~15 min with AI, ~60 min without
Enhanced review with source cross-check; higher scrutiny for patient or regulatory content.Reviewed source → AI audience adaptation → Accuracy cross-check → Adapted version
Best for
- Repurposing approved specialist content for GPs, nurses, payers, or patients
- Preparing multi-audience materials from a single evidence base
- Adapting a technical manuscript summary into a client-facing or internal briefing
- Creating tiered stakeholder content from the same core data
- Shifting emphasis (e.g., efficacy-led to practical-considerations-led) for a different reader
Inputs
- Source content: reviewed, accurate, with clear references
- Target audience specification: be specific (e.g., “community pharmacists in primary care,” not just “HCPs”)
- Context on the target audience’s knowledge level, priorities, and information needs
- Format or length requirements for the adapted version
- Regulatory context for the adapted version (promotional, non-promotional, educational, patient-facing)
Steps
Confirm source content is verified
Only adapt content that has already been reviewed for accuracy. This workflow transforms — it does not create. If the source has not been through QC, do that first.
Define the target audience precisely
Generic audience labels produce generic adaptations. Specify who will read this, what they already know, and what they need from it.
Provide source content and audience specification to AI
Paste the source content along with clear instructions about the target audience, format, and any regulatory context. Use the prompt pattern below.
Generate the adapted version
Run the prompt in LLMentor (or Patiently AI for patient audiences). Request multiple options if you are unsure of the right framing.
Review for meaning preservation
The highest-priority check. Read each clinical claim in the adapted version and confirm it says the same thing as the source — not just something that sounds similar.
Cross-check qualifiers, safety data, and data points
List every qualifier in the source and verify each is preserved or appropriately rephrased. Confirm safety information has not been compressed out. Check all numbers.
Output
A well-adapted document reads naturally for its target audience, not like a mechanical word substitution of the original. It preserves all essential factual content including safety information, adjusts emphasis to match what the target audience needs most, and contains no claims that cannot be traced to the source content.Prompt pattern
Why this works
AI handles the mechanical work of adjusting vocabulary, restructuring paragraphs, and shifting emphasis — tasks that are time-consuming but low-risk when done from verified source content. The human writer retains the high-judgement decisions: what the audience needs to know, whether simplified claims still mean the same thing, and whether the adapted version meets its regulatory requirements.Common mistakes
Meaning drift during simplification
Meaning drift during simplification
Source says “Treatment X demonstrated non-inferior efficacy to Treatment Y.” The GP-facing adaptation reads “Treatment X works as well as Treatment Y.” These are not the same claim. Cross-check every clinical claim line-by-line against the source, reading for meaning rather than surface similarity.
Dropped qualifiers
Dropped qualifiers
Source states efficacy “in patients with moderate-to-severe disease (PASI ≥12).” The adapted version drops the qualifier, making the claim appear to cover all patients. List every qualifier in the source and confirm each one survives the adaptation.
Hedging language removed
Hedging language removed
Source uses “may provide benefit” or “showed a trend toward improvement.” The adaptation writes “provides benefit” or “improved outcomes.” Compare certainty levels claim by claim between source and output.
Safety information omitted for brevity
Safety information omitted for brevity
A 2-page GP summary drops the safety section to save space, leaving a one-sided efficacy narrative. Safety information must appear in every adapted version. If space is limited, compress — do not remove.
AI introduces unsourced claims
AI introduces unsourced claims
AI adds a sentence about mechanism of action or treatment guidelines drawn from its training data rather than the source. Verify that every statement in the output traces to the source content. Flag any sentence that sounds like background context; this is where training data leaks in.
Tool stack
| Tool | Role |
|---|---|
| LLMentor | Primary tool for audience-level adaptation |
| Patiently AI | When the target audience is patients or carers |
Review checklist
Human review checklist
Human review checklist
- All factual claims in the adapted version match the source content
- No new information has been introduced that is not in the source
- Safety information is preserved and appropriately represented
- Qualifiers and limitations are retained
- Language is genuinely appropriate for the target audience (not just slightly simplified)
- Medical terms that have been simplified remain accurate
- Data points are correctly reproduced
- The adapted version meets any regulatory or compliance requirements for the target audience/channel
- Emphasis and framing are appropriate for the target audience’s priorities
- The adapted version would make sense to a reader from the target audience without access to the original
Next steps: If your target audience is patients or carers, use Create a Plain Language Summary. Once adapted, run Final Human Review before release, or Repurpose Across Channels to adapt for different channel formats.
Last reviewed: 15 April 2026