Clinical evidence synthesis uses AI agents to read new trial results, safety data and published studies, and draft a cited brief that shows consensus findings and gaps for your clinicians to review.
An agent in H2O AI Super Agent gathers trial results, safety data and published studies on a drug or condition and drafts one structured brief with a citation for every finding.
The brief separates consensus findings from open questions, such as thin evidence for a patient subgroup, so reviewers see the gaps as well as the answer.
Clinical evidence synthesis is decision support: it changes where your clinicians and pharmacists start, not who decides.
Enterprise h2oGPTe runs in four deployment options, on-premises, air-gapped, private cloud and cloud, so internal documents and any protected health information stay inside the boundary you choose.
Keep your formulary and care pathways current with the evidence
New trial readouts, label updates and journal articles arrive every week. Your pharmacy and therapeutics committee, clinical decision support team and research department each need the current picture before they update a formulary, an order set or a care pathway.
Questions people ask before they call us.
It is the use of AI agents to collect clinical trial reports, regulatory documents and published studies, extract efficacy and safety findings, and summarize them in one cited brief that shows consensus findings and gaps. Clinicians review the brief and make the decisions.
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Today someone reads each source by hand, copies efficacy and safety findings into a spreadsheet and writes a summary. That work takes days, and a summary without a source for each claim is hard for a committee to trust.
The gaps matter as much as the findings. Your reviewers need to know which populations a trial did not cover and where the evidence is thin, before a recommendation reaches a clinician.
How AI clinical evidence synthesis works
An agent in H2O AI Super Agent plans the research, searches the sources you allow, reads each document, and writes a structured brief that your team reviews and edits.
Step 1: define the question
Your reviewer states the drug, condition or guideline question, the outcomes that matter and the sources to trust. The agent turns that request into a research plan, which you can approve or change before it runs.
Step 2: gather and read the evidence
The agent searches published trial reports, regulatory documents and journals, plus your own collections such as prior committee reviews and internal protocols. Retrieval-augmented generation keeps every statement tied to the passage it came from.
Step 3: extract and compare findings
The agent pulls efficacy endpoints, adverse events and study design details into a comparison table, then marks where studies agree, where they conflict and which subgroups have little data.
Step 4: draft the brief for human review
The agent writes an evidence summary with a limitations section and a citation for each claim. Visible sources help your reviewers catch errors before anything is used.
Step 5: publish into your decision support process
After your clinicians approve the brief, it can feed the clinical decision support content your electronic medical record already uses. The agent can repeat the scan on a schedule, so the brief refreshes when new evidence appears.
Evidence synthesis is decision support, not a clinical decision
The agent prepares the evidence. Your clinicians and pharmacists still decide what changes in a formulary, order set or care pathway. Enterprise h2oGPTe runs in four deployment options, on-premises, air-gapped, private cloud and cloud, so internal documents and any protected health information stay inside the boundary you choose.
