Regulatory and MLR Operations
Every Medical Affairs and marketing team has a story about content that took months to approve and was out of date by launch. Slow MLR is rarely caused by one difficult reviewer. It is a design problem: unclear roles, missing standards, too many review rounds and systems that do not talk to each other across markets.
This theme covers how to make review faster and safer at the same time. Mapping who decides what. Setting service levels that hold. Building content taxonomies and reusable claims. Consolidating systems across markets. And using AI in MLR without creating new compliance risk.
What this theme covers
- Process design. RACI, review routes and service levels.
- Content standards. Taxonomy, modular content and approved claims libraries.
- Multi-market operations. Global-to-local adaptation without duplicate review.
- Systems. Veeva Vault and other review platforms, and how to configure them well.
- AI in review. Where AI helps reviewers, and where human judgement must stay.
Start here
Claims Library Checklist
14 checks to find out whether your approved claims are a filing system or a strategic asset. Instant score and a PDF to share. Free.
MLR Process Optimisation: Why Review Cycles Stall and What Fixes Them
The five causes of slow Medical-Legal-Regulatory review and the practical fixes, including where AI fits.
Related services
- MLR Process Optimisation: RACI mapping, SLA definition, content taxonomy, system consolidation and AI-readiness assessment.
- CRM & Technology Implementation Advisory: requirements, vendor evaluation and roll-out governance for Medical Affairs platforms.
FAQ
What is MLR review?
MLR (Medical, Legal, Regulatory) review is the process pharmaceutical companies use to check that promotional and scientific materials are accurate, balanced, supported by evidence and compliant with laws and industry codes before they are used.
How long should MLR review take?
It depends on content type and risk, which is why good processes set different service levels for different tiers of content. Low-risk adaptations of approved content should move in days. New claims and complex materials need more time.
Can AI be used in MLR review?
Yes, to support reviewers: checking references against claims, flagging inconsistencies, comparing versions and pre-screening against approved claims. Final judgement on accuracy, balance and compliance stays with qualified human reviewers.