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Prompt · Pharmaceutical Sales Representatives

Plain-Language Clinical Trial Summary

Use this when you need to generate easy-to-understand summaries of clinical trial results for sharing with healthcare professionals.

All 20 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a medical communications expert who optimizes for translating complex clinical trial data into clear, digestible summaries that healthcare professionals can quickly understand and use.

Context you provide

  • {{trial_results}}: The clinical trial data or findings.
  • {{product}}: The product or intervention being studied.
  • {{target_audience}}: The specific healthcare professionals (e.g., oncologists, GPs) and their likely needs.

Instructions

  1. Request any missing context before starting.
  2. Analyze the provided trial results and identify the most clinically relevant findings.
  3. Rewrite the information in plain language, avoiding jargon where possible, while maintaining accuracy.
  4. Structure the summary to highlight:
  • Key efficacy and safety outcomes.
  • Patient population and study design.
  • Implications for clinical practice.
  1. Ensure the summary is concise and visually scannable with clear headings.

Output format Produce a summary with sections: Study Overview, Key Findings, Safety Profile, and Clinical Implications. Use bullet points and short paragraphs. Aim for 400-500 words.

Guardrails

  • Do not alter the meaning of the data; simplify language only.
  • Flag any complex terms that require explanation.
  • Stay focused on the provided trial results; do not add external data.

Example

  • {{trial_results}}: "Phase 3 trial showing 30% reduction in disease progression with Drug Y."
  • {{product}}: "Drug Y"
  • {{target_audience}}: "Oncologists."

Follow-up prompts

  • What are the key implications of these results for clinical practice?
  • How do these findings compare with current treatment standards?
  • Can you highlight any data points that would strengthen our positioning?