Illustrative scenario

Ship Sponsor Data Packages Faster with Automated CDISC SDTM Mapping

For the Head of Biostatistics at a mid-size CRO, the bottleneck between trial close-out and sponsor data package delivery is almost always the same: SDTM mapping is painstaking, Pinnacle 21 validation surfaces issues late, and the cycle repeats until the submission is clean. When annual MSA value runs $500K to $2M, delivery speed is directly tied to sponsor satisfaction and renewal probability. An AI agent changes the throughput math.

Up and running in ~16 wkFor: Head of Biostatistics, mid-size CRO
Estimate your payback
~4 mo
Payback period
$1.3M
Est. savings / year
+$900K
Year-1 net

Rough estimate — change the numbers to match your business. We scope the real figures with you on a call.

Where SDTM Mapping Slows Down

eCRF field mapping to CDISC SDTM domains is detailed, rule-bound work — each variable must be mapped to the correct domain, properly labeled, and validated against CDISC standards before Pinnacle 21 will pass the dataset cleanly. The manual workflow means biostatisticians review mapping specifications in parallel with SAS dataset builds, validation findings surface iteratively, and critical-finding waivers create back-and-forth with sponsors. On complex trials, this cycle absorbs weeks of senior biostatistician time that could be directed toward analysis.

How an AI Agent Handles the Mapping Workflow

An AI Labor Company agent mines SDTM mapping specification review emails and SAS dataset validation logs to learn your team's mapping patterns and waiver logic. A managed agent then auto-maps eCRF fields to CDISC SDTM domains, runs Pinnacle 21 validation checks on the resulting datasets, and queues only the critical-finding waivers that genuinely require your sign-off. Clean cases flow through without interruption; your biostatisticians spend time on the exceptions and the statistical analysis, not the mechanics of mapping. Teams running this workflow typically see it live in approximately 16 weeks.

Revenue and Capacity, Not Just Time Savings

This is a growth story as much as an efficiency story. When data package delivery accelerates by roughly 40%, a CRO can take on more concurrent trials without adding headcount — the same biostatistics team serves a larger study portfolio. Faster delivery also strengthens sponsor relationships and renewal rates, which are the real revenue engine of an MSA-driven business. The 55–75% reduction in manual mapping effort compounds: it shortens the timeline from trial close-out to sponsor delivery and frees senior staff for the analytical and regulatory work that commands the highest fees.

Questions

Can the agent handle both SDTM and ADaM dataset mapping, or just SDTM?

The initial workflow focuses on SDTM mapping, which is typically the higher-volume and higher-friction stage. ADaM derivation can be incorporated in a subsequent phase depending on your study mix and sponsor requirements.

How does the agent stay current with CDISC standard updates and FDA/EMA submission expectations?

AI Labor Company maintains the CDISC standard layer and updates the agent's mapping logic when new SDTM implementation guides are released. Sponsor-specific conventions are captured from your mapping specification history and applied consistently across studies.

Related use cases

Illustrative scenario for data, research & analytics. Figures are example ranges, not guarantees — we scope real numbers with you on a call.

Want this running in your business?

We'll scope an agent for this on a free 15-minute call.

Book a free call