You evaluate pipelines and market risk across many companies from the outside. ClinicaLister turns days of manual diligence into a sourced company dossier your AI assistant assembles in minutes. IP-cliff analysis is the one thing it cannot give you — the patent and exclusivity data is too sparse to be honest about, and the limitations say exactly how sparse.
The highest-leverage things ClinicaLister does for a investor / bd analyst.
Every recurring activity, mapped to what ClinicaLister does — on which surface (the App, the MCP graph, or both), the time it saves, and how confident that claim is.
| Activity | What ClinicaLister does | Surface | Time saved | Confidence |
|---|---|---|---|---|
| Deal sourcing / screening a therapeutic area | See which indications are crowded and which are white space, ranked by how many sponsors and trials compete in each. | Both | days of cross-ref → a density map in one pass | High |
| Pipeline due diligence on a target | Reconstruct a sponsor's entire pipeline — maturity, diversification, and termination or approval status — in a single rollup. | Both | whole pipeline in minutes vs a multi-day desk exercise | High |
| Competitive landscape for one asset | Map every competing molecule, trial, sponsor, and site around one asset without hopping between portals. | Both | full asset landscape without portal-hopping | High |
| Revenue-exposure proxy per asset | Medicare Part D spend and ASP give a public spend proxy per asset. The patent / loss-of-exclusivity half of this is NOT available — IP coverage is 4.4% / 1.8%, so no cliff timeline can be built. | Both | spend proxy only — no IP timing | Low |
| Market sizing / TAM proxy | Your AI assistant builds a per-drug Medicare revenue proxy as a first-cut read on market size. | MCP | Medicare revenue proxy per drug — not charted in the app | Medium |
| Comparable / benchmark analysis | Rank peers on approval speed and IP strength to build comparables without hand-assembling comps. | MCP | peer benchmarking without hand-built comps | High |
| Investment-thesis build | A sourced company brief pulls catalysts, IP, and competitive density into a bull/bear scaffold to build a thesis on. | MCP | bull/bear scaffold from sourced data | Medium |
| Catalyst / readout / approval tracking | Newly posted trials, sponsor activity, and severity-ranked alerts surface catalysts in hours, plotted on an approval timeline. | Both | catalysts in hours, not after the print | High |
| Biosimilar / generic threat assessment | See approved biosimilars and generics already on a reference moiety. This shows erosion that has HAPPENED; it cannot time erosion that has not, because exclusivity end-dates are on 1.8% of records. | Both | observed erosion, not a forecast | Medium |
| White-space identification | Surface under-competed indications to aim a new-company or in-licensing thesis at open fields. | Both | points a new-co / in-licensing thesis at open fields | High |
| Portfolio-holdings monitoring | One saved auto-following query watches a whole list of sponsors at once and alerts you to field-level changes — no re-running searches. | App | live watch on a watchlist, no re-runs | High |
| Red-team / risk assessment | Supply-chain shortage signals, safety flags, and protocol-change churn combine into a structured downside register. | Both | a structured downside register | Medium |
| One-shot company brief | Point your AI assistant at a public sponsor and get pipeline, competition, safety, regulatory, geography, and recent changes in one deliverable. | MCP | IC-ready dossier from a single ask | High |
Straight answers on where ClinicaLister stops today — so there are no surprises.
US payer proxy, not global TAM. Market sizing draws on US Medicare pricing and spend only — no commercial-payer, ex-US, or epidemiology-based market size, and it's a report your AI assistant builds, not a chart in the app.
No valuation or deal data. There are no cap tables, burn, revenue, deal terms, or multiples, and no private-company or pre-clinical financials — ClinicaLister surfaces the sourced evidence, but the model is yours.
A public-registry ceiling. Undisclosed deals, stealth-mode assets, and pre-registration programs are invisible — absence of data is not absence of activity.
Patent and exclusivity coverage is thin, and this is the honest number: of 29,777 FDA drug records we hold patents on 4.4%, exclusivity end-dates on 1.8%, and Purple Book patents on 0.05% (measured 2026-08-17). That supports a per-drug lookup where the data happens to exist — it does NOT support a portfolio patent-cliff or loss-of-exclusivity timeline, and we would rather say so than return an empty chart that reads as "nothing expiring". A full Orange Book / Purple Book feed is not yet ingested.
AI links are scored suggestions, not facts. Every trial-to-drug-to-patent link carries a confidence tier and its provenance; safety and shortage signals are candidates for your review.
Not a data terminal or API. There's no live feed or bulk export — output is synthesized reports refreshed through the day, with no earnings calendar or price and volume signals.
Point your AI assistant at any public sponsor and get a sourced pipeline, competition, safety and market-risk brief in minutes — with a Medicare spend proxy to size what each asset is exposed to.