An AI literature review system for biotech reads papers, preprints, patent filings and trial registries on a schedule, and reports what changed for your targets, modalities and competitors, with every finding linked to the passage it came from. It is a monitoring and mapping tool. The judgement about what a finding means stays with your scientists and your patent attorney.
The hard part is not summarising. It is coverage across vocabularies: a competitor’s patent claims a “binding agent” where your team says “antibody”, a preprint describes your target under a gene alias, a trial registration names the compound only by an internal code. Keyword alerts miss these. Retrieval built on embeddings, synonym expansion and entity resolution across PubMed, bioRxiv, Espacenet, the USPTO, WIPO PATENTSCOPE, ClinicalTrials.gov and the EU CTIS is what catches them.
If what you need is evidence extraction from published trial reports, such as cohorts, endpoints and adverse events into a table, that is covered on our life-sciences research page. This page is about the strategic picture: who holds what, who is running what, and what was published this week.