AI Peer Review — structured, auditable, fast
We pair domain experts with AI to check healthcare content against trusted sources (MHRA, NICE, EMA). You get a clear decision log, citations, and JSON-LD updates that improve AI visibility.
What you get
- Structured checklist covering facts, claims, compliance and clarity
- Source-anchored decisions with outbound citations (MHRA/NICE/EMA)
- Suggested edits + 40–50 word canonical “answer” for AI Overviews
- JSON-LD blocks (Service/Article/FAQPage) ready to paste
- Change log with rationale for each revision
How it works
- Ingest page/PDF → extract headings, meta, likely FAQs
- AI + editor review against authority sources
- Proposed edits and structured data
- Final human validation
- Re-scan and freshness update (dateModified, sitemap)
We don’t replace experts — we make them faster and more consistent.
Benefits
- Trust: everything cites a specific section in a regulator-approved source
- Speed: faster cycles without losing rigour
- Visibility: AI-ready content (FAQs, canonical answers, schema)
- Governance: decision log for audit and medical sign-off
Frequently asked questions
What is PharmAdvisor’s AI Peer Review?
AI Peer Review combines domain experts with AI tools to check healthcare content against trusted sources (e.g., regulator and guideline sites). You receive a structured decision log, suggested edits, and JSON-LD updates so pages are clear, accurate and eligible for AI citations.
What problems does it solve?
It reduces review backlog and inconsistency. We highlight factual gaps, ambiguous claims and missing citations; propose concise, patient-friendly wording; and add structured data and freshness signals so AI search can confidently quote and attribute your content.
How does the process work?
We ingest your page or PDF, extract headings/metadata/likely FAQs, and ground each claim against authoritative sources. Editors validate AI suggestions, author a 40–50 word canonical answer, add JSON-LD (WebPage/Article/FAQPage), and align visible “Last updated” with dateModified and sitemap.
What do we receive?
A change log with rationales, redlines or suggested copy, canonical answer, refined FAQs, validated JSON-LD snippets, and a publish checklist. We also provide a re-scan confirming freshness and schema validity after you implement changes.
How do you handle safety and accuracy?
We ground claims in regulator-approved or otherwise authoritative sources and include outbound citations. High-risk topics include explicit warnings and deferrals to healthcare professionals. Editors have final say—AI suggestions never auto-publish.
Which pages benefit most?
Service pages, patient FAQs, clinical summaries and research explainers—any content that answers specific questions. Start with high-traffic or high-risk pages, then extend to related topics for broader coverage.
Ready to trial AI Peer Review?
We offer a fixed-scope pilot for a set of pages or a report. See the output, then expand.
Get in touch
Follow us on LinkedIn or email steve@pharmadvisor.org.uk.