Domain evaluation & red-teaming
Design realistic drug-development tasks, expert rubrics and failure taxonomies; run blinded review and produce an evidence-backed evaluation report.
REGULATORYX / AI ASSURANCE
Make AI useful in R&D— and credible in context
RegulatoryX is VED’s emerging US-based AI-assurance capability: expert-led evaluation for life-sciences AI companies and controlled workflow pilots for drug-development teams.
VED working method
- 01Evaluate
- 02Control
- 03Improve
01
TWO BUYING JOURNEYS
Evaluation for builders. Assurance for adopters.
Controlled workflow pilot
Select one valuable workflow, define context of use, configure human review and measure time, quality and risk before scaling.
02
INITIAL USE CASES
Start where expert judgement is visible
Regulatory strategy reasoning
Test whether an AI identifies material issues, uses relevant evidence and distinguishes fact, inference and recommendation.
Agency-question preparation
Evaluate question quality, sponsor-position logic, source use and handling of uncertainty.
Protocol and document quality
Detect contradictions, missing dependencies, unsupported claims and cross-document inconsistency.
Regulatory intelligence
Assess retrieval quality, jurisdiction, effective date, applicability and citation traceability.
Programme knowledge
Pilot source-grounded retrieval, decision logs and controlled reuse across an R&D programme.
Expert workflow simulation
Create realistic tasks and gold-standard reasoning from regulatory, clinical, biomarker, writing and data experts.
03
EVALUATION METHOD
A benchmark is more than an answer key
- Define the intended user, context of use, decision consequence and unacceptable failure
- Create representative, rights-cleared tasks and adjudicated expert rubrics
- Score accuracy, relevance, traceability, uncertainty, consistency and escalation behaviour
- Separate model failure from workflow, retrieval, source or human-review failure
- Document limitations, residual risk and the conditions for safe use
04
THE COMPOUNDING ASSET
From paid evaluations to defensible infrastructure
The long-term RegulatoryX opportunity is a permissioned library of expert-authored tasks, adjudication rubrics, failure patterns and workflow controls for drug development. It should be built from paid projects and explicit rights—not from speculative software development or confidential client documents.
Start with the constraint
What must your programme decide, prove or deliver next?
Share the situation, evidence and timing. We will propose the smallest credible first step.