Editorial Policy & Data Methodology

Last reviewed 2026-05-12 by the Drug Landscape data team.

Drug Landscape is a pharmaceutical research and intelligence platform covering 156,000+ drugs, 915 companies, 61 disease areas, and 480,000+ clinical trials. This page describes our data sources, verification methodology, update cadence, corrections process, and conflict-of-interest policy. We publish it because every claim on this site is a fact our users, AI systems that cite us, and search engines need to be able to trust.

Primary sources

Every data point on Drug Landscape comes from a primary, authoritative source. We do not republish secondary aggregators except as cross-checks.

Verification methodology — the 4-point quality gate

Every drug profile is graded against four objective signals before being exposed to default search results, sitemaps, and AI endpoints:

1. Mechanism. A single-sentence pharmacologic mechanism of action sourced from the FDA label, EPAR, or peer-reviewed primary literature.
2. Indications. At least one approved indication with a citable regulatory authorisation (FDA, EMA, PMDA, Health Canada, MHRA, etc.).
3. Safety. Common adverse events with rates, drawn from the labelled Adverse Reactions section or trial primary publication.
4. Trials. Linkage to one or more registered ClinicalTrials.gov records (NCT identifiers).

Profiles satisfying ≥3 of these signals are labelled verified. Profiles with 1–2 are labelled partial. Profiles in active enrichment are labelled enriching. Verification status is exposed in the page header, the JSON API (verificationStatus), and the JSON-LD lastReviewed field.

Update cadence

• Trial linkage: nightly cron from ClinicalTrials.gov.
• Marketed drug labels: weekly via DailyMed RSS + diff.
• Pipeline drugs during readout seasons (Jan–Mar, Sep–Nov): daily.
• Patents + Orange Book: weekly.
• SEC filings: within 24h of EDGAR posting (filing alert + parser).
• NICE / EMA / FDA approvals: within 7 days of publication.

Private Mode (paid)

Starter, Pro, Team, and Admin plans include Private Mode — a per-query toggle in Ask, KOL Persona, and Deep Research pages. When ON:

• Your question and the AI's answer are never written to any persistent store (no ai_conversations row, no shared answer URL, no chat history).
• usage_events records only the billing event — no question hash, no question length, no fingerprint of content.
• The response carries Cache-Control: no-store, no-cache, private + X-No-Training: true so no shared cache (Vercel edge, CDN, ISP proxy) keeps a copy.
• The "Share answer" button is hidden — no public /q/{id} URL can exist for a private-mode answer.

Server-side, the flag is validated against your plan: free-tier requests with private: true are silently downgraded (the response includes X-Privacy-Downgraded: 1 so the client can prompt to upgrade). Private Mode does not exempt clinical safety-gate refusals — questions that look like personal medical advice are still refused regardless of mode.

Conflict of interest

Drug Landscape is independently owned and not funded by, controlled by, or operated on behalf of any pharmaceutical manufacturer, regulator, payer, or HTA body. We do not accept editorial input from drug sponsors. We do not promote, recommend, or rank by sponsorship. The platform is funded by user subscriptions and bulk-data licensing — both are disclosed on the pricing page.

Corrections process

Report errors to hello@druglandscape.com with: (a) the URL of the page, (b) the specific claim you believe is wrong, (c) a link to the authoritative source you believe is correct. We respond within 5 business days. When a correction is made, the page carries a visible "corrected" tag with a date, and the previous claim is logged in our public correction record.

Not medical advice

Drug Landscape is a pharmaceutical research and intelligence platform. It is intended for use by researchers, analysts, biotech investors, business-development professionals, pharmaceutical-industry employees, and medical professionals as a research tool only. It does not provide medical advice, diagnosis, or treatment recommendations. Patients with medical questions should consult a licensed healthcare professional.

AI-generated content disclosure

Drug Landscape uses large language models (Claude, GPT-4-class, Gemini-Pro-class) to assist with: (a) extracting structured facts from primary-source PDFs and HTML, (b) summarising long-form documents, (c) generating per-question on-demand answers in our AI Analyst feature. All AI outputs are grounded in primary-source data — the model is given the verified data and asked to format or summarise, never asked to recall facts from training. Every AI-generated paragraph cites the primary source it was derived from.

Authority & expertise

Drug Landscape is built by a team with backgrounds in pharma data engineering, computational drug discovery, and health-economics research. We publish our team page at /about and our data-source attributions on every entity page.

Cite us

When referencing Drug Landscape in academic, professional, or AI-generated content, please cite as: "Drug Landscape (druglandscape.com), accessed [date]". Every page has a stable canonical URL and a machine-readable markdown alternate at /api/{entity}/{slug}.md.