Beyond Controlled Vocabulary: The Case for Regulatory Reasoning

Beyond Controlled Vocabulary: The Case for Regulatory Reasoning

For decades, our industry has grappled with the challenge of consistent, compliant data. The solution, for a long time, was the controlled vocabulary. And don’t get me wrong, it was a massive leap forward. Before controlled vocabulary, we faced metadata chaos – free-text fields, endless variations for the same concept, and the sheer impossibility of aggregation or automation. The shift to picklists and predefined terms brought order, consistency, and the foundation for structured submissions.

But here’s the thing: I’ve spent the last several years building technology and delivering consulting engagements that process hundreds of submissions across global health authorities. What I’ve seen, time and again, is that while controlled vocabulary solves the problem of “is this term valid?”, it consistently fails to answer the more critical question: “will this term get accepted by this authority, for this submission type, at this point in time?”

This isn’t a minor distinction. The gap between a term being merely “valid” according to a static list and it being truly “effective” in a specific regulatory context is where regulatory teams spend an enormous amount of time, experience countless headaches, and often face unnecessary queries or delays. We treat vocabulary as a configuration problem – pick the right term from the right picklist. I believe it’s an intelligence problem, and it’s time our tools reflected that.

The Vocabulary Ceiling: Why “Valid” Isn’t Enough Anymore

Think about the journey of a regulatory professional. They’re not just looking for a technically correct term. They’re navigating a complex web of jurisdictional preferences, historical precedents, and constantly evolving guidance. A traditional controlled vocabulary system, no matter how well-maintained, hits a ceiling when faced with this reality.

Here’s what I mean:

• Jurisdictional Nuance: A term like “film-coated tablet” might be perfectly valid by global standards, but it might carry slightly different connotations or preferred synonyms for the EMA versus the FDA. A system that only says “yes, this is a valid dosage form” misses this critical nuance. We’ve seen instances where a perfectly valid term, when used in a specific submission type for a particular authority, consistently generated clarification requests, while a functionally identical synonym sailed through.
• Performance Patterns: Does your controlled vocabulary know that a specific route-of-administration and dosage-form combination has historically generated an above-average number of queries from the PMDA for a certain product type? Of course not. It’s designed for validation, not for learning from past interactions. This kind of pattern recognition – understanding what works and what doesn’t in practice – is pure tribal knowledge today, locked in the minds of experienced regulatory leads.
• Dynamic Evolution: Health authority standards are living documents. A term you used correctly and successfully in a 2022 submission might be quietly deprecated in a 2024 EDQM update. Your static controlled vocabulary might eventually get updated, but does it automatically flag three in-flight submissions that are affected by this change? Does it tell you the impact on your entire portfolio? Typically, this requires a painstaking, manual audit, often discovered reactively during a late-stage review.

These aren’t hypothetical scenarios; these are the real-world challenges we hear about constantly from our clients. They highlight the fundamental limitation of treating vocabulary as a static set of rules rather than a dynamic, context-aware intelligence layer.

“The gap between a term being merely ‘valid’ according to a static list and it being truly ‘effective’ in a specific regulatory context is where regulatory teams spend an enormous amount of time, experience countless headaches, and often face unnecessary queries or delays.”

What Regulatory Intelligence Actually Looks Like: Building the Future

When we started DnXT, we knew we had to go beyond merely managing controlled vocabulary. We needed to build a system that could reason, learn, and guide. This meant engineering a new kind of regulatory intelligence fabric. Here are five capabilities we’ve been building and refining:

1. Semantic Ontology: Concepts, Not Just Terms

At the heart of true regulatory intelligence is a robust semantic ontology. We don’t just store terms; we store concepts. A canonical identity for “oral tablet” isn’t just a string of characters; it’s a concept that can be cross-mapped to its equivalent in NCI Thesaurus, EDQM, SPL codes, and MedDRA, among others. This concept is then dynamically resolved to the precise, preferred term based on the specific health authority, submission type, and even the phase of development. This foundational layer allows us to understand the relationships between terms, not just their individual validity. It’s about moving from flat lists to a rich, interconnected web of meaning.

2. Jurisdiction-Aware Resolution

One of the biggest pain points for global teams is the variability in acceptable values across jurisdictions. Our system is designed so that the “valid values” for any given data element – whether it’s a dosage form, route of administration, or even a regulatory activity type – depend dynamically on the jurisdiction (FDA, EMA, PMDA, etc.), the specific submission type (eCTD, IND, NDA), the phase of development, and even the document type within a submission. Instead of maintaining separate picklists for each scenario, our single concept engine resolves to the correct, context-specific value set in real time. This dramatically reduces errors and ensures compliance with granular local requirements without manual cross-referencing.

3. Living Vocabulary: Learning from Submission History

This is where intelligence truly comes into play. Our system learns from your organization’s entire submission history. It’s not enough to know what terms are valid; we need to know what terms are effective. The living vocabulary surfaces patterns across your portfolio: which term combinations generate the most queries from specific health authorities? Which choices deviate from established internal practice or common industry usage? By analyzing past interactions, the system can identify high-risk choices and proactively suggest alternatives, transforming reactive problem-solving into anticipatory guidance. This turns your historical data from an archive into an active learning engine.

4. Change Propagation: Impact Reports, Not Manual Audits

When a health authority updates a standard – a new version of the EDQM standard, a change in NCI Thesaurus, or an update to an SPL code list – the impact can be far-reaching and difficult to trace. Our system leverages its semantic ontology to automatically trace that change through the entire regulatory landscape. It can identify every affected concept, every record, every document, and every in-flight or planned submission across your portfolio. Instead of a manual audit that takes weeks, you get an immediate, comprehensive impact report. This capability is absolutely critical for maintaining continuous compliance and understanding your exposure to evolving regulations.

5. Authoring Intelligence: Guiding Towards What’s Right

Ultimately, the goal is to make it easier for regulatory professionals to get it right the first time. Our authoring intelligence drives the creation experience in real time. As a user types or selects, the system provides intelligent suggestions. These aren’t just alphabetically sorted picklist entries; they are ranked by jurisdictional validity, historical precedent within your organization, and even the likelihood of acceptance based on our aggregated industry data. The system guides authors towards what’s not just valid, but what’s most likely to be accepted, preventing errors at the source rather than merely validating them later.

The Corpus Advantage: Fueling Regulatory Intelligence

What truly separates regulatory intelligence from sophisticated software is the underlying signal – the data that powers the learning and reasoning. At DnXT, we’ve had the unique opportunity to build this intelligence layer by processing a massive and diverse corpus of regulatory data. To date, we’ve processed over 340 submissions across more than 20 customers, spanning major global authorities like the FDA, EMA, PMDA, NMPA, Health Canada, and TGA.

This extensive, anonymized corpus provides an unparalleled advantage. It allows our system to develop pattern recognition at a portfolio scale that no single company could ever build internally. We see trends in queries, authority preferences, and successful terminology usage across a broad spectrum of products, therapeutic areas, and submission types. This aggregated insight is the secret sauce that transforms our ontology from a static map into a truly living, learning regulatory intelligence fabric.

“This aggregated insight is the secret sauce that transforms our ontology from a static map into a truly living, learning regulatory intelligence fabric.”

What This Means for Regulatory Teams

Moving beyond a simple controlled vocabulary to a true regulatory intelligence system has profound implications for regulatory teams:

• Shift from Reactive to Anticipatory: Instead of reacting to queries or discovering non-compliance during a critical review cycle, teams are notified of affected assets and potential issues before they even begin an audit or author a new document.
• Democratized Knowledge: New staff members or those working in unfamiliar jurisdictions get the right options and context-specific guidance in real time, reducing reliance on tribal knowledge and accelerating onboarding.
• Reduced Rework and Delays: Inconsistencies, deviations from best practices, or problematic term combinations are flagged during authoring, not at late-stage review, saving countless hours of rework and preventing submission delays.
• Enhanced Strategic Planning: With a clearer understanding of regulatory trends and potential challenges, teams can make more informed strategic decisions about market entry, product development, and portfolio management.

This isn’t just about efficiency; it’s about elevating the role of regulatory affairs from a compliance function to a strategic partner. It’s about empowering teams with the insights they need to navigate an increasingly complex global landscape with confidence and precision.

Ready to Experience Regulatory Reasoning?

The future of regulatory operations isn’t just about managing data; it’s about understanding it, learning from it, and using it to drive better outcomes. We’ve built the Regulatory Intelligence Fabric to do exactly that. If you’re ready to move beyond the limitations of controlled vocabulary and harness the power of true regulatory intelligence, we’d love to show you how.

Contact us today to See the Regulatory Intelligence Fabric in Action.