the eighteen kinds with its own fields and a real example. Relationship fields hold ids of other records; backlinks are derived, so a link is declared once.

Where the schema lives

Source of truth: src/lib/schema.ts (Zod). Machine-readable JSON Schema: /api/v1/schema.json, published with the open API. Ids match ^[a-z0-9]+(-[a-z0-9]+)*$; dates are YYYY-MM-DD.

Base fields (every kind)

Identity, the two-register text (TL;DR for anyone, summary for specialists), the date the facts were checked, sources, and the relationship arrays that make the graph.

FieldTypeRequiredDescription
identity idyesStable kebab-case identifier; also the URL slug.
namestringyesDisplay name.
akastring[]
default []
noOther names, brands and abbreviations; used by search and hover-linking.
tldrstringyesPlain-language explanation for someone with no background.
summarystringyesTechnical summary. Markdown-light: paragraphs separated by blank lines.
status"approved" | "phase-3" | "phase-2" | "phase-1" | "preclinical" | "concept" | "standard-of-care" | "established" | "emerging" | "historic" | "withdrawn" | "active" | "completed" | "recruiting" | "positive" | "negative" | "mixed" | "planned"noStage or state, from the shared status list.
asOfdate (YYYY-MM-DD)yesDate the facts were last checked.
wikipediaURLnoWikipedia article for the concept.
links{ label, url }[]
default []
noExternal sources: label and URL.
  • label: string
  • url: URL
tagsstring[]
default []
noFree-form tags (for example "spike", "failure").
relatedentity id[]
default []
noFree-form related entity ids (any kind).
cancersentity id[]
default []
noTyped relationship arrays. Each holds ids of the named kind.
sectionsentity id[]
default []
no
technologiesentity id[]
default []
no
targetsentity id[]
default []
no
drugsentity id[]
default []
no
companiesentity id[]
default []
no
institutionsentity id[]
default []
no
pathwaysentity id[]
default []
no
termsentity id[]
default []
no
trialsentity id[]
default []
no
peopleentity id[]
default []
no
bottlenecksentity id[]
default []
noBottlenecks of the war on cancer this object bears on (ideas attack them; technologies, trials, collections relieve them).
keyPapersentity id[]
default []
noKey papers (kind "paper") this object rests on or is discussed in.
journalsentity id[]
default []
noJournals (kind "journal") this object was published in or is tied to.
notesstring[]
default []
noWhy this matters / what is hard about it. Optional editorial notes.
simplestringnoEven simpler explanation (about a 12-year-old reading age). Optional.
provenance{ editedBy, editedOn, note }noWho last substantively edited this record (name or handle) and when.
  • editedBy: string
  • editedOn: date (YYYY-MM-DD)
  • note: string (optional)
confidence{ probability, by, on, note }noNamed probability estimate for speculative content.
  • probability: [number, number]
  • by: string
  • on: date (YYYY-MM-DD)
  • note: string (optional)

Cancer

Cancer64 cancers

One page per disease: state of the art, history, and what is coming.

FieldTypeRequiredDescription
kind"cancer"yesDiscriminator; fixed per kind.
groupstringyesICD-O / organ system grouping, e.g. "breast", "lung", "blood".
burdenstringnoRoughly how common, in words.
subtypesstring[]
default []
noNamed subtypes a clinician distinguishes.
biomarkersstring[]
default []
noKey biomarkers a clinician tests for.
standardOfCare{ setting, approach, refs, guideline }[]
default []
noOne row per clinical setting: the approach, the products it references, and the guideline mapping.
  • setting: string
  • approach: string
  • refs: entity id[] (optional)
  • guideline: { nccn, esmoMcbs, version, url } (optional)
stateOfArtstring[]
default []
noWhat is state of the art today, in one paragraph per point.
history{ year, title, note, refs }[]
default []
noDated milestones for the timeline, each pointing at the records it concerns.
  • year: integer | string
  • title: string
  • note: string (optional)
  • refs: entity id[] (optional)
pipelineentity id[]
default []
noWhat is coming: ids of drugs/technologies/trials/ideas.
openProblemsstring[]
default []
noWhat is still unsolved, one paragraph each.
Example: nsclc (arrays trimmed to three items, long strings shortened)
{
  "id": "nsclc",
  "kind": "cancer",
  "name": "Non-small-cell lung cancer",
  "tldr": "Non-small-cell lung cancer is the biggest cancer killer, and the proving ground for precision medicine: a dozen targetable mutations, immunotherapy for the r...",
  "summary": "Non-small-cell lung cancer is ~85% of lung cancer and the leading cause of cancer death worldwide (~1.8 million deaths a year, all lung cancer). Adenocarcino...",
  "asOf": "2026-09-06",
  "wikipedia": "https://en.wikipedia.org/wiki/Non-small-cell_lung_cancer",
  "tags": [
    "lung",
    "spike"
  ],
  "related": [
    "kras-roadmap",
    "adc-generations",
    "immunotherapy-roadmap"
  ],
  "technologies": [
    "kinase-inhibitors",
    "checkpoint-inhibitor",
    "adc"
  ],
  "targets": [
    "egfr",
    "alk",
    "kras"
  ],
  "companies": [
    "astrazeneca",
    "johnson-johnson",
    "pfizer"
  ],
  "pathways": [
    "ras-mapk",
    "pi3k-akt-mtor",
    "pd1-checkpoint"
  ],
  "terms": [
    "tps",
    "egfr-exon19-l858r",
    "egfr-exon20-insertion"
  ],
  "group": "lung",
  "burden": "~85% of lung cancer; lung cancer kills ~1.8 million people a year, more than any other cancer.",
  "subtypes": [
    "Adenocarcinoma",
    "Squamous",
    "EGFR-mutant"
  ],
  "biomarkers": [
    "EGFR",
    "ALK",
    "ROS1"
  ],
  "standardOfCare": [
    {
      "setting": "Screening",
      "approach": "Annual low-dose CT for high-risk smokers (NLST, NELSON); AI nodule scoring emerging.",
      "refs": [
        "ct",
        "radiology-ai-screening"
      ],
      "guideline": {
        "version": "NCCN Guidelines: Non-Small Cell Lung Cancer",
        "url": "https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1450"
      }
    },
    {
      "setting": "Early stage",
      "approach": "Surgery or SBRT; perioperative chemo-immunotherapy; adjuvant osimertinib (EGFR) or alectinib (ALK).",
      "refs": [
        "sbrt",
        "adaura",
        "osimertinib"
      ],
      "guideline": {
        "version": "NCCN Guidelines: Non-Small Cell Lung Cancer",
        "url": "https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1450"
      }
    },
    {
      "setting": "Stage III unresectable",
      "approach": "Chemoradiation → durvalumab (PACIFIC) or osimertinib (LAURA, EGFR).",
      "refs": [
        "durvalumab",
        "imrt-igrt"
      ],
      "guideline": {
        "version": "NCCN Guidelines: Non-Small Cell Lung Cancer",
        "url": "https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1450"
      }
    }
  ],
  "stateOfArt": [
    "5-year PFS 60% with lorlatinib in ALK+ disease.",
    "Adjuvant osimertinib halves death risk.",
    "First regimen to beat osimertinib (MARIPOSA) and first to beat pembrolizumab (ivonescimab, China)."
  ],
  "history": [
    {
      "year": 2002,
      "title": "Gefitinib approved; dramatic responses in a minority",
      "refs": []
    },
    {
      "year": 2004,
      "title": "EGFR mutations explain gefitinib responses",
      "refs": []
    },
    {
      "year": 2004,
      "title": "EGFR mutations explain gefitinib responses",
      "note": "Lynch, Paez, and Pao identify activating EGFR mutations; the birth of lung cancer precision medicine.",
      "refs": [
        "egfr",
        "egfr-exon19-l858r"
      ]
    }
  ],
  "pipeline": [
    "ivonescimab",
    "izalontamab-brengitecan",
    "sacituzumab-tirumotecan"
  ],
  "openProblems": [
    "Resistance to every TKI.",
    "Squamous histology has few targets.",
    "Screening uptake below 20% in the US."
  ]
}

Front

Front19 fronts

The fronts of the war on cancer: from imaging and early detection to ADCs, radiopharma, and cell therapy.

FieldTypeRequiredDescription
kind"section"yesDiscriminator; fixed per kind.
orderintegeryesPosition of the front in the navigation.
iconstringnoIcon id for the front.
Example: ai-computation (arrays trimmed to three items, long strings shortened)
{
  "id": "ai-computation",
  "kind": "section",
  "name": "AI & Computation",
  "tldr": "Software that reads scans and slides, predicts outcomes, designs drugs, and matches patients to trials.",
  "summary": "FDA-cleared digital pathology risk tools (ArteraAI), radiology triage and screening models, pathology and radiology foundation models, multimodal patient-lev...",
  "asOf": "2026-09-04",
  "order": 15,
  "icon": "chip"
}

Technology

Technology348 technologies

Every way we see, measure, or attack a tumour, explained.

FieldTypeRequiredDescription
kind"technology"yesDiscriminator; fixed per kind.
principlestringyesHow it works, for a technical reader.
generationstringnoWhich generation of the idea this is, if the field talks in generations.
strengthsstring[]
default []
noWhat it does well.
limitationsstring[]
default []
noWhere it falls short.
sinceinteger | stringnoYear first used in humans or first approved, if meaningful.
Example: checkpoint-inhibitor (arrays trimmed to three items, long strings shortened)
{
  "id": "checkpoint-inhibitor",
  "kind": "technology",
  "name": "Immune checkpoint inhibitors",
  "tldr": "Antibodies that release the brakes on immune cells so they can attack the cancer. They cure a minority of patients across many cancers, something chemotherap...",
  "summary": "Anti-CTLA-4 (ipilimumab), anti-PD-1 (pembrolizumab, nivolumab, cemiplimab, dostarlimab, toripalimab, tislelizumab), anti-PD-L1 (atezolizumab, durvalumab, ave...",
  "status": "standard-of-care",
  "asOf": "2026-09-04",
  "wikipedia": "https://en.wikipedia.org/wiki/Checkpoint_inhibitor",
  "sections": [
    "immunotherapy"
  ],
  "targets": [
    "pd1",
    "pdl1",
    "ctla4"
  ],
  "drugs": [
    "pembrolizumab",
    "nivolumab",
    "ipilimumab"
  ],
  "terms": [
    "cps",
    "tmb",
    "msi"
  ],
  "principle": "Blocking inhibitory receptor-ligand interactions restores T-cell priming (CTLA-4) and effector function (PD-1).",
  "strengths": [
    "Durable, sometimes curative responses",
    "Broad applicability"
  ],
  "limitations": [
    "Most patients do not respond",
    "Autoimmune toxicity",
    "Biomarkers are imperfect"
  ],
  "since": 2011
}

Target

Target92 targets

The molecules drugs and tracers aim at.

FieldTypeRequiredDescription
kind"target"yesDiscriminator; fixed per kind.
symbolstringnoGene symbol / protein name.
biologystringyesWhat the target does in normal and cancer cells.
whereFoundstring[]
default []
noExpression or alteration by cancer, free text.
targetClass"surface-antigen" | "kinase" | "checkpoint" | "nuclear-receptor" | "enzyme" | "transcription" | "oncogene" | "tumor-suppressor" | "stroma" | "other"
default "other"
noBroad class used for filtering.
prevalence{ cancerId, pct, measure, source, note }[]
default []
noFraction of each cancer that expresses or carries the alteration, sourced. `pct` is 0-100 or a range string like "15-20".
  • cancerId: entity id
  • pct: number | string
  • measure: string (optional)
  • source: URL (optional)
  • note: string (optional)
Example: pd1 (arrays trimmed to three items, long strings shortened)
{
  "id": "pd1",
  "kind": "target",
  "name": "PD-1",
  "tldr": "PD-1 is a brake on T cells. Blocking it releases the immune system against the tumour and has cured some previously incurable cancers.",
  "summary": "PD-1 blockade (pembrolizumab, nivolumab, cemiplimab, dostarlimab and a growing list of biosimilar-adjacent agents) is standard across melanoma, NSCLC, RCC, u...",
  "asOf": "2026-09-04",
  "wikipedia": "https://en.wikipedia.org/wiki/Programmed_cell_death_protein_1",
  "tags": [
    "checkpoint"
  ],
  "cancers": [
    "melanoma",
    "nsclc",
    "rcc"
  ],
  "pathways": [
    "pd1-checkpoint"
  ],
  "symbol": "PDCD1",
  "biology": "Inhibitory receptor on activated T cells; ligands PD-L1/PD-L2. Tumour PD-L1 expression, TMB, and MSI predict response imperfectly.",
  "whereFound": [
    "Exhausted T cells in the tumour microenvironment"
  ],
  "targetClass": "checkpoint",
  "prevalence": [
    {
      "cancerId": "melanoma",
      "pct": "30-40",
      "measure": "Objective response to PD-1 monotherapy (proxy)",
      "source": "https://en.wikipedia.org/wiki/Programmed_cell_death_protein_1",
      "note": "Not an expression prevalence"
    },
    {
      "cancerId": "nsclc",
      "pct": "20-45",
      "measure": "Response by PD-L1 stratum (proxy)",
      "source": "https://en.wikipedia.org/wiki/Programmed_cell_death_protein_1"
    }
  ]
}

Product

Product377 drugs

Approved and pipeline products, with what they hit and who makes them.

FieldTypeRequiredDescription
kind"drug"yesDiscriminator; fixed per kind.
brandstringnoBrand name where marketed.
codestringnoDevelopment code(s), comma separated.
modalitystringyesModality, e.g. "ADC", "small molecule", "mAb", "radioligand", "cell therapy", "vaccine", "device".
payloadstringnoCytotoxic payload, for ADCs.
linkerstringnoLinker chemistry, for ADCs.
mechanismstringyesOne or two sentences on how it works.
approvals{ region, year, indication, note }[]
default []
noRegulatory approvals: region, year, indication.
  • region: string
  • year: integer
  • indication: string
  • note: string (optional)
mechanismStepsstring[]
default []
noStep-by-step mechanism for the animated mechanism card.
dosing{ route, schedule, modifications, monitoring, source }noRoute, schedule, modifications and monitoring, from the label.
  • route: string
  • schedule: string
  • modifications: string (optional)
  • monitoring: string (optional)
  • source: URL (optional)
toxicity{ event, anyGradePct, grade3PlusPct, source, note }[]
default []
noAdverse events with rates in percent, from the label or pivotal trial.
  • event: string
  • anyGradePct: number (optional)
  • grade3PlusPct: number (optional)
  • source: URL (optional)
  • note: string (optional)
access{ country, listPrice, reimbursement, assistance, generic, source, asOf }[]
default []
noCost and access by country.
  • country: string
  • listPrice: string (optional)
  • reimbursement: string (optional)
  • assistance: string (optional)
  • generic: boolean (optional)
  • source: URL (optional)
  • asOf: date (YYYY-MM-DD) (optional)
regulatoryEvents{ date, type, region, note, source }[]
default []
noDated designations, filings, decisions and label changes.
  • date: string
  • type: "designation" | "filing" | "pdufa" | "approval" | "crl" | "withdrawal" | "label-change" | "advisory-committee"
  • region: string
  • note: string
  • source: URL (optional)
Example: pembrolizumab (arrays trimmed to three items, long strings shortened)
{
  "id": "pembrolizumab",
  "kind": "drug",
  "name": "Pembrolizumab",
  "tldr": "The most widely used cancer immunotherapy, approved in more than 40 settings, including before and after surgery for triple-negative breast cancer.",
  "summary": "Approvals span melanoma, NSCLC, head and neck, Hodgkin, urothelial, MSI-H/dMMR tumours (first tumour-agnostic approval, 2017), gastric, oesophageal, cervical...",
  "status": "approved",
  "asOf": "2026-09-04",
  "wikipedia": "https://en.wikipedia.org/wiki/Pembrolizumab",
  "cancers": [
    "tnbc",
    "nsclc",
    "melanoma"
  ],
  "technologies": [
    "checkpoint-inhibitor"
  ],
  "targets": [
    "pd1"
  ],
  "companies": [
    "merck"
  ],
  "trials": [
    "keynote-522",
    "keynote-355",
    "ascent-04"
  ],
  "brand": "Keytruda / Keytruda Qlex (SC)",
  "modality": "Monoclonal antibody (anti-PD-1)",
  "mechanism": "Humanised IgG4 blocking PD-1; restores T-cell effector function.",
  "approvals": [
    {
      "region": "US",
      "year": 2014,
      "indication": "Melanoma (first of >40 indications)"
    },
    {
      "region": "US",
      "year": 2017,
      "indication": "MSI-H/dMMR solid tumours (tumour-agnostic)"
    },
    {
      "region": "US",
      "year": 2020,
      "indication": "Metastatic TNBC, PD-L1 CPS ≥10, with chemotherapy"
    }
  ],
  "mechanismSteps": [
    "Antibody binds PD-1 on T cells",
    "PD-1/PD-L1 engagement between T cell and tumour is blocked",
    "Exhausted tumour-reactive T cells regain effector function"
  ],
  "dosing": {
    "route": "IV infusion over 30 min (subcutaneous Keytruda Qlex available)",
    "schedule": "200 mg every 3 weeks or 400 mg every 6 weeks; paediatric 2 mg/kg (max 200 mg) every 3 weeks; up to 24 months in most metastatic settings",
    "modifications": "Hold for grade 2 immune-mediated events; permanently discontinue for grade 4 or recurrent grade 3",
    "monitoring": "Thyroid function, LFTs, creatinine, glucose at baseline and periodically; patient education on immune-related symptoms",
    "source": "https://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=9333c79b-d487-4538-a9f0-71b91a02b287"
  },
  "toxicity": [
    {
      "event": "Hypothyroidism (immune-mediated)",
      "anyGradePct": 8,
      "source": "https://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=9333c79b-d487-4538-a9f0-71b91a02b287",
      "note": "Pooled monotherapy data, >2,800 patients"
    },
    {
      "event": "Pneumonitis (immune-mediated)",
      "anyGradePct": 3.4,
      "source": "https://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=9333c79b-d487-4538-a9f0-71b91a02b287",
      "note": "Pooled monotherapy data, >2,800 patients"
    },
    {
      "event": "Colitis (immune-mediated)",
      "anyGradePct": 1.7,
      "source": "https://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=9333c79b-d487-4538-a9f0-71b91a02b287",
      "note": "Pooled monotherapy data, >2,800 patients"
    }
  ],
  "access": [
    {
      "country": "US",
      "listPrice": "$11,564 per 200 mg dose (WAC, Merck price disclosure 2024)",
      "reimbursement": "Medicare Part B (physician-administered); commercial plans per formulary",
      "assistance": "https://www.merckaccessprogram-keytruda.com",
      "source": "https://www.cms.gov/medicare/payment/part-b-drugs/asp-pricing-files",
      "asOf": "2026-09-06"
    },
    {
      "country": "UK",
      "reimbursement": "NICE: recommended across many indications (melanoma, NSCLC, TNBC KEYNOTE-522/355, RCC, HNSCC, cervical, oesophageal and others)",
      "source": "https://www.nice.org.uk/guidance/published?ngt=Technology%20appraisal%20guidance",
      "asOf": "2026-09-06"
    },
    {
      "country": "EU",
      "reimbursement": "EMA approved; reimbursed in all member states for core indications",
      "asOf": "2026-09-06"
    }
  ],
  "regulatoryEvents": [
    {
      "date": "2014-09-04",
      "type": "approval",
      "region": "US",
      "note": "Accelerated approval, advanced melanoma after ipilimumab; first PD-1 inhibitor in the US",
      "source": "https://www.fda.gov/drugs/resources-information-approved-drugs/oncology-cancer-hematologic-malignancies-approval-notifications"
    },
    {
      "date": "2015-10-02",
      "type": "approval",
      "region": "US",
      "note": "PD-L1+ NSCLC after platinum",
      "source": "https://www.fda.gov/drugs/resources-information-approved-drugs/oncology-cancer-hematologic-malignancies-approval-notifications"
    },
    {
      "date": "2017-05-23",
      "type": "approval",
      "region": "US",
      "note": "MSI-H/dMMR solid tumours: first tumour-agnostic approval",
      "source": "https://www.fda.gov/drugs/resources-information-approved-drugs/oncology-cancer-hematologic-malignancies-approval-notifications"
    }
  ]
}

Company

Company295 companies

Who is building what.

FieldTypeRequiredDescription
kind"company"yesDiscriminator; fixed per kind.
hqstringyesHeadquarters city.
countryISO 3166 country codeyesISO 3166-1 alpha-2 country code.
companyType"pharma" | "biotech" | "diagnostics" | "imaging" | "devices" | "ai-software" | "radiopharma" | "cell-therapy" | "cro-services" | "nonprofit"yesBroad type used for filtering and the landscape grid.
websiteURLyesOfficial website.
tickerstringnoStock ticker with exchange suffix where needed.
foundedintegernoYear founded.
Example: bms (arrays trimmed to three items, long strings shortened)
{
  "id": "bms",
  "kind": "company",
  "name": "Bristol Myers Squibb",
  "tldr": "Pioneer of checkpoint inhibitors (Opdivo, Yervoy), now betting on the first successful bispecific ADC and alpha radiopharmaceuticals.",
  "summary": "Nivolumab, ipilimumab, Opdualag; izalontamab brengitecan (SystImmune, $8.4B); RayzeBio ($4.1B, RYZ101); Mirati (adagrasib); Breyanzi and Abecma CAR-T; BioNTe...",
  "asOf": "2026-09-04",
  "sections": [
    "immunotherapy",
    "adcs",
    "radiopharma"
  ],
  "drugs": [
    "nivolumab",
    "ipilimumab",
    "relatlimab-nivolumab"
  ],
  "hq": "Princeton, NJ",
  "country": "US",
  "companyType": "pharma",
  "website": "https://www.bms.com",
  "ticker": "BMY"
}

Institution

Institution421 institutions

The centres and universities that matter, mapped and ranked.

FieldTypeRequiredDescription
kind"institution"yesDiscriminator; fixed per kind.
citystringyesCity.
countryISO 3166 country codeyesISO 3166-1 alpha-2 country code.
latnumberyesLatitude, for the map.
lngnumberyesLongitude, for the map.
institutionType"cancer-center" | "university" | "hospital" | "research-institute" | "government" | "consortium"yesBroad type used for filtering.
websiteURLyesOfficial website.
nci"comprehensive" | "clinical" | "basic"noNCI designation, US only.
newsweekOncology2026integernoNewsweek / Statista World's Best Specialized Hospitals 2026, Oncology rank.
universitystringnoParent university, when the institution is a cancer center inside one.
programsstring[]
default []
noNamed programmes or centres of excellence.
Example: nci (arrays trimmed to three items, long strings shortened)
{
  "id": "nci",
  "kind": "institution",
  "name": "National Cancer Institute (NIH)",
  "tldr": "The NCI is the US government's cancer research agency, spending ~$7B a year and running the Cancer Centers Program, TCGA, and Rosenberg's cell therapy lab.",
  "summary": "Funds the 74 NCI-designated centres, ran TCGA and the RAS Initiative, runs SEER and ClinicalTrials-linked cooperative groups (NRG, SWOG, Alliance, ECOG-ACRIN...",
  "asOf": "2026-09-04",
  "technologies": [
    "til-therapy",
    "tcr-t"
  ],
  "city": "Bethesda, MD",
  "country": "US",
  "lat": 39.003,
  "lng": -77.104,
  "institutionType": "government",
  "website": "https://www.cancer.gov",
  "programs": [
    "Cancer Centers Program (74 centres)",
    "TCGA / GDC",
    "Cooperative groups"
  ]
}

Pathway

Pathway80 pathways

The classic signalling circuits, drawn and explained.

FieldTypeRequiredDescription
kind"pathway"yesDiscriminator; fixed per kind.
analogystringyesLayman explanation using an analogy.
nodes{ id, label, x, y, targetId }[]yesDiagram nodes with positions; a node may point at a target record.
  • id: string
  • label: string
  • x: number
  • y: number
  • targetId: entity id (optional)
edges{ from, to, type }[]yesDiagram edges: activates or inhibits.
  • from: string
  • to: string
  • type: "activates" | "inhibits" (optional)
interventionsstring[]
default []
noHow drugs attack it.
Example: ras-mapk (arrays trimmed to three items, long strings shortened)
{
  "id": "ras-mapk",
  "kind": "pathway",
  "name": "RAS / RAF / MEK / ERK (MAPK)",
  "tldr": "The RAS-MAPK pathway is the cell's 'divide' relay. A signal at the surface flips RAS on, which passes to RAF, MEK, and ERK, which tell the nucleus to make th...",
  "summary": "Growth-factor receptors recruit GRB2/SOS to load GTP onto RAS (KRAS, NRAS, HRAS). RAS-GTP recruits RAF (BRAF, CRAF) dimers, which phosphorylate MEK1/2, which...",
  "asOf": "2026-09-04",
  "wikipedia": "https://en.wikipedia.org/wiki/MAPK/ERK_pathway",
  "cancers": [
    "pancreatic",
    "colorectal",
    "nsclc"
  ],
  "targets": [
    "kras",
    "braf",
    "egfr"
  ],
  "drugs": [
    "sotorasib",
    "adagrasib",
    "daraxonrasib"
  ],
  "analogy": "A relay race: receptor hands the baton to RAS, RAS to RAF, RAF to MEK, MEK to ERK, ERK runs into the nucleus and shouts 'divide'. A KRAS mutation is a runner...",
  "nodes": [
    {
      "id": "rtk",
      "label": "RTK (EGFR, ALK, RET, MET)",
      "x": 50,
      "y": 5,
      "targetId": "egfr"
    },
    {
      "id": "sos",
      "label": "GRB2 / SOS1",
      "x": 50,
      "y": 20
    },
    {
      "id": "ras",
      "label": "RAS (KRAS)",
      "x": 50,
      "y": 36,
      "targetId": "kras"
    }
  ],
  "edges": [
    {
      "from": "rtk",
      "to": "sos",
      "type": "activates"
    },
    {
      "from": "sos",
      "to": "ras",
      "type": "activates"
    },
    {
      "from": "nf1",
      "to": "ras",
      "type": "inhibits"
    }
  ],
  "interventions": [
    "KRAS G12C inhibitors (sotorasib, adagrasib) ± anti-EGFR in colorectal cancer",
    "Pan-RAS(ON) inhibitor daraxonrasib (phase 3, pancreatic)",
    "BRAF + MEK inhibitors (dabrafenib/trametinib, encorafenib/binimetinib)"
  ]
}

Term

Term600 terms

Glossary with plain-English TL;DRs and Wikipedia links.

FieldTypeRequiredDescription
kind"term"yesDiscriminator; fixed per kind.
categorystringyesGlossary category (Endpoints, Biomarkers, Trials, ...).
Example: mrd (arrays trimmed to three items, long strings shortened)
{
  "id": "mrd",
  "kind": "term",
  "name": "Minimal / molecular residual disease (MRD)",
  "tldr": "Cancer still present after treatment but too small to see on scans, detected by blood or marrow tests.",
  "summary": "In leukaemia/myeloma: flow cytometry or NGS of marrow (clonoSEQ). In solid tumours: ctDNA after surgery. MRD positivity predicts relapse; MRD-guided escalati...",
  "asOf": "2026-09-04",
  "wikipedia": "https://en.wikipedia.org/wiki/Minimal_residual_disease",
  "technologies": [
    "mrd-testing"
  ],
  "trials": [
    "imvigor011",
    "dynamic"
  ],
  "category": "Biomarkers"
}

Trial

Trial401 trials

Landmark and current trials that define the standard of care.

FieldTypeRequiredDescription
kind"trial"yesDiscriminator; fixed per kind.
nctstringnoPrimary registry id: ClinicalTrials.gov NCT number, or ISRCTN, ACTRN or NTR.
phase"1" | "2" | "3" | "4" | "1/2" | "2/3" | "observational" | "platform"yesTrial phase.
settingstringyesDisease setting and line of therapy.
sponsorstringnoLead sponsor.
resultstringnoHeadline result in one or two sentences, with numbers only if sourced.
yearReportedintegernoYear the primary result was reported.
enrolledintegernoParticipants enrolled.
outcomes{ endpoint, primary, unit, arms, hr, ci, p, source }[]
default []
noStructured outcomes; values in the arm's unit (months, percent). Enables pictograms and comparisons.
  • endpoint: string
  • primary: boolean (optional)
  • unit: string (optional)
  • arms: { name, n, value, note }[]
  • hr: number (optional)
  • ci: [number, number] (optional)
  • p: string (optional)
  • source: URL (optional)
replicationstringnoHas an independent trial or real-world study confirmed the effect?
Example: imvigor011 (arrays trimmed to three items, long strings shortened)
{
  "id": "imvigor011",
  "kind": "trial",
  "name": "IMvigor011",
  "tldr": "The first trial to use a blood test for leftover cancer to decide who gets immunotherapy, and it worked.",
  "summary": "DFS HR 0.64; OS HR 0.59 in ctDNA-positive patients; ctDNA-negative patients had excellent outcomes without treatment. FDA approval Q2 2026, the first ctDNA-g...",
  "status": "positive",
  "asOf": "2026-09-04",
  "links": [
    {
      "label": "ClinicalTrials.gov NCT04660344",
      "url": "https://clinicaltrials.gov/study/NCT04660344"
    }
  ],
  "cancers": [
    "urothelial"
  ],
  "technologies": [
    "mrd-testing"
  ],
  "drugs": [
    "atezolizumab",
    "signatera"
  ],
  "terms": [
    "mrd",
    "ctdna"
  ],
  "nct": "NCT04660344",
  "phase": "3",
  "setting": "Muscle-invasive bladder cancer after cystectomy, ctDNA-positive (Signatera): atezolizumab vs placebo",
  "sponsor": "Roche",
  "result": "DFS HR 0.64; OS HR 0.59 in ctDNA+.",
  "yearReported": 2025,
  "enrolled": 761,
  "outcomes": [
    {
      "endpoint": "Disease-free survival (ctDNA-positive, randomised)",
      "primary": true,
      "unit": "months",
      "arms": [
        {
          "name": "Atezolizumab",
          "n": 167,
          "value": 9.9
        },
        {
          "name": "Placebo",
          "n": 83,
          "value": 4.8
        }
      ],
      "hr": 0.64,
      "ci": [
        0.47,
        0.88
      ],
      "p": "0.005",
      "source": "https://www.roche.com/media/releases/med-cor-2025-10-20b"
    },
    {
      "endpoint": "Overall survival (ctDNA-positive)",
      "unit": "months",
      "arms": [
        {
          "name": "Atezolizumab",
          "value": 32.8
        },
        {
          "name": "Placebo",
          "value": 21.1
        }
      ],
      "hr": 0.59,
      "ci": [
        0.41,
        0.86
      ],
      "p": "0.005",
      "source": "https://www.roche.com/media/releases/med-cor-2025-10-20b"
    },
    {
      "endpoint": "Disease-free survival at 12 months, persistently ctDNA-negative (untreated surveillance)",
      "unit": "%",
      "arms": [
        {
          "name": "ctDNA-negative, surveillance only",
          "n": 357,
          "value": 95.4,
          "note": "12-month OS 100% in this group"
        }
      ],
      "source": "https://www.roche.com/media/releases/med-cor-2025-10-20b"
    }
  ],
  "replication": "Contrasts with IMvigor010 (unselected adjuvant atezolizumab, negative), whose exploratory ctDNA analysis generated the hypothesis; IMvigor011 is the prospect..."
}

Pairing

Pairing85 pairings

Things that work better together, and things that do not.

FieldTypeRequiredDescription
kind"pairing"yesDiscriminator; fixed per kind.
aentity idyesFirst member of the pair (entity id).
bentity idyesSecond member of the pair (entity id).
rationalestringyesWhy the pair works better than either alone.
evidencestringyesThe evidence for the pairing, with trial names.
pairingType"combination" | "sequence" | "diagnostic-therapeutic" | "platform" | "caution"yesCombination, sequence, diagnostic-therapeutic, platform or caution.
Example: btki-plus-venetoclax-fixed-duration (arrays trimmed to three items, long strings shortened)
{
  "id": "btki-plus-venetoclax-fixed-duration",
  "kind": "pairing",
  "name": "BTK inhibitor + venetoclax, fixed duration",
  "tldr": "Block the survival signal and remove the death shield at the same time, for about a year, then stop and stay in remission for years.",
  "summary": "CAPTIVATE and GLOW (ibrutinib), AMPLIFY (acalabrutinib; FDA approved February 2026), SEQUOIA arm D (zanubrutinib), and CELESTIAL (sonrotoclax + zanubrutinib)...",
  "asOf": "2026-09-07",
  "cancers": [
    "cll"
  ],
  "targets": [
    "btk",
    "bcl2"
  ],
  "drugs": [
    "acalabrutinib",
    "ibrutinib",
    "zanubrutinib"
  ],
  "trials": [
    "amplify",
    "glow",
    "captivate"
  ],
  "a": "acalabrutinib",
  "b": "venetoclax",
  "rationale": "BTK inhibition mobilises CLL cells out of protective lymph-node niches and increases BCL-2 dependence; venetoclax then kills them. The two resistance mechani...",
  "evidence": "Multiple positive phase 3 trials; US approval 2026.",
  "pairingType": "combination"
}

Roadmap

Roadmap13 roadmaps

Where a technology has been and where it is heading.

FieldTypeRequiredDescription
kind"roadmap"yesDiscriminator; fixed per kind.
steps{ era, title, description, refs, status }[]yesOrdered eras from history to horizon, each with a status.
  • era: string
  • title: string
  • description: string
  • refs: entity id[] (optional)
  • status: "historic" | "current" | "emerging" | "speculative"
Example: frontier-2035 (arrays trimmed to three items, long strings shortened)
{
  "id": "frontier-2035",
  "kind": "roadmap",
  "name": "Radical oncology: what could change the war by 2035",
  "tldr": "Radical oncology is a horizon map of the wilder ideas in cancer, sorted by how close they are to mattering, with the reason each one might never arrive.",
  "summary": "Most of what is celebrated as a breakthrough is an incremental gain on an existing modality. This roadmap collects the ideas that would change the shape of t...",
  "asOf": "2026-09-08",
  "sections": [
    "drug-discovery",
    "radiation",
    "cell-therapy"
  ],
  "steps": [
    {
      "era": "Now (randomised data exists)",
      "title": "Ideas already being tested against a control arm",
      "description": "Microbiome modulation, spatially fractionated radiotherapy, sonodynamic therapy in glioblastoma, GDF-15 blockade for cachexia, and repurposed cheap drugs all...",
      "refs": [
        "microbiome-modulation-io",
        "lattice-radiotherapy",
        "sonodynamic-therapy"
      ],
      "status": "current"
    },
    {
      "era": "By 2027 (early clinical, readouts imminent)",
      "title": "Living drugs, logic gates, and designed proteins reach decision points",
      "description": "Engineered bacteria, logic-gated cell therapies, molecular glue platforms, and de novo designed binders all have first-in-human programmes running. The quest...",
      "refs": [
        "engineered-bacteria-therapy",
        "logic-gated-therapeutics",
        "molecular-glue-platforms"
      ],
      "status": "emerging"
    },
    {
      "era": "By 2030 (physics and chemistry maturing)",
      "title": "Radiation and radiopharmaceuticals get a second act",
      "description": "Auger emitters, contained alpha nanogenerators, proton arc delivery, and very-high-energy electrons are all limited today by engineering rather than biology:...",
      "refs": [
        "auger-electron-therapy",
        "alpha-nanogenerators",
        "proton-arc-therapy"
      ],
      "status": "emerging"
    }
  ]
}

Idea

Idea1107 ideas

Hypotheses and new directions, linked to the evidence.

FieldTypeRequiredDescription
kind"idea"yesDiscriminator; fixed per kind.
hypothesisstringyesThe claim, in one sentence.
rationalestringyesWhy the pair works better than either alone, or why it is a caution.
teststringyesWhat experiment or trial would confirm or kill it.
maturity"speculative" | "preclinical-evidence" | "early-clinical" | "being-tested-at-scale"yesHow far the idea has been tested.
actor"research" | "clinic" | "industry" | "regulator" | "payer" | "policy" | "patients" | "data" | "philanthropy" | "engineering"noWho would have to act: research, clinic, industry, regulator, payer, policy, patients, data, philanthropy.
cost"small" | "medium" | "large"noRough cost to try: small (<$1M), medium ($1-50M), large (>$50M).
horizonYearsintegernoTime to first evidence of impact in years.
Example: idea-fund-surgical-trials-network (arrays trimmed to three items, long strings shortened)
{
  "id": "idea-fund-surgical-trials-network",
  "kind": "idea",
  "name": "A permanently funded international network for randomised cancer surgery trials",
  "tldr": "Surgery cures more cancer than any drug, yet most operations have never been compared in a proper trial. A standing network of hospitals, with core funding, ...",
  "summary": "A surgical oncology trials network with core funding for trial units, research nurses and data managers at fifty to one hundred hospitals, standing ethics an...",
  "asOf": "2026-09-08",
  "links": [
    {
      "label": "GlobalSurg Collaborative",
      "url": "https://globalsurg.org/"
    },
    {
      "label": "IDEAL Collaboration",
      "url": "https://www.ideal-collaboration.net/"
    }
  ],
  "related": [
    "idea-fund-non-drug-trial-quota",
    "idea-fund-surgical-video-registry",
    "idea-fund-organ-preservation-programme"
  ],
  "technologies": [
    "robotic-surgery",
    "sentinel-node"
  ],
  "institutions": [
    "jcog",
    "alliance-oncology",
    "royal-marsden"
  ],
  "people": [
    "kitagawa-yuko",
    "sano-takeshi",
    "chaturvedi-pankaj"
  ],
  "bottlenecks": [
    "b-surgery-radiation-innovation",
    "b-trial-enrolment"
  ],
  "hypothesis": "A funded network completes at least ten adequately powered randomised surgical trials per five years with more than 80% accrual to target, compared with the ...",
  "rationale": "Where surgical trial infrastructure has been funded, landmark results followed: the LACC trial on minimally invasive radical hysterectomy, the JCOG gastric l...",
  "test": "Fund the network for one five-year cycle with a portfolio of five trials and audit accrual, completion and guideline impact against surgical trials run witho...",
  "maturity": "early-clinical",
  "actor": "policy",
  "cost": "large",
  "horizonYears": 5
}

Collection

Collection110 collections

The open databases and registries the field runs on.

FieldTypeRequiredDescription
kind"collection"yesDiscriminator; fixed per kind.
urlURLyesOfficial URL.
holdsstringyesWhat the collection or database holds.
licensestringnoLicence the data are released under.
maintainerstringnoWho maintains it.
Example: clinicaltrials-gov (arrays trimmed to three items, long strings shortened)
{
  "id": "clinicaltrials-gov",
  "kind": "collection",
  "name": "ClinicalTrials.gov",
  "tldr": "ClinicalTrials.gov is the master list of clinical trials. Every trial on this site links to its record.",
  "summary": "Mandatory registration for US trials; API v2 provides structured access to eligibility, arms, outcomes, and results. The backbone for any trial-matching tool.",
  "asOf": "2026-09-04",
  "technologies": [
    "ai-trial-matching"
  ],
  "url": "https://clinicaltrials.gov",
  "holds": "Registry and results database of >500,000 clinical studies worldwide.",
  "license": "Public domain (US Government)",
  "maintainer": "NIH / NLM"
}

Person

Person464 people

The clinicians and scientists doing the work: specialisms, bios, papers, and where to find them.

FieldTypeRequiredDescription
kind"person"yesDiscriminator; fixed per kind.
rolestringyesCurrent role and affiliation in one line, e.g. "Chief, Breast Medicine Service".
institutionIdentity idnoPrimary institution id (also list in `institutions`).
specialismsstring[]
default []
noSpecialisms, for filtering.
profiles{ label, url }[]
default []
noProfessional links: profile, lab, Google Scholar, ORCID, PubMed, X/LinkedIn.
  • label: string
  • url: URL
papers{ title, journal, year, url, doi, note }[]
default []
noSelected publications, most recent or most cited first.
  • title: string
  • journal: string (optional)
  • year: integer (optional)
  • url: URL (optional)
  • doi: string (optional)
  • note: string (optional)
orcidstringnoORCID id.
hIndexintegernoh-index, if known and sourced.
Example: sara-tolaney (arrays trimmed to three items, long strings shortened)
{
  "id": "sara-tolaney",
  "kind": "person",
  "name": "Sara M. Tolaney",
  "tldr": "Leads Dana-Farber's breast oncology division and many of the trials that moved ADCs and de-escalated therapy into breast cancer care.",
  "summary": "Led the APT trial establishing adjuvant paclitaxel-trastuzumab for small HER2-positive tumours, and is a principal investigator across the DESTINY, TROPION a...",
  "asOf": "2026-09-08",
  "cancers": [
    "breast-her2-positive",
    "breast-hr-positive",
    "tnbc"
  ],
  "technologies": [
    "adc"
  ],
  "targets": [
    "her2",
    "trop2"
  ],
  "drugs": [
    "trastuzumab-deruxtecan",
    "datopotamab-deruxtecan",
    "sacituzumab-govitecan"
  ],
  "institutions": [
    "dana-farber"
  ],
  "trials": [
    "apt-trial",
    "tropion-breast01",
    "destiny-breast09"
  ],
  "role": "Chief, Division of Breast Oncology; Associate Director, Susan F. Smith Center for Women's Cancers",
  "institutionId": "dana-farber",
  "specialisms": [
    "Breast cancer",
    "HER2-positive breast cancer",
    "Antibody-drug conjugates"
  ],
  "profiles": [
    {
      "label": "Dana-Farber profile",
      "url": "https://www.dana-farber.org/find-a-doctor/sara-m-tolaney"
    },
    {
      "label": "PubMed",
      "url": "https://pubmed.ncbi.nlm.nih.gov/?term=Tolaney%20SM%5BAuthor%5D"
    }
  ],
  "papers": [
    {
      "title": "Adjuvant paclitaxel and trastuzumab for node-negative, HER2-positive breast cancer",
      "journal": "New England Journal of Medicine",
      "year": 2015,
      "url": "https://doi.org/10.1056/NEJMoa1406281",
      "doi": "10.1056/NEJMoa1406281"
    },
    {
      "title": "Datopotamab deruxtecan versus chemotherapy in previously treated inoperable/metastatic hormone receptor-positive HER2-negative breast cancer (TROPION-Breast01)",
      "journal": "Journal of Clinical Oncology",
      "year": 2025,
      "url": "https://doi.org/10.1200/JCO.24.00920",
      "doi": "10.1200/JCO.24.00920"
    }
  ]
}

Bottleneck

Bottleneck45 bottlenecks

The systemic constraints slowing the whole war on cancer, with the ideas that could break each one.

FieldTypeRequiredDescription
kind"bottleneck"yesDiscriminator; fixed per kind.
stage"biology" | "prevention-detection" | "trials" | "regulation-manufacturing" | "access-delivery" | "data-knowledge" | "funding-incentives" | "people-culture"yesWhere in the pipeline it bites.
severity"critical" | "major" | "moderate"yesHow much it slows the whole effort.
metrics{ label, value, source, url }[]
default []
noNumbers that show the size of the problem, each with a source.
  • label: string
  • value: string
  • source: string (optional)
  • url: URL (optional)
causesstring[]
default []
noRoot causes, plain English, one per item.
currentEffortsstring[]
default []
noWhat is already being tried and by whom.
successLooksLikestringnoWhat would count as the bottleneck being broken.
Example: b-toxicity-qol (arrays trimmed to three items, long strings shortened)
{
  "id": "b-toxicity-qol",
  "kind": "bottleneck",
  "name": "Toxicity and quality of life are undervalued",
  "tldr": "Trials measure how long people live, not how they live. Side-effects are under-reported and under-treated.",
  "summary": "Oncology trials are designed around survival and progression, and the harms and lived experience of treatment are secondary at best. Clinicians systematicall...",
  "asOf": "2026-09-08",
  "links": [
    {
      "label": "Di Maio et al., Symptomatic toxicities experienced during anticancer treatment: agreement between patient and physician reporting (JCO 2015)",
      "url": "https://doi.org/10.1200/JCO.2014.57.9334"
    },
    {
      "label": "Davis et al., Availability of evidence of benefits on overall survival and quality of life of cancer drugs approved by EMA 2009-13 (BMJ 2017)",
      "url": "https://doi.org/10.1136/bmj.j4530"
    },
    {
      "label": "EORTC Quality of Life Group",
      "url": "https://qol.eortc.org/"
    }
  ],
  "related": [
    "fda-approvals",
    "esmo-guidelines"
  ],
  "sections": [
    "supportive-care"
  ],
  "technologies": [
    "scalp-cooling",
    "cardio-oncology",
    "adc"
  ],
  "institutions": [
    "esmo",
    "asco",
    "nci"
  ],
  "terms": [
    "irae",
    "crs",
    "icans"
  ],
  "stage": "people-culture",
  "severity": "major",
  "metrics": [
    {
      "label": "Cancer drug indications approved by the EMA 2009-2013 with no evidence of quality-of-life or survival benefit at approval",
      "value": "57%",
      "source": "Davis et al., BMJ 2017",
      "url": "https://doi.org/10.1136/bmj.j4530"
    },
    {
      "label": "Agreement between physician and patient reporting of symptomatic toxicities (anorexia, nausea, vomiting, constipation, diarrhoea, hair loss) in three randomi...",
      "value": "Physicians under-reported all six symptoms",
      "source": "Di Maio et al., JCO 2015",
      "url": "https://doi.org/10.1200/JCO.2014.57.9334"
    },
    {
      "label": "Median overall survival with routine patient-reported symptom monitoring vs usual care during chemotherapy (randomised)",
      "value": "31.2 vs 26.0 months",
      "source": "Basch et al., JAMA 2017",
      "url": "https://doi.org/10.1001/jama.2017.7156"
    }
  ],
  "causes": [
    "Regulatory approval and pricing are based on efficacy endpoints, so sponsors invest little in quality-of-life measurement.",
    "Clinician-graded adverse event scales miss what patients feel and ignore chronic low-grade toxicity.",
    "Quality-of-life analyses are heterogeneous, unpublished or reported long after the primary paper."
  ],
  "currentEfforts": [
    "PRO-CTCAE (NCI) provides a validated patient-reported version of the toxicity scale now used in many trials.",
    "The FDA guidance on core patient-reported outcomes in cancer clinical trials (2021 draft) specifies which PRO domains should be measured.",
    "SISAQOL-IMI is developing consensus standards for analysing and reporting quality-of-life data in cancer trials."
  ],
  "successLooksLike": "Every registrational oncology trial collects and publishes patient-reported outcomes with the primary results, quality of life is graded in every value frame..."
}

Key paper

Key paper146 key papers

The papers that changed practice or thinking, each explained: what it found, what it means, and what to be careful about.

FieldTypeRequiredDescription
kind"paper"yesDiscriminator; fixed per kind.
journalstringyesJournal name as printed.
yearintegeryesPublication year.
doistringnoDigital object identifier.
pmidstringnoPubMed id.
authorsstringyes"Surname A, Surname B, et al."
paperType"rct" | "meta-analysis" | "observational" | "real-world" | "basic" | "translational" | "review" | "guideline" | "methods"yesStudy design.
findingsstring[]
default []
noThe key results, one per item, with the numbers.
whatItMeansstringyesPlain English: what this changes for patients, clinicians or the field.
caveatsstring[]
default []
noLimitations, open questions, disputes.
changedPracticebooleannoDid it change guidelines or approvals?
participantsintegernoRoughly how many participants, for trials and cohorts.
Example: paper-destiny-breast03-nejm-2022 (arrays trimmed to three items, long strings shortened)
{
  "id": "paper-destiny-breast03-nejm-2022",
  "kind": "paper",
  "name": "DESTINY-Breast03: trastuzumab deruxtecan beats T-DM1 as second-line treatment of HER2-positive metastatic breast cancer",
  "tldr": "A newer antibody-drug conjugate, trastuzumab deruxtecan, kept HER2-positive metastatic breast cancer under control roughly four times longer than the previou...",
  "summary": "Open-label phase 3 trial of 524 patients with HER2-positive unresectable or metastatic breast cancer previously treated with trastuzumab and a taxane, random...",
  "asOf": "2026-09-08",
  "links": [
    {
      "label": "NEJM 2022",
      "url": "https://doi.org/10.1056/NEJMoa2115022"
    },
    {
      "label": "ClinicalTrials.gov NCT03529110",
      "url": "https://clinicaltrials.gov/study/NCT03529110"
    }
  ],
  "related": [
    "idea-payload-switching"
  ],
  "cancers": [
    "breast-her2-positive"
  ],
  "technologies": [
    "adc",
    "topoisomerase-inhibitors"
  ],
  "targets": [
    "her2"
  ],
  "drugs": [
    "trastuzumab-deruxtecan",
    "trastuzumab-emtansine"
  ],
  "companies": [
    "daiichi-sankyo",
    "astrazeneca"
  ],
  "terms": [
    "pfs",
    "os",
    "payload"
  ],
  "trials": [
    "destiny-breast03"
  ],
  "people": [
    "javier-cortes",
    "kim-sung-bae",
    "im-seock-ah"
  ],
  "bottlenecks": [
    "b-resistance",
    "b-toxicity-qol"
  ],
  "journal": "New England Journal of Medicine",
  "year": 2022,
  "doi": "10.1056/NEJMoa2115022",
  "authors": "Cortes J, Kim SB, Chung WP, et al.",
  "paperType": "rct",
  "findings": [
    "12-month progression-free survival 75.8% with T-DXd vs 34.1% with T-DM1; HR 0.28 (95% CI 0.22-0.37).",
    "Confirmed objective response 79.7% vs 34.2%.",
    "Updated analysis (Lancet 2023): median PFS 28.8 vs 6.8 months; overall survival HR 0.64."
  ],
  "whatItMeans": "For HER2-positive metastatic breast cancer that has progressed after trastuzumab and a taxane, trastuzumab deruxtecan is now the standard second-line treatme...",
  "caveats": [
    "Open-label design, though the primary endpoint was assessed by blinded central review.",
    "Interstitial lung disease requires proactive CT surveillance and dose interruption; fatal cases occurred in other T-DXd trials.",
    "Many patients had not received pertuzumab-based first-line therapy, so the population differs slightly from today's second line."
  ],
  "changedPractice": true,
  "participants": 524
}

Journal

Journal67 journals

Where the evidence is published: the journals, their scope and access model, and the key papers each one carried.

FieldTypeRequiredDescription
kind"journal"yesDiscriminator; fixed per kind.
publisherstringyesPublisher.
urlURLyesOfficial URL.
issnstringnoISSN.
scopestringyesBroad scope: general medicine, oncology, haematology, basic science, radiology, etc.
access"subscription" | "hybrid" | "open-access" | "diamond"noOpen access model: subscription, hybrid, open access, diamond.
foundedintegernoYear founded.
impactFactor{ value, year, source }noLatest impact factor or citation metric, with the year it refers to. Optional and clearly labelled.
  • value: number
  • year: integer
  • source: string (optional)
matchNamesstring[]
default []
noNames as they appear in paper records, so papers can be matched to this journal.
societystringnoOwning or affiliated society.
Example: annals-of-oncology (arrays trimmed to three items, long strings shortened)
{
  "id": "annals-of-oncology",
  "kind": "journal",
  "name": "Annals of Oncology",
  "aka": [
    "Ann Oncol"
  ],
  "tldr": "Annals of Oncology is ESMO's flagship journal, publishing European phase 3 trials, the ESMO Clinical Practice Guidelines and the abstract books for the ESMO ...",
  "summary": "Annals of Oncology appears monthly and publishes the ESMO Clinical Practice Guidelines (free to read), ESMO-MCBS benefit scores, trial results often presente...",
  "asOf": "2026-09-09",
  "links": [
    {
      "label": "ESMO Guidelines",
      "url": "https://www.esmo.org/guidelines"
    }
  ],
  "related": [
    "src-annals-oncology",
    "src-esmo-congress",
    "esmo-guidelines"
  ],
  "institutions": [
    "esmo"
  ],
  "publisher": "Elsevier",
  "url": "https://www.annalsofoncology.org",
  "issn": "0923-7534",
  "scope": "clinical oncology",
  "access": "hybrid",
  "founded": 1990,
  "impactFactor": {
    "value": 56.7,
    "year": 2023,
    "source": "Clarivate Journal Citation Reports 2024 (2023 JIF)"
  },
  "matchNames": [
    "Annals of Oncology",
    "Ann Oncol"
  ],
  "society": "European Society for Medical Oncology"
}

Statuses

One shared list across kinds. Products use the approval and phase values; trials use recruiting, active, completed and the outcome values; technologies use established, emerging and historic.

ValueShown as
approvedApproved
phase-3Phase 3
phase-2Phase 2
phase-1Phase 1
preclinicalPreclinical
conceptConcept
standard-of-careStandard of care
establishedEstablished
emergingEmerging
historicHistoric
withdrawnWithdrawn
activeActive
completedCompleted
recruitingRecruiting
positivePositive
negativeNegative
mixedMixed
plannedPlanned