The pharmaceutical industry is entering a new era of Medical, Legal, and Regulatory (MLR) review. As life sciences organizations produce more content across more channels—and face growing pressure to move that content through review faster—traditional workflows are struggling to keep pace.
Artificial intelligence is beginning to change that equation. But the next evolution of AI-powered MLR isn't simply about adding an AI assistant to an existing review process.
It's about agentic AI: intelligent systems capable of performing specialized compliance tasks, coordinating information, identifying potential risks, and supporting reviewers throughout the MLR lifecycle.
At ERMA Systems, we're helping shape this next generation of pharmaceutical review.
What Is Agentic AI for MLR?
Traditional AI tools typically respond to individual prompts or perform isolated tasks. Agentic AI goes further.
An agentic MLR environment can use specialized AI agents to perform different functions within the review process—evaluating claims, finding supporting references, applying regulatory guidance, identifying potential compliance issues, and helping reviewers understand why something may require attention.
Rather than asking AI one question at a time, organizations can build AI into the workflow itself.
For pharmaceutical MLR teams, this creates an opportunity to move from AI assistance to AI-powered orchestration.
ERMA is designed around this concept.
Moving Beyond Basic MLR Automation
Many pharmaceutical organizations have already digitized their MLR workflows. Documents can be uploaded, routed to reviewers, annotated, approved, and archived electronically.
But digitizing a workflow is not the same as making it intelligent.
Reviewers still spend significant time performing highly manual work:
- Identifying promotional claims
- Finding and validating supporting references
- Reviewing references against claims
- Checking content against FDA guidance
- Identifying inconsistencies across materials
- Reviewing previous annotations and decisions
- Comparing versions
- Preparing materials and documentation for submission
ERMA introduces an AI intelligence and compliance layer designed specifically around these activities.
Instead of simply moving documents from one reviewer to another, ERMA helps analyze the content moving through the workflow.
An AI Compliance Operating System for Life Sciences
ERMA is being built as an AI compliance operating system for life sciences—from development through commercialization.
Within promotional review, that means bringing together specialized capabilities that traditionally exist across disconnected processes.
AI-Powered Claims Detection
ERMA uses AI to identify potential claims directly within promotional content.
Rather than relying solely on predefined lists of claims, the system analyzes the material itself to identify language that may represent efficacy, safety, comparative, product, or other relevant promotional claims.
This gives reviewers an intelligent first pass before manual review begins.
Agentic Reference Assignment
Finding the correct substantiation for a promotional claim can be one of the most time-consuming parts of MLR preparation.
ERMA's agentic approach is designed to evaluate claims against available references and help identify relevant supporting evidence.
This can transform reference management from a manual search exercise into an intelligent process where AI helps connect the claim, the evidence, and the reviewer.
FDA Regulatory Intelligence
Agentic MLR also requires regulatory context.
ERMA incorporates FDA-focused intelligence designed to help evaluate content against applicable regulatory considerations, including promotional guidance and enforcement patterns from organizations such as the FDA's Office of Prescription Drug Promotion (OPDP).
The objective isn't to replace regulatory professionals. It is to give them a system capable of surfacing relevant information earlier so their expertise can be focused where it matters most.
Agentic AI Doesn't Replace the MLR Reviewer
One of the most important distinctions in ERMA's approach is the role of the human reviewer.
Pharmaceutical promotional review requires judgment.
Medical reviewers evaluate scientific accuracy and context. Legal reviewers assess risk. Regulatory professionals interpret guidance, precedent, labeling, and promotional requirements.
Agentic AI can augment that expertise by doing more of the investigative work surrounding the decision.
The future of MLR isn't AI instead of reviewers.
It's AI working alongside reviewers.
That distinction is critical.
ERMA is designed to help reviewers identify issues faster, understand the supporting evidence, and make informed decisions while maintaining appropriate human oversight and auditability.
Creating a More Intelligent MLR Workflow
Imagine a promotional asset entering an MLR workflow.
Instead of waiting for reviewers to manually identify every potential issue, an agentic system can begin working immediately.
It can identify claims within the material, search available references for supporting evidence, evaluate relationships between claims and references, surface relevant regulatory considerations, and flag areas requiring human attention.
By the time the material reaches the reviewer, much of the preliminary analysis has already been performed.
The reviewer isn't starting from zero.
They're starting with intelligence.
That is where agentic AI has the potential to fundamentally change MLR.
Working With Existing Pharmaceutical Technology
The future of pharmaceutical technology is unlikely to be defined by a single platform.
Many organizations already have substantial investments in content-management and promotional-review infrastructure, including systems such as Veeva Vault PromoMats.
ERMA is designed to operate either as a standalone MLR platform or as an AI intelligence layer alongside an organization's existing technology environment.
This approach allows organizations to explore agentic AI without necessarily replacing their established system of record.
The intelligence layer becomes the differentiator: analyzing content, claims, references, regulatory considerations, and review information while existing enterprise systems continue performing their established functions.
From Drug Development to Commercialization
The opportunity for agentic regulatory intelligence also extends beyond promotional review.
Many of the same fundamental challenges exist throughout the pharmaceutical lifecycle: enormous volumes of scientific information, complex regulatory requirements, extensive documentation, and highly specialized human review.
ERMA's broader vision extends from drug development through commercialization, creating an AI-powered compliance environment capable of supporting life sciences organizations across the product lifecycle.
That includes applications spanning clinical and regulatory documentation, submission readiness, reference validation, promotional review, and post-approval compliance activities.
The underlying idea remains consistent:
Give life sciences professionals intelligent agents capable of analyzing information before it reaches the human decision-maker.
Why Agentic MLR Matters Now
The amount of pharmaceutical content being created is increasing rapidly.
At the same time, organizations are being asked to operate faster without compromising regulatory standards.
Simply adding more reviewers is difficult to scale.
AI creates another option.
When implemented responsibly, agentic AI can help organizations reduce repetitive work, surface potential compliance issues earlier, improve consistency, and allow experienced reviewers to spend more time on the decisions that actually require human expertise.
That can ultimately create a different operating model for MLR—one where AI isn't an occasional tool used during review, but an active participant throughout the workflow.
ERMA's Vision for the Future of MLR
We believe the next generation of MLR technology will move beyond workflow management.
It will understand the content inside the workflow.
It will understand claims.
It will understand references.
It will understand regulatory context.
And it will bring those elements together before asking a human reviewer to make the final decision.
That is the direction ERMA Systems is building toward.
As agentic AI continues to mature, MLR teams have an opportunity to fundamentally rethink how pharmaceutical content is reviewed—not by removing human expertise from the process, but by surrounding that expertise with significantly better intelligence.
The future of MLR isn't simply automated. It's agentic.
And ERMA Systems is building the infrastructure to help life sciences organizations get there.