Post-Market Surveillance Challenges in Pharma & Medtech
Why Smarter, AI-Ready Systems Are Urgently Needed
Introduction: The Urgent Need for PMS Transformation
Post-Market Surveillance (PMS) is no longer just a regulatory checkbox—it’s a strategic necessity for Pharma and Medtech companies under pressure to ensure safety, compliance, and market competitiveness. Yet, PMS remains one of the most fragmented and outdated areas of the product lifecycle.
Despite advances in real-world data, digital health, and AI, many manufacturers still struggle with:
Manual case intake and signal detection
Data silos and vendor fragmentation
Lagging integration with real-world evidence (RWE)
Inefficient global reporting systems
Recent insights from Deloitte, Accenture, BCG, the World Economic Forum, and multiple digital health experts highlight that next-generation pharmacovigilance must evolve—not just incrementally, but fundamentally.
1. Fragmented Systems Create Safety Risks and Inefficiencies
Many PMS processes still depend on disconnected spreadsheets, legacy systems, and siloed vendor solutions. According to Cervicorn Consulting, the PMS software market is crowded, often forcing companies to use multiple vendors for intake, assessment, signal detection, and reporting—each with varying degrees of compliance readiness (Cervicorn).
➡️ This fragmentation slows reaction time, increases cost, and undermines coordinated signal tracking.
2. Generative AI Offers Promise—but Only with the Right Infrastructure
Generative AI is rapidly entering pharmacovigilance, with use cases ranging from automated narrative writing to predictive signal detection. As PharmaPhorum and John Praveen’s LinkedIn article note, AI can significantly reduce time and cost in PMS processes (PharmaPhorum; LinkedIn).
However, AI alone is not a silver bullet. According to Accenture, over 70% of pharma companies face regulatory resistance and internal compliance barriers when attempting to use AI for personalized or real-time reporting (Accenture).
➡️ The future of AI in PMS depends on a foundation of clean, structured, and interoperable data models—not just algorithms.
3. PMS Is Expanding Beyond Adverse Event Reporting
The traditional definition of PMS—centered around adverse event collection—is evolving. Deloitte and the World Economic Forum note that regulators and industry are moving toward broader safety tracking, including patient-reported outcomes, behavioral data, and care pathway insights (Deloitte; WEF).
➡️ A modern PMS system must be designed to ingest and analyze real-world evidence at scale, with support for standards like HL7 FHIR, SNOMED CT, and ICD-10.
4. Compliance, Legal, and Data Privacy Still Hold Back Innovation
Despite regulatory pushes for modernization, many companies remain risk-averse. As noted by BCG and LinkedIn contributor Lucki, legal and privacy teams often block the use of proactive tools, especially when it comes to AI-driven personalization or real-time insights (Lucki on LinkedIn; Bates on LinkedIn).
➡️ To succeed, PMS innovation must align with regulatory-grade compliance while enabling more agile, data-driven workflows.
5. Toward a Unified, Intelligence-Ready PMS Future
The future of PMS lies in platforms that can:
Unify fragmented processes from intake to reporting
Integrate with real-world evidence and structured data streams
Support AI use cases through interoperable ontologies and compliance alignment
This requires more than a software patch—it demands a rearchitecting of PMS strategies around standards, lifecycle engagement, and real-time data.
Ready to Future-Proof Your PMS Strategy?
Whether you’re exploring AI for pharmacovigilance or looking to unify fragmented post-market systems, the next generation of solutions will be intelligence-ready, standards-based, and lifecycle-driven.
📩 Curious how Meplis is helping industry partners prepare for this shift?
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References
Transforming Pharmacovigilance: The Revolutionary Impact of Generative AI – PharmaPhorum
Transforming Pharmacovigilance – LinkedIn (John Praveen)
Transforming Pharmacovigilance: Modernizing the Operating Model – Deloitte
AI in Pharmacovigilance Market Report – Cervicorn Consulting
The Future of Pharmacovigilance – LinkedIn (Lucki)
How Pharma Companies Can Leverage AI Across the Value Chain – LinkedIn (Bates)
Innovation in Regulatory – Accenture
The Future of AI-Enabled Health 2025 – World Economic Forum