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What you get

A recurring brief covering what appeared in the literature about your products, your competitors’ products, and the mechanisms behind them — filtered down to the items that matter, with an explicit empty state when nothing does.

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Who it’s for

Commercial, medical affairs, and competitive-intelligence teams in life sciences, and consultancies running this on behalf of clients. Also the shape used by companies building literature monitoring into their own product.

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How it works

1

Build the watchlist from mechanisms, not just brand names

Brand names are unreliable in the literature — papers name the molecule, the device class, or the mechanism. Query all of them: brand, generic or molecule name, device category, and the underlying mechanism.
2

Add the competitor and author axes

Once you know which authors publish in the space, track their names as queries in their own right. Shifts in who publishes often precede shifts in what is published.
3

Window and diff

Set year_min and month_min to the last run. Diff on doi against stored state so the brief contains only what is new.
4

Interpret, do not list

For each new paper, say what it implies — a competitor’s program stage, a safety question, a comparator result. Flag changes in venue, geography, or collaborator.
5

Escalate on signal type, not volume

Route safety findings and head-to-head comparisons to a human immediately. Everything else can wait for the weekly brief.

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The API call

Useful narrowing for this workflow:

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Turning it into a product

Several customers resell this. If that is the shape you are building:
  • The API is per-integration, not per-user. One x-api-key covers your service; your own users never need Consensus accounts.
  • Size the plan against request volume. A watchlist of 50 entities refreshed weekly, paginated, runs into the thousands of requests a month.
  • Cache on the full parameter set. Two clients watching overlapping mechanisms will issue near-identical queries.
  • Pass the url through. Every result links back to the paper on Consensus, which is the citation trail your users need.

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What to check before you trust it

  • Brand-name-only watchlists miss most of the literature. Verify by searching the molecule and mechanism separately and comparing volume.
  • Alert when a run returns nothing across the whole watchlist. That is usually a broken job, not a quiet week.
  • Short brand names collide. Spot-check any entity producing unusually high volume for unrelated hits.
  • The brief must have an empty state and use it. A monitor that always finds five things trains people to ignore it.

Track new papers across many topics on a schedule

The engineering underneath: pagination, diffing, backoff.

Build a drug target validation dossier

Go deep on a mechanism the monitor surfaced.

Best practices

Diff-against-last-run and the rest of the primitives.

All use cases

Browse the gallery by persona.