PMCF compliance costs and AI-enabled approaches

PMCF requirements are raising hard questions about cost, device viability, and where AI fits in

Derk Arts (Castor) and Dr. Bassil Akra (AKRA TEAM) share 60 minutes on EU MDR evidence strategy, AI-assisted chart review, and when US real-world data can support European submissions. Watch On-Demand

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Duration: 60 minutes

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PMCF compliance costs and AI-enabled approaches

EU MDR post-market clinical follow-up requirements continue to influence device portfolio economics. For some teams, PMCF evidence costs now rival the commercial return on keeping a product in market.

Castor CEO Derk Arts and Dr. Bassil Akra, EU MDR Expert and CEO of AKRA TEAM, work through the questions that rarely get straight answers: what AI-assisted chart review can realistically deliver for evidence generation, when US real-world data can support EU submissions, and how to estimate PMCF costs before committing to a study design.

Leave with a 5-step framework for integrating AI into PMCF strategy.

Why PMCF costs are now driving product retirement decisions
When US real-world data can meaningfully support EU MDR submissions
Where AI-assisted chart review fits within regulatory standards
A 5-step framework for integrating AI into PMCF strategy

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Frequently Asked Questions

What does EU MDR require for post-market clinical follow-up?
EU MDR Article 61(11) requires manufacturers to collect clinical data on their devices after market authorization to confirm the safety profile, effectiveness, and clinical benefit. Post-Market Clinical Follow-up (PMCF) is the systematic process for gathering this data. Required activities must be defined in a PMCF plan (Annex XIV Part B) and reported in a PMCF evaluation report. The scope and frequency are proportional to the risk classification of the device and the clinical evidence already available.
What does PMCF evidence collection cost under EU MDR?
Costs vary widely by device risk class and evidence strategy. Registry studies can cost EUR 50,000 to 500,000 per year depending on site complexity and data volume. Prospective PMCF clinical investigations routinely exceed EUR 1 million for mid-sized device companies. AI-assisted chart abstraction from existing clinical records is an emerging cost-reduction approach, though its regulatory acceptability depends on the quality of the source data and the documentation of the AI methodology.
Can AI-assisted chart review meet EU MDR evidence requirements?
AI-assisted chart review can support PMCF evidence generation, but regulatory acceptability depends on study design, methodology documentation, and data quality. The EU MDR does not prohibit AI tools in evidence generation, but the manufacturer remains responsible for demonstrating that the data collected is sufficient, reliable, and traceable. Current EU guidance requires that real-world data used for PMCF has clearly defined collection methods and risk of bias assessments, regardless of whether AI was involved in data extraction.
When can US real-world data support EU MDR submissions?
US real-world data can support EU MDR post-market obligations when the patient population, device indication, and clinical environment are sufficiently similar to EU use. EU MDR permits use of equivalent device data and real-world evidence from other jurisdictions, provided the manufacturer demonstrates the data is relevant, of sufficient quality, and collected under comparable conditions. US registry data and electronic health record studies are increasingly accepted for low-to-medium risk PMCF, but high-risk devices typically require EU-specific clinical evidence.