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Catch common compliance issues before they reach the Medical, Legal, and Regulatory committee. MedCheckr scans near-final content for the language patterns that most often trigger MLR rejection, so you can submit cleaner documents and spend review time on harder judgement calls.

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The problem it solves

Every MLR rejection cycle costs time, budget, and credibility. Common rejection reasons — unsubstantiated superlatives, insufficient fair balance, language that implies off-label use, comparative claims without adequate substantiation — are pattern-based issues that can be caught before submission. MedCheckr runs a pre-MLR scan that flags these patterns in near-final content, giving writers and reviewers a structured list of items to address before the document enters the formal approval queue. The goal is cleaner submissions, fewer rejection cycles, and more productive MLR review sessions.

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How to use it

1

Prepare a near-final draft

MedCheckr is most effective on content that is close to submission. Run it after your standard internal review, not on rough first drafts where the language is still in flux.
2

Run MedCheckr

Submit the content for compliance signal scanning. MedCheckr reviews text for language patterns, claim structures, and framing that commonly raise concerns under pharmaceutical advertising codes and regulatory guidelines.
3

Review each flagged item in context

Not every flag is an actual issue. Some patterns are appropriate for certain content types or can be substantiated. Assess each flag against the specific document context.
4

Revise where needed

Address genuine compliance concerns in the content — revise superlative language, add fair balance, clarify indication-specific framing, or add substantiation where required.
5

Proceed to formal review

MedCheckr does not replace MLR review. Submit the revised content through your standard approval process with the MedCheckr output as a pre-review audit trail.

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What it does well

  • Flags superlative and comparative language that may require substantiation
  • Identifies potential off-label implications in claim framing
  • Highlights areas where fair balance may be insufficient
  • Detects language patterns commonly raised in MLR review
  • Helps writers self-check before submitting to formal approval

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What it does not do

MedCheckr is a pre-screening tool. A clean scan does not mean the content is compliant — it means the automated scan found no flagged patterns. Formal compliance determination requires qualified reviewers.
Promotional codes vary by market. MedCheckr flags general patterns — market-specific compliance always requires specialist review from someone with expertise in that jurisdiction.
A clean MedCheckr result means no patterns were flagged by the automated scan. Compliance determination is a human responsibility.
MedCheckr screens for compliance signals, not reference accuracy. Use RefCheckr to verify that claims are supported by cited references.

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Risk tier

MedCheckr is used in high-risk workflows. Its outputs are compliance support inputs, not compliance determinations. Every MedCheckr result — flagged or clean — requires expert review before the content is approved for use. See the risk levels framework for full context.
This playbook does not provide regulatory or legal advice. MedCheckr and the compliance workflows described here are designed to help medical writers identify potential issues earlier in the content development process. They do not replace the judgement of qualified compliance, legal, or regulatory professionals.

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Workflow integrations

Check promotional compliance

Primary use. Automated compliance signal detection as a structured pre-MLR step.

Final human review

Supporting use. Compliance layer within the final QC gate before submission.

Verify claims against references

Pair with RefCheckr. Use MedCheckr for compliance signals and RefCheckr for claim-to-reference accuracy.

Repurpose content across channels

Supporting use. Re-screen repurposed content when promotional material is adapted for a new format or channel.

Try MedCheckr at PharmaTools.AI

Part of the PharmaTools.AI toolkit for medical writing teams.