Ferma for Scientific Communications
AI agents that map the evidence landscape, cover every congress, and track what is coming next, so your team owns the scientific conversation.
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Clinical readouts, regulatory decisions, and competitive moves reshape the scientific narrative every week. Emerging biotechs surface faster than any team can brief them. China went from marginal to the largest origin of global pipeline and publication output in five years. The volume of signal is compounding. The teams processing it are not.
Your team spends weeks analyzing conference readouts, pipeline movements, and investor reports to assemble one publication or congress briefing. The tools provide raw ingredients but do none of the synthesis. PoS, endpoint specifics, competitive positioning: the nuances that determine narrative quality take hours to synthesize for a single asset.
And while your team is still assembling scientific briefings, nimble competitors are already publishing, presenting, and briefing KOLs. When a narrative window closes, there may not be another. Compressed timelines force decisions on incomplete work, raising the risk of losing narrative ground or missing scientific nuance entirely. A delayed story is a lost opportunity.
You define the objective. Each agent delivers a finished workflow: an evidence gap map, a congress readout, a catalyst forecast, or an MSL synthesis. Every output is cited, formatted for committee review, and exportable to PowerPoint, Excel, or PDF.
Every agent pulls from preclinical, clinical, commercial, and regulatory sources. Your methodology encodes the plan; the agent runs the workflow against it and cites every claim to source.
You validate the output, refine the plan, iterate. Agents handle the grunt work. You own the deep work.
Most platforms make you the integration layer. One database for trials, another for publications, a third for regulatory signals, hours spent stitching them together. Ferma resolves every data point to a core entity, so clinical results, publication history, and competitive narrative context all link at the asset level. One query, full picture.
Ferma's agents aren't built by engineers guessing what Scientific Communications teams need. They're co-designed with practitioners who have led publication plans and congress strategy at the world's largest biopharma companies.
Which data to pull, how to weight it, what thresholds matter, when to flag a risk. The implicit judgment that lives in your team's heads, made explicit and encoded into every agent.
How to map published evidence against a scientific story, surface white spaces, and score where your team can lead.
Which endpoints matter for a given TA. How to structure a publication comp. What drives an audience reach model.
Epidemiology inputs, audience reach benchmarks, narrative adoption curves, and PoS by phase. Validated against real publication and congress outcomes.
Scoring dimensions, report structures, and deliverable formats that mirror how stakeholders actually make decisions.