Field notes from the translation layer.
Writing about clinical data management, CDISC standards, and the engineering of trustworthy agents. No gated PDFs, no webinar funnel.
Your enterprise AI is writing emails. It should be closing study builds.
Sponsors pay five figures a year for frontier-model access and point it at meeting notes. Nexus Assistant makes every CDISC-native TrialNexus agent callable from Claude, ChatGPT, or Gemini — with a Part 11 signature behind every approval.
Is your AI clinical trial tool actually 21 CFR Part 11 compliant? A checklist.
Most AI vendors claim Part 11 compliance. Here is what the regulation actually requires for AI-generated clinical data artifacts — and the questions to ask before you sign.
The SDTM submission errors that cause Pinnacle 21 failures — and how to prevent them
A breakdown of the most common SDTM conformance failures, why they happen, and what a prevention-first pipeline looks like.
What ICH E6(R3) actually requires for AI-assisted clinical data management
The GCP guideline finalized in January 2025 has specific implications for sponsors using AI tools in their data management pipeline. Here is what changed and what it means.
Agentic AI in clinical trials: what it actually means for your data management team
The term is everywhere. Here is a precise definition, what agentic AI can and cannot do in a regulated trial, and how to evaluate a platform that claims it.
Why "human in the loop" is the only viable model for AI in regulated clinical trials
Autonomy and compliance are not opposites — but getting both requires an architecture that most AI tools have not built. Here is what the compliant version looks like.
Why USDM v4.0 is the most important standard in clinical trials — and why nobody is talking about it
A walkthrough of the Unified Study Definitions Model and what changes when protocols are machine-readable by default.
Building an audit trail you would actually show a regulator
How we designed immutable provenance records on top of Postgres, and the tradeoffs we made for Part 11.
The agency dial: how to give agents responsibility without losing oversight
The user-interface primitive we keep coming back to, and why it matters more than any model benchmark.
What goes wrong in a 68-day study build — a timeline from a real DMP process
Anonymized cycle-time data from conversations with DM leads at six mid-size sponsors.
SDTM mapping is pattern-matching with consequences
Why LLM-assisted SDTM mapping is hard, where it works, and where it should never be autonomous.
Introducing TrialNexus — people were never meant to be middleware
Our founding post. Why we think the next ten years of clinical data management belong to agent-based pipelines.
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