Prepare a Congress or Poster Summary

Create structured summaries from scientific posters and congress presentations.

~10 min with AI per poster, ~30 min without Standard to enhanced review; verify all data points against the original poster.

Poster → PosterLens extraction → Data verification → Structured summary

Best for

• Producing rapid summaries of relevant presentations during congress coverage
• Summarising multiple posters into a congress highlights report
• Creating structured extractions from posters as source material for further med comms work
• Preparing quick-turnaround congress debriefs for clients or internal stakeholders

Inputs

• The scientific poster (image, PDF, or text extraction)
• Any accompanying abstract or oral presentation slides
• Context on the therapeutic area and why this poster is relevant
• Target format for the summary (e.g., one-page brief, structured extraction, bullet-point format)
• Audience for the summary (e.g., medical affairs team, client account lead, publications group)

Steps

1. Obtain the full poster

   Ensure you have access to the complete poster content, not just the abstract. Check that any embargoed data has been cleared for processing.

2. Extract structured content

   Use PosterLens to extract key information (study design, endpoints, results, conclusions) into a structured format.

3. Review the extraction against the poster

   Verify that PosterLens has accurately captured the poster content. Pay special attention to data from figures, tables, and footnotes, as visual elements are the most common source of extraction errors.

4. Draft the summary

   Using the structured extraction as source material, draft the summary in the required format. Match the depth and framing to the target audience.

5. Verify every data point

   Confirm every number, endpoint, and finding in the summary matches the original poster exactly. Check Kaplan-Meier curves, forest plots, and waterfall plots manually.

6. Add context and finalise

   If required, add brief therapeutic area context. Clearly distinguish between information from the poster and contextual information you have added. Confirm the summary is appropriate for the target audience.

Output

A good poster summary runs 200–500 words for a single poster, follows a consistent structure (poster reference, study design, population, primary results, secondary results, safety, conclusions, significance), and contains exact data points from the poster. It distinguishes between presented results and the authors’ interpretation, and explicitly notes whether safety data was or was not presented.

Prompt pattern

You are a medical writing assistant. Your task is to create a summary of the following scientific poster presentation.

Format the summary with these sections:
- Poster reference (authors, title, congress, poster number)
- Study design and objective
- Key population characteristics
- Primary results
- Secondary / additional results
- Safety findings (if presented)
- Authors' conclusions
- Relevance / significance (brief — what this adds to the field)

Source material:
[INSERT POSTER CONTENT OR POSTERLENS EXTRACTION]

Target audience for this summary: [SPECIFY]
Target length: [SPECIFY — e.g., 300 words, one page, bullet-point format]

Rules:
- Base the summary only on what is presented in the poster. Do not add data from other sources.
- Reproduce data points exactly as presented.
- If safety data is not presented on the poster, note this explicitly rather than omitting the safety section.
- Flag any data points that are unclear or difficult to read in the source with [VERIFY].
- Do not interpret results beyond what the authors state in their conclusions.

Customisation: For congress coverage of multiple posters, use a consistent template across all summaries so stakeholders can compare them easily. Adjust the target length and detail level based on whether the summary is for a highlights report (shorter) or detailed briefing document (longer).

Why this works

AI rapidly extracts and organises structured data from visually complex poster layouts, handling the mechanical work of pulling study design, results, and conclusions into a consistent format. The human writer then verifies data accuracy (especially from figures), selects what to emphasise for the audience, and contextualises the findings within the broader congress and evidence landscape. This enables same-day congress coverage at a quality level that manual-only approaches struggle to match.

Common mistakes

Misreading data from figures

A Kaplan-Meier curve shows median PFS of 11.2 months, but the extraction reads it as 12.1 months from the figure. This incorrect number enters a congress highlights report sent to 30 stakeholders. Verify every data point from figures and tables against the original poster manually.

Missing data encoded in visual elements

Waterfall plots, forest plots, and complex tables contain key results that extraction tools miss because the data is encoded visually rather than as text. Open the original poster and manually check all figures, tables, and footnotes.

Dropping qualifiers from results

The poster reports “a numerical trend toward improvement (not statistically significant).” The summary states “improvement was observed.” The qualifier vanishes. Compare every result statement against the poster’s Results and Conclusions sections.

Overlooking safety data on the poster

A safety table in a lower panel gets missed by the extraction. The summary reports no safety data when data was in fact presented. Explicitly scan the full poster for AE tables, safety narratives, discontinuation data, and deaths.

Cross-contamination across posters

When summarising 15 posters from a congress, data from Poster #7 leaks into the summary of Poster #8 because AI processes them in sequence. Summarise one poster at a time in separate sessions and verify each against its specific poster.

Tool stack

Tool	Role
PosterLens	Structured extraction of poster content from images and PDFs
PubCrawl	Find related publications or trial registry data alongside the poster

Alternatives: Claude or ChatGPT for drafting summaries from extracted poster content. Napkin for creating visual summaries of poster data for internal distribution.

Review checklist

Human review checklist

• Poster reference (authors, title, congress, poster number) is correct
• Study design is accurately described
• Population characteristics match the poster
• All data points are verified against the original poster
• Results from figures and tables are accurately captured
• Safety data is included (or noted as not presented)
• Authors’ conclusions are correctly represented
• No data from other posters or sources has been mixed in
• Summary format and length meet the project requirements
• Summary is appropriate for the target audience

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Next steps: Use the summary to Extract Study Data or Extract Key Messages, then Repurpose Across Channels for different deliverable formats.

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Last reviewed: 15 April 2026