Trial landscape scan
For a condition or intervention, pull every relevant registered trial into one notebook, sort by phase and status, and see the literature behind each one — a landscape read in an afternoon instead of a week of registry searches.
Turn a trial search into a documented pass. Pull registered studies by condition, intervention or population into a notebook, read them beside the papers written about them, and keep every detail — sponsor, phase, status — tied to its source.
Pull the registered trial record[1]
Read it beside the literature[2]
Search across everything you've collected[3]
File the review with sources attached[3]
What you can do
The concrete work behind "ai for clinical research" — not a feature list.
Search registered studies by condition, intervention or population and bring the record — sponsor, phase, status — into a notebook, not just a summary.
Pull the papers written about a trial into the same notebook, so its registered design and its published results sit next to each other.
Semantic search over trial records, papers and your own notes — find the detail without re-opening every record.
Export the summary to versioned storage alongside the underlying records, so the next review starts from the same file.
What it reads against
The reference collections this job draws on. Each is a page you can open and read before you trust a single answer.
Registered studies kept as registry records — with phase, sponsor and recruiting status intact — beside the literature.
Open-access research read in full — with the datasets a finding rests on kept alongside the write-up.
The settled account of a subject, read from the maintained entry rather than a copy of it.
Collections are libraries the workspaces read from, kept as what they are rather than flattened into one pile. See the full collection breakdown.
The stack under the work
Listed in the order the work moves through them, each carrying its live status.
Example workflows
For a condition or intervention, pull every relevant registered trial into one notebook, sort by phase and status, and see the literature behind each one — a landscape read in an afternoon instead of a week of registry searches.
Line up two or three trials on the same question side by side — population, endpoints, phase — and note where the designs actually differ, each detail tied to its record.
Questions
Different job? Browse every use case or start from your industry.
For clinicians
Request private access and we will walk through the workspaces this job runs on.
Browse the rest of the catalog at /apps.
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