In regulated software, a false success is worse than a crash. Three real silent-failure stories from our own platform, the engineering discipline that eliminates them, and what buyers should ask vendors.
Audit preparation should not be a three-week fire drill. How continuous readiness scoring, one-click audit packs, and mock inspection mode turn inspection prep into a standing capability.
Most ‘AI search’ in regulatory software is keyword matching with a chat interface. Here is what true vector retrieval looks like, why citations are non-negotiable in GxP, and how we proved ours works.
DnXT’s auto-assign engine places documents into eCTD sections using patterns mined from 3,081 real sequences — deterministic first, AI last, and every placement explainable.
We studied 14 real NDA-program tracking spreadsheets before building DnXT’s document tracking grid. Here is what Excel gets right, where it breaks, and what replaces it.
How DnXT models multi-market submissions: a global core template, market variants that inherit and diverge deliberately, and a variance ledger that shows every difference at a glance.
Generic regulatory news feeds create triage debt. DnXT scores every guidance, approval and safety action against your actual portfolio — so surveillance becomes signal, not noise.
DnXT’s Predictive HAQ Readiness forecasts the health authority questions your submission is most likely to receive — before you submit — grounded in analysis of 1,000+ real agency questions.
A practical playbook for responding to FDA information requests: triage, discipline routing, drafting, QC — and where AI genuinely helps without crossing the GxP line.
Grouped submissions let one sequence serve multiple related FDA applications. Here is how the mechanics actually work — shared files, member sequences, metadata mirroring, and cumulative views.
