From scientific literature
to a referenced draft.
A generative AI workflow turns scientific sources into evidence-based drafts, ready for expert review and final editing.
Medical affairs teams at a pharmaceutical company
The challenge
In the pharmaceutical industry, medical affairs teams create high-quality, evidence-based documents that demonstrate the safety and efficacy of new treatments. This takes time-intensive work:
- Searching literature databases
- Screening abstracts for relevance
- Extracting metadata (authors, journals, dates)
- Summarising and structuring scientific findings
- Making sure every claim is correctly referenced
Creating one coherent narrative from fragmented sources could take several days of manual work, especially when tailoring the content to diverse audiences, from clinicians and researchers to patients and stakeholders.
The solution
Common Sense AI developed a generative AI solution that automates the end-to-end workflow of evidence generation for medical affairs teams.
Built on large language models (LLMs), the solution supports:
- Automated generation of search terms for literature databases
- Abstract screening and filtering for relevance
- Metadata extraction from publications
- Drafting of scientifically accurate, well-structured content
- On-demand answers to targeted medical questions, with references
By integrating domain-specific knowledge into the AI pipeline, the tool turns raw literature into a polished, readable and referenced draft, ready for review and final editing.
The result
Work that previously took several days can now be done in minutes.
- Greater consistency in scientific writing and referencing
- More strategic focus for medical teams, shifting effort from manual processing to high-value analysis
- Better responsiveness, with on-demand summaries, comparisons and claims across therapeutic areas
The project shows how generative AI can transform medical content creation: faster workflows, more accuracy, and faster, better-informed communication across the pharmaceutical sector.