Illustrative scenario

Generating TLF Packages Against Locked ADaM Data Without the Full Contract Biostatistics Bill

Between SAP lock and submission deadline, a biostatistics team at a mid-cap pharma is racing to produce hundreds of tables, listings, and figures — each mapped to a specific output shell in the eCTD package, each traceable to the locked ADaM dataset. At $500K–$5M per study in biostatistics spend, a meaningful share of that budget goes to R and SAS programming work that is deterministic once the SAP and ADaM specs are fixed.

Up and running in ~10 wkFor: Director Biostatistics, mid-cap pharma
Estimate your payback
~4 mo
Payback period
$3.3M
Est. savings / year
+$2.3M
Year-1 net

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

The TLF Production Bottleneck After SAP Lock

Contract biostatisticians are expensive because they carry both statistical judgment and programming execution. But once the SAP is locked and the ADaM datasets are clean, the production phase — writing programs, running them against data, and populating output shells — is largely a structured programming task. When that work bottlenecks on contract programmer availability, timelines slip and study costs climb. For a Director of Biostatistics managing multiple studies simultaneously, the backlog compounds.

An Agent That Programs Against ADaM Specs and Populates eCTD Shells

An AI Labor Company agent mines TLF shell and SAP review workflows from biostats team SharePoint and SAS code-review threads to understand each study's output specifications. It auto-generates R and SAS programs mapped against the locked ADaM datasets and populates the corresponding output shells in the eCTD data package. The Responsible Statistician reviews and approves each output before it is included in the submission — the agent handles the programming production cycle, not the statistical design or final review.

Faster Submissions and Recoverable Contract Budget

A 30% reduction in contract biostatistics spend per study is the direct cost case, but the more strategically significant outcome is submission timeline compression. Studies that move from SAP lock to TLF completion faster reach the review queue earlier, which in a competitive therapeutic area has real commercial implications. Teams in this position also find that freed programming capacity lets the statistical team take on more studies in parallel without proportionally expanding their contractor roster. The agent is typically live in ten weeks.

Questions

Does the agent require a specific programming language — R or SAS?

The agent can generate programs in either R or SAS depending on the study's specification. If the organization uses both, output preference can be set at the study or output level.

How does the agent handle ADaM dataset amendments after TLF production has started?

When a locked dataset is amended, the agent flags affected outputs, reruns the relevant programs against the updated data, and routes the revised outputs back to the Responsible Statistician for re-review. It does not silently propagate changes through already-approved outputs.

Related use cases

Illustrative scenario for healthcare, pharma & life sciences. 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