For every eCRF, see how comparable studies built their edit checks. Know what you have, what's missing, and what to reuse — before SSU starts.
Stop guessing. Pull forward with confidence.
Every edit check in your last study was approved by someone. Do you know why they chose that logic over an alternative?
In many cases, it's because there wasn't time to go looking for a better answer. Over 60% of checks in a typical study are pulled forward from a reference study. The question is whether that reference was the best one available.
The goal isn't to change the workflow — it's to make sure every decision behind it is backed by evidence, not just whatever was easiest to find.
Vetryx surfaces the full landscape before your team commits — what comparable studies built, where the variation is, and what held up in production. So when your CDM makes that call, they're making it with everything your portfolio knows.
Don't settle just because of timeline pressure.
You don't know what you have going in. Without cross-study visibility, study-specific gaps aren't caught until the study is live.
Same program wide eCRF but different query behavior. Sites lose confidence and start ignoring legitimate checks.
Copied logic carries the wrong assumptions forward. Old thresholds and stale field references reach the next study unchanged.
CDM time spent on cleanup that should not exist. Hours resolving queries that could have been caught at build.
The same Vetryx evidence layer supports both sides of the workflow. Sponsors use it to strengthen reuse and standards. CROs use it to accelerate SSU without sacrificing quality.
Sponsors do not just need faster builds. They need to know whether teams are reusing the right patterns, where variation is happening, and which checks are ready to become stronger standards.
CRO teams are often asked to move fast with limited time to investigate what was done before. Vetryx gives teams a stronger starting point before specs get locked.
A form-level reference your team actually uses during build. Not a report that sits in a folder.
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No CDM, however experienced, carries cross-portfolio visibility across hundreds of checks and dozens of studies simultaneously. Vetryx does — and surfaces what that visibility reveals.
ALS exports, specification files, check logic across historical studies and programs — Vetryx reads the structure, not just the text.
Two checks written completely differently by two different programmers on two different studies get recognized as the same logical concept. That's not something a senior CDM with a spreadsheet can do quickly — and cross-study conceptual mapping across an entire portfolio isn't something Excel was built to do at all.
Across every study in your portfolio, simultaneously. Reuse rates, variation patterns, coverage gaps — at a scale no manual review process reaches, delivered before SSU begins.
The output is form-organized and filterable — not a prescribed answer. Pull up any form, see what comparable studies built, and go into SSU knowing what your data says.
See how comparable checks actually performed across your portfolio — not just what was built, but how it behaved. Query volume, resolution time, and re-query rates compared side by side across similar studies. The same check generating 40 queries in one study and 400 in another is the signal most teams never see before build begins.
Most tools tell you what checks exist. Vetryx tells you what was built and whether it worked. Pattern intelligence combined with real performance data from your own portfolio — that's not a report. That's the institutional knowledge your team has never been able to capture until now.
CDM is at the table during SSU planning. The eCRF scope is defined. Now every form-level decision needs a reference — not a guess, not the last study by default. Vetryx pins your portfolio behind that moment so your team builds with context, not just instinct.
Pull up any eCRF and see how comparable studies built their checks — what patterns exist, where gaps are, and what's ready to reuse.
Separate current-state risk from pre-production design decisions.
See where teams reuse, adapt, or recreate existing edit check patterns.
Measure edit check consistency across a program, indication, or portfolio.
Narrow by form, status, source, or criticality to prioritize review effort.
