Traditional compliance treats regulations as checklists applied after systems are built. We believe compliance should be executable, testable, and embedded directly into healthcare data systems. Building on our experience validating ACMG guidelines in AnFiSA, we’ve pioneered approaches that transform regulatory requirements from static documents into living code that governs data processing. This shift from “documenting compliance” to “computing compliance” fundamentally changes how healthcare organizations approach regulatory challenges.

The gap between regulatory text and technical implementation creates massive inefficiencies. Organizations interpret requirements differently, auditors struggle to verify implementation, and every regulatory change triggers manual system reviews. Meanwhile, clinical guidelines published as PDFs cannot be systematically validated against actual practice. Whether implementing Five Safes principles in TREs, ensuring GDPR-compliant data flows, meeting EHDS technical specifications, or validating clinical decision support against medical guidelines, the pattern repeats: human interpretation of rules that should be computationally precise.

Our Domain-Specific Language approach makes compliance computational. By expressing regulatory requirements and clinical guidelines in formal yet accessible languages, we enable automated validation that systems implement requirements correctly, continuous testing that compliance is maintained as systems evolve, transparent documentation generated from actual implementation, and rapid adaptation when regulations change. From genomic interpretation rules to TRE security policies, from data quality frameworks to clinical pathways, our methodology ensures that what’s required is what’s built. This evolution from reactive compliance to proactive, embedded governance provides healthcare organizations with the confidence that their systems don’t just claim compliance—they compute it.