For medical device manufacturers managing large and diverse portfolios, the real challenge is no longer producing individual CERs. The challenge is maintaining them – accurately, consistently, and on time.

With renewal deadlines approaching under the EU MDR and IVDR, manufacturers must shift to a continuous maintenance model that keeps every CER aligned with current evidence, emerging safety signals, and evolving Notified Body expectations.

Unlike CER development—which focuses on building a strong evidence foundation – CER maintenance is about operational discipline, risk-based planning, and portfolio-wide synchronization. This requires a different set of tools and strategies altogether.

Why CER Maintenance Will Become More Intensive in 2026

Renewal cycles demand fully updated CERs

When Notified Bodies reopen technical files for renewal, there is a growing expectation that CERs demonstrate continuity of clinical evidence. Outdated or partially updated CERs, or CERs that do not follow the established best practices such as a systematic literature review conducted according to relevant guidance documents, evaluation of the relevancy of acceptance criteria, evidence on similar devices, and appropriate scientific justifications can result in major audit findings. Even small inconsistencies accumulate over time and become major obstacles during renewal reviews, causing significant delays in certification and market access.

Large portfolios inherently create scale challenges

The clinical evaluation documents are no longer a compilation of data. The notified body reviewer looks for traceability and consistency across various Plans and Reports, scientific depth, rigor, and validated critical interpretations and conclusions. Increased expectations of clinical evidence from multiple data sources including PMCF, quantitative in-depth analysis, and clear, organized presentation of evidence are not easy to meet for organizations with 50, 100, or 200+ devices constantly in a maintenance cycle. Without structured systems, teams of highly qualified experts spend months managing documents, tracking timelines, and responding to the same notified body questions across multiple CERs.

Maintenance requires systems – not just skill.

Key Challenges Slowing Down Portfolio-Wide CER Maintenance

Outdated State of the Art

The State of the Art must be updated. Because SoTA evolves continuously, infrequent updates lead to:

• Inconsistency across similar device portfolio
• Misalignment with current literature
• Weak comparative analyses

Annual update frequency – challenging timelines

CER maintenance must be coordinated alongside PMS evaluations, PMCF activities, risk file updates, and internal review cycles—involving multiple stakeholders and departments, making timelines difficult to control and predict.

Overlapping evidence across device families

Teams often redo work because CERs for similar devices in the same portfolio use similar content:

• Similar state of the art
• Similar intended use and performance and safety objectives
• Similar testing or preclinical data
• Similar benefit risk profiles
• Overlapping risk content or justifications

Scattered evidence repositories worsen the problem.

How AI Strengthens CER Maintenance Across Large Portfolios

AI-enabled tools are particularly effective during maintenance cycles because they automate repetitive, version-based tasks and provide consistency across device families.

Automated literature refresh cycles

AI tools can:

• Re-run literature searches
• Signal new studies
• Summarize key details
• Compare evidence with prior versions

This ensures evidence stays current without time-intensive manual screening.

Cross-version comparison identifies required updates

AI highlights:

• Changes in clinical evidence
• Variations in safety outcomes
• New regulatory expectations
• Outdated claims or references

Teams update only what has changed—saving time and improving reliability.

Consistency checks across multiple CERs

AI monitors terminology, content alignment, and data presentation to ensure that device families maintain coherent documentation.

Portfolio Priorities for 2026 CER Maintenance

Risk-based annual maintenance calendar

High-risk devices should be prioritized, followed by devices with PMS signals or significant market exposure.

Automated evidence refresh cycles

AI-supported systematic literature search and review allow teams to maintain compliance with comprehensive review of available literature without overburdening resources.

Clear traceability for reviewers

Review outputs with:

• Linked evidence
• Change logs
• Version comparisons
• Structured updates

This reduces internal clarification rounds and creates audit-ready records.

Practical Steps to Stay Audit-Ready

1. Start with high-risk and high-volume product lines
   Address devices with the greatest regulatory scrutiny or the widest clinical use first.
2. Introduce planned SoTA refresh cycles
   Many manufacturers now refresh SoTA quarterly or bi-annually to stay aligned with evolving technologies and benchmark devices.
3. Standardize CER formats across the portfolio
   Unified templates support:
   • Efficient, consistent writing
   • Reliable and efficient review cycles
   • AI-assisted partial drafts with pre-populated content
   • Predictable, scalable maintenance workflows.

Organizations that treat portfolio-wide maintenance as strategic portfolio management activity rather than admin work, will be best positioned for renewal success and have shorter time to market than their competitors.

How Celegence Supports Portfolio-Wide CER Maintenance

Celegence helps manufacturers implement structured, technology-enabled CER maintenance programs that support annual updates, renewal readiness, and portfolio-wide consistency. With CAPTIS®, our AI-powered authoring platform – teams gain version comparison tools, structured evidence repositories, and automated literature refreshes.

To explore how we can strengthen your CER maintenance strategy, contact us at info@celegence.com.

The CER Challenge

For medical device manufacturers, Clinical Evaluation Reports (CERs) have become one of the most resource-intensive requirements under the EU MDR. Each report demands exhaustive literature searches, detailed analysis, and a high degree of traceability to satisfy notified body scrutiny. As regulations evolve, the volume of documentation continues to grow — stretching teams that are already under pressure to deliver faster with limited resources.

This burden has led some manufacturers to delay product launches or even withdraw devices from the EU market. Against this backdrop, artificial intelligence (AI) is emerging as a practical solution. Not to replace medical writers, but to enable them to work more efficiently, reduce repetitive tasks, and focus on the analytical work that drives compliance and patient safety.

From Manual Methods to AI-Supported CERs

CER development has traditionally been a painstakingly manual process. Writers and reviewers relied on spreadsheets, Word documents, and countless shared folders to manage literature reviews and draft content. It was thorough, but it was also slow, error-prone, and difficult to scale.

The first generation of digital tools provided modest relief, with reference managers or literature screening modules. But these worked in silos and often created as many challenges as they solved. What the industry needed was a holistic, end-to-end approach.

Automation and AI-supported platforms are now delivering exactly that. Automated workflows manage literature searches, screening, evidence tagging, drafting, and review cycles within a single environment — with AI adding intelligent assistance on top. For writers, this means fewer hours lost to repetitive background work and more time to focus on interpretation, strategy, and regulatory judgment.

The Promise of Automation and AI for CER Development

Automation is already transforming the CER process, streamlining repetitive tasks and enforcing consistency, while AI adds intelligent support to enhance speed, insight, and adaptability. Together, they’re delivering measurable improvements:

• Efficiency: Literature reviews that once took months are now being completed in weeks. In many cases, time savings exceed 50%.
• Transparency: Paragraph-level traceability and one-click source verification give reviewers and auditors confidence in the evidence base.
• Scalability: With tech-enabled workflows, teams can manage large volumes of data and keep pace with post-market surveillance requirements without endlessly expanding headcount.
• Forward-looking features: AI-assisted risk mapping, literature strategy suggestions, and draft text generation for stable CER sections are all on the horizon.

Celegence’s own experience illustrates the potential. Using its CAPTIS^® platform, the team reduced CER timelines for manufacturers from six months to just six to eight weeks — all while maintaining quality and compliance. To date, the platform has supported more than 500 CERs and processed over 500,000 literature records — tangible evidence that tech-enabled regulatory writing can move CERs from burden to breakthrough.

Challenges in Applying AI to CERs

Like any technology shift, AI adoption for CER development comes with challenges.

• Data quality: AI outputs are only as good as the literature and source documents provided. Poor inputs risk weak outputs.
• Complex content: Source information for CERs often include tables, scanned PDFs, and variable data formats that can be difficult for AI to interpret accurately.
• Trust: For regulatory writing, transparency is essential. Writers and reviewers must be able to trace every AI-supported suggestion back to its source.
• User adoption: Many regulatory professionals are new to generative AI and may feel uncertain about how to use it effectively.

The lesson is clear: AI is not plug-and-play. Successful integration requires thoughtful automated workflows, transparency features, and user enablement. Celegence has found that libraries of pre-configured prompts, embedded AI templates, and training sessions can make adoption smoother and build user confidence.

Real-World Use Cases for CERs

The combined impact of automation and AI in CERs is no longer theoretical. Practical use cases include:

• Literature reviews: Automation and AI-support speed up article screening, categorization, and summarization, saving writers days or even weeks of effort.
• Evidence management: Saved searches can be updated without compromising prior review data — a critical advantage for ongoing CER updates.
• Drafting support: For stable, repeatable sections of CERs, AI can generate draft content that writers refine, reducing drafting cycles.

Users often describe these systems as a “medical writing assistant”. Automation removes much of the administrative burden – handling repetitive, time-consuming tasks – while AI provides contextual insights that help experts focus on high-value interpretation. Together, they ease the pressure of tighter regulatory timelines and more demanding audits.

The Road Ahead: AI as a CER Partner

As MDR and IVDR requirements evolve, the need for efficient CER processes will only intensify. Technology offers not just a short-term productivity boost, but a scalable, long-term solution. Structured content and modular authoring, combined with generative AI, will allow manufacturers to repurpose evidence across multiple reports – from CEPs to CERs and PMSRs – without duplicating effort.

The future of CER writing is collaborative. Automation with AI support will manage the heavy lifting of repetitive tasks, while medical writers bring the expertise, judgment, and context that no algorithm can replace. Together, they will produce stronger, faster, and more resilient submissions.

Empowering Medical Writers Through Technology

AI has already begun transforming CER development from a fragmented, manual process into a streamlined, technology-enabled workflow. Manufacturers that embrace AI-supported approaches will not only cut timelines and reduce costs but also strengthen the robustness of their submissions.

The end goal is not to replace writers, but to empower them. With automation and AI as a partner, regulatory professionals can focus on the analysis and insights that safeguard patient safety — while leaving the repetitive burden of CERs to technology.

Celegence combines experienced medical writers with AI-enabled workflows to help manufacturers deliver compliant, defensible CERs without added operational burden.

Contact us at info@celegence.com to discuss how AI-supported CER workflows can work for your portfolio.

The European Commission has confirmed a major milestone for the medical devices and IVD industry. On November 27, 2025, the Commission published Commission Decision (EU) 2025/2371 in the Official Journal of the European Union (OJEU), formally validating four fully functional modules of the European Database on Medical Devices (EUDAMED).

This development activates the ‘gradual roll-out’ provisions introduced by Regulation (EU) 2024/1860 and sets the date for mandatory EUDAMED use on 28 May 2026, exactly six months from its publication.

For manufacturers, authorized representatives, importers, and Notified Bodies, this marks one of the most significant regulatory developments since the introduction of the EU MDR and IVDR. The update provides long-awaited clarity about compliance timelines and reinforces the EU’s commitment to transparency, traceability, and post-market oversight.

Organisations that have not begun uploading their UDI and device data have a very tight window of less than 6 months to prepare, validate, and upload huge datasets into the EUDAMED database.

What the Announcement Means for Industry

The Commission’s publication confirms that four out of the six EUDAMED modules meet the functional requirements set out in the MDR and IVDR:

• Actor Registration
• UDI & Device Registration
• Notified Bodies & Certificates
• Market Surveillance

This validation triggers Article 123(3) MDR transitional provisions, introducing fixed deadlines for mandatory use. From May 28, 2026, economic operators across the EU must shift from optional to required EUDAMED participation.

The Legacy Device registration deadline is November 27, 2026.

According to Article 10a (effective January 2025) introduced by Regulation (EU) 2024/1860, manufacturers must notify authorities, economic operators, and health institutions of any interruption or discontinuation of supply that could result in serious harm. Failure to notify about an unavailable device registered as ‘On the Market’ in EUDAMED may lead to double liability for the manufacturer.

With EUDAMED becoming the central regulatory data source, it is essential for stakeholders to prepare early. User Interface (UI) challenges or operational issues will no longer justify delaying compliance.

Which EUDAMED Modules are Officially Functional?

The Commission has confirmed the operational readiness of the following modules:

1. Actor Registration (Art. 30 MDR / Art. 27 IVDR)

   This module issues the Single Registration Number (SRN) for all economic operators. The SRN is the digital identity for any regulatory activity within the EU, including conformity assessment applications and device registration. Manufacturers, authorised representatives (ARs), importers, system/procedure pack producers (SPPPs), and clinical investigation sponsors must submit organizational, and PRRC information to the portal. National Competent Authorities (CAs) validate submissions, and a surge in registrations may create backlogs. Delayed SRN issuance will block device registrations and market access. Non-EU manufacturers need verification from ARs before CAs and must ensure that the digital linkage to their AR is valid. Termination of AR’s contract will be immediately visible to the market and authorities.

2. UDI & Device Registration (Art. 28–29 MDR / Art. 25–26 IVDR)

   This is the most resource-intensive module. Manufacturers and SPPPs must enter every medical device and IVD for sale in the EU market into the portal, using the Unique Device Identification (UDI) system. All devices must be registered in EUDAMED before being placed on the EU market from 28 May 2026. New device launches from May 2026 must consider EUDAMED data entry timelines.

3. Key concepts:

   • Basic UDI-DI (BUDI-DI) is the primary key grouping devices with the same intended purpose, risk class, and essential design characteristics.
   • BUDI-DI is also the link to certificates and vigilance records and therefore, care must be taken when grouping devices under a BUDI-DI.
   • BUDI-DI is distinct from the UDI-DI, which is the GTIN on the device package.
   • Existing product families must be uploaded by 27 November 2026 to maintain current UDI-DI structures.
   • EUDAMED has a restricted site and a public site. The public site will display most of the device data, including the intended purpose, warnings and CMR substances. Marketing claims must align with EUDAMED entries perfectly to prevent misbranding allegations.
   • Manufacturers with large portfolios should evaluate Machine-to-Machine (M2M) solutions to integrate ERP/PLM systems directly with EUDAMED via XML-based protocols.

4. Notified Bodies & Certificates (Art. 57 MDR / Art. 52 IVDR)

   This module centralizes all certificate information under MDR and IVDR. NBs are obligated to register granted, refused, withdrawn, or suspended certificates. Refused applications will be visible to all NBs, requiring manufacturers to disclose prior failures. NBs must upload certificates issued prior to the mandatory date by May 28, 2027. During the interim, manufacturers should maintain accessible copies for distributors or importers.

5. Market Surveillance (Art. 100 MDR / Art. 95 IVDR)

   This module is accessible only to Competent Authorities and supports coordination of inspections, enforcement actions, non-compliance reports, and public health protection measures. A report filed by any Member State becomes instantly visible across the EU.

Mandatory Use Begins 28 May 2026

All economic operators must complete Actor Registration and obtain an SRN before 28 May 2026. This includes:

• Manufacturers
• Authorised Representatives (ARs)
• Importers
• System and procedure pack producers (SPPPs)
• Clinical investigation sponsors

Without an SRN, no regulatory activity in EUDAMED can proceed. This transition will be especially demanding for manufacturers with extensive portfolios or multi-country distribution networks within the EU.

What’s Still Pending?

Two modules remain under development:

• Module 4: Clinical Investigations Module: For reporting and managing clinical studies carried out under MDR.
• Module 5: Vigilance Module: For reporting serious incidents, Field Safety Corrective Actions (FSCAs), and trends. Until the module becomes functional, manufacturers must continue reporting directly to national Competent Authorities.

Once these modules are deemed fully functional, the Commission will determine the date for mandatory use of the complete EUDAMED system.

Until then, the industry should assume that timelines will accelerate and not slow down.

Legacy Device Registration

Legacy devices intended to remain on the market after November 2026 must be registered within 12 months of the functionality notice. For these devices, a EUDAMED-DI (EUDAMED Device Identifier) and a EUDAMED-ID (instead of the BUDI-DI) must be generated.

Given that legacy devices constitute the majority of many portfolios, the data volume will be significant. Early preparation will be critical to avoid congestion and system delays. However, the devices to be launched must be prioritised over the ones already in the market.

How Manufacturers Should Prepare now

With less than two years remaining, organizations should begin structured implementation:

• Validate internal UDI data for accuracy and completeness.
• Ensure organisational details, PRRC information, and hierarchies are updated.
• Register new MDR/IVDR devices on priority to prevent launch delays post-May 2026.
• Identify legacy devices that will remain on the market past November 2026 and initiate their EUDAMED-DI creation.
• Align PMS, vigilance, and QMS procedures with EUDAMED outputs.
• Confirm timelines for uploading certificates with NBs.
• Plan for long-term digital strategies. Manual processes will not scale once EUDAMED becomes fully operational.

Starting early will reduce pressure and prevent last-minute compliance risks.

How Celegence Can Support Your EUDAMED Readiness

Celegence supports medical device and IVD manufacturers with regulatory consulting and technology-enabled services designed to help navigate evolving EU MDR/IVDR environment. Our teams assist with:

• Actor registration and SRN preparation
• UDI-DI and Basic UDI-DI mapping
• EUDAMED data preparation, validation and entry
• Portfolio-wide device registration strategies
• EU MDR and IVDR regulatory transition planning
• PMS and PMCF documentation alignment

With CAPTIS^®, our AI-enabled regulatory authoring platform, we help streamline documentation, improve data consistency, and support end-to-end readiness for the 2026 EUDAMED transition.

If you need guidance preparing for your EUDAMED planning, contact us at info@celegence.com.

Introduction: Complexity Meets Innovation

Medical and technical writing has always been at the heart of life sciences, where accuracy, clarity, and compliance directly affect patient outcomes. But the demands on writers have grown exponentially. From Clinical Evaluation Reports (CERs) under EU MDR to Chemistry, Manufacturing and Controls (CMC) submissions, the volume of documentation required has never been greater. Teams are under pressure to deliver faster, with higher scrutiny from regulators, and often with limited resources.

It’s no surprise that artificial intelligence (AI) has become part of the conversation. Yet it is often positioned at two extremes: either as a silver-bullet that will “replace” writers, or as an untrustworthy experiment. The reality lies somewhere in between. AI is not about replacing expertise, but about enabling experts to focus on the work that matters most.

From Manual to Machine-Supported: The Evolution of Writing

Traditionally, writing regulatory and technical documents was almost entirely manual. Teams relied on spreadsheets, word processors, and countless shared folders. This approach was thorough but painfully slow.

The first wave of automation introduced reference managers, templates, and rule-based tools that eliminated some repetition. They were helpful, but they didn’t address the complexity of integrating evidence, ensuring consistency, and maintaining audit readiness across documents.

Today, AI-supported platforms are beginning to bridge that gap. These tools not only automate administrative steps but also provide context-aware assistance, from summarizing dense scientific articles to suggesting draft text. This evolution allows skilled professionals to shift their role from pure drafting to validation, quality oversight, and strategic analysis.

The Promise of AI in Medical and Technical Writing

The real power of AI lies in its ability to make writing tasks more efficient, scalable, and resilient. Consider three dimensions:

• Efficiency: Literature reviews and drafting that once consumed months can now be completed in weeks. In some projects, review times have been cut by more than half.
• Accuracy and consistency: Features like one-click source verification and paragraph-level traceability reduce duplication and strengthen audit readiness.
• Scalability: With regulations becoming more demanding, AI provides a way to manage larger data volumes without endlessly expanding teams.

For example, Celegence’s CAPTIS^® platform has helped deliver CERs in as little as 6–8 weeks – a process that previously stretched to six months, without compromising quality. Beyond time savings, this frees medical writers to focus on critical analysis rather than repetitive formatting and reconciliation.

Looking ahead, the integration of structured content with generative AI points to a future where modular, review-ready outputs can be assembled faster than ever, while maintaining the accuracy regulators expect.

Challenges and Lessons Learned

Despite the promise, adopting AI in regulatory writing is not without challenges.

• Data quality: AI is only as reliable as the content it processes. Poorly structured or incomplete data can undermine outputs.
• Complex content: Regulatory documents often include tables, scanned documents, and variable formats that can be difficult for AI to interpret.
• Trust and adoption: Transparency and traceability are non-negotiable in compliance workflows. Writers and reviewers need to see exactly where AI-generated content originated.
• User readiness: Many professionals are new to prompting and generative AI. Without training, adoption can lag.

Celegence’s experience has shown that success requires more than technology. Prompt libraries, embedded AI templates, and training are key to helping users feel confident and empowered rather than overwhelmed. AI is not plug-and-play; it requires thoughtful integration into existing processes.

Real-World Use Cases

AI is already making a difference in everyday writing tasks. Examples include:

• Data extraction and summarization: Pulling key insights from hundreds of articles for literature reviews.
• Draft generation: Producing initial text for standard sections of regulatory documents, with writers reviewing and refining.
• CMC pilots: Early trials show AI can support “first-draft-ready” submissions, reducing review cycles and accelerating delivery.

In practice, CAPTIS^® has supported over 500 CERs and processed more than 500,000 literature records, delivering measurable time savings of 50% or more for manufacturers.. The outcome isn’t just faster documents — it’s more satisfied writers, smoother reviews, and greater resilience when workloads spike.

The Road Ahead: AI as a Partner, Not a Replacement

Looking forward, the role of AI in medical and technical writing will continue to expand, but its success depends on balance. Structured content, modular authoring, and generative AI will shape the next wave of innovation. Writers will increasingly act as strategists and validators, ensuring accuracy and context, while AI takes on repetitive, time-consuming tasks.

At Celegence, our perspective is clear: AI should empower professionals, not replace them. The goal is to give skilled experts more time for the analysis, interpretation, and communication that truly make a difference in regulatory compliance and patient safety.

Conclusion

AI in medical and technical writing has moved beyond hype to deliver tangible results. The industry is learning that success depends not on choosing between humans or machines, but on building effective partnerships between the two.

Organizations that adopt AI thoughtfully — with the right data, workflows, and oversight — stand to gain faster timelines, improved efficiencies, and stronger quality. Most importantly, they give their experts the space to do what they do best: bring clarity and confidence to the most complex challenges in life sciences.

Learn how AI-supported writing can streamline workflows, strengthen document quality, and elevate regulatory efficiency. Contact us at info@celegence.com.

Clinical Evaluation Reports (CERs) have evolved significantly under the EU Medical Device Regulation (MDR). What was once a static, point-in-time submission is now a living dossier requiring continuous updates, traceable evidence, and alignment with real-world performance data. Technology and particularly artificial intelligence (AI) – is playing an increasingly critical role in helping manufacturers meet these expanding expectations.

From Static Documents to Dynamic Compliance

Under MDR Article 61 and Annex XIV, clinical evidence is no longer a one-time submission. Manufacturers must continuously monitor literature, post-market surveillance (PMS) data, clinical investigations, and competitor products to ensure safety and performance across the lifecycle of a device.

This shift has introduced significant challenges:

• Volume of Evidence: Literature reviews, PMS inputs, and registry data flood regulatory teams, increasing the burden of data triage and synthesis.
• Traceability Requirements: Establishing and maintaining links between clinical claims, data points, and source materials can be time-intensive and error-prone.
• Higher Scrutiny: Notified bodies are rejecting a notable percentage of CERs due to insufficient or poorly justified evidence, creating costly delays and rework cycles.

These challenges are prompting manufacturers to explore how AI and other emerging technologies can enable more scalable, audit-ready CER processes.

AI as a Clinical Evaluation Enabler

AI’s contribution to CER development goes beyond speeding up literature searches. At its most effective, AI integrates directly into regulatory workflows to provide:

• Contextualized Evidence Retrieval: AI tools can flag relevant studies based on the device’s intended purpose and risk classification, while filtering out non-compliant sources.
• Gap Identification: By comparing incoming data against MDR expectations or established templates, AI can proactively identify missing safety endpoints or weak benefit-risk conclusions.
• Intelligent Synthesis: Advanced algorithms can correlate findings from literature, PMS reports, and clinical studies, helping teams build stronger justifications for equivalence or performance claims.

These applications significantly reduce manual workload and improve the consistency and scientific quality of CERs.

Technology-Supported Workflows: From Evidence to Submission

An integrated, tech-enabled CER process typically includes:

• Centralized Evidence Foundation: Systems aggregate clinical and post-market data into a structured repository. AI layers can map the content against regulatory requirements highlighting deficiencies in equivalence data or long-term outcomes.
• Modular Document Generation: Instead of static document creation, modular authoring allows dynamic updates to background sections, benefit-risk profiles, and literature summaries. Some platforms also offer predictive analytics that signal which sections are likely to trigger notified body scrutiny.
• Post-Market Intelligence Loop: With MDR’s emphasis on continuous updates, technology can flag safety signals early, recommend updates, and even integrate with other quality systems (e.g., PMS plans, SSCPs).

For example, a manufacturer monitoring PMS reports from Asia-Pacific detected emerging safety trends weeks ahead of formal regulatory queries allowing proactive updates to the CER and avoiding potential findings.

Quantifying the Impact of AI-Driven CER Processes

While experiences vary, organizations adopting intelligent regulatory technologies often report measurable improvements:

Beyond efficiency gains, regulatory teams are also freed up to focus on higher-value tasks like supporting new indication expansions, refining clinical strategies, or collaborating more closely with notified bodies.

From Compliance Burden to Strategic Asset

When leveraged effectively, CERs can become more than just a regulatory requirement. They can support:

• Market Expansion: Well-structured CERs can support reimbursement strategies, additional market approvals, or competitive positioning.
• Data-Driven Strategy: Analyzing trends in regulator expectations across CER reviews can inform future development and risk mitigation strategies.
• Regulatory Agility: With regulatory requirements becoming more dynamic—especially in the lead-up to IVDR enforcement organizations need compliance infrastructure that evolves in parallel.

Some manufacturers are now embedding CER processes within broader regulatory operating systems, integrating authoring, surveillance, and quality management to enable real-time adaptability.

Conclusion: AI’s Role in the Future of CER Excellence

As regulatory expectations continue to rise, manufacturers are shifting from reactive compliance to strategic, data-driven evidence generation. Technologies like AI and advanced automation play a critical role in enabling this shift reducing manual workload, increasing document accuracy, and aligning internal operations with regulatory expectations.

Organizations that invest in these capabilities today are better positioned for faster approvals, stronger regulator relationships, and more agile market access strategies tomorrow.

Contact us at info@celegence.com to learn more.

Systematic literature reviews are a central component of Clinical Evaluation Reports. However, searching multiple databases, screening thousands of titles, extracting structured data and preparing audit-ready documentation often absorbs the author’s time and delays progress. When used responsibly, AI can accelerate these repetitive tasks while preserving reproducibility and traceability.

Common Bottlenecks in Traditional SLRs

Teams frequently encounter the same constraints:

• Running inconsistent and inadequate queries across databases and managing large duplicate sets.
• Manual title and abstract screening that consumes significant SME/author hours.
• Extracting study-level fields such as design, population, endpoints and harms into a consistent dataset.
• Producing PRISMA-style documentation, version control and traceability for audits and Notified Body review.

These efforts are essential for MDR compliance but can also significantly impact timelines and quality.

What AI Contributes, with Safeguards

AI is most valuable for repetitive, pattern-based work. Key capabilities that benefit SLRs include:

• Automated retrieval and de-duplication across multiple sources.
• Assisted screening that ranks records by relevance, keeping reviewers in control.
• Rapid structured extraction into a standardized data dictionary.
• Automatic generation of PRISMA flows and exportable audit trails.

AI should extend human capability, not replace it. Every AI generated result must link back to the source and remain verifiable by reviewers.

A Regulator-Ready Hybrid Workflow

Below is a practical sequence that balances automation with mandatory human checks:

• Scope and protocol: Define the clinical questions, populations, comparators and acceptance criteria; pre-register search strings, databases and date ranges.
• Automated retrieval and clean-up: Run pre-registered searches, remove duplicates and tag records for screening.
• Assisted screening with adjudication: Use AI scoring to assess records; two reviewers confirm inclusions and resolve disagreements.
• Full-text extraction and verification: AI extracts data based on pre-defined instructions into templates; reviewers verify critical fields such as endpoints and harms.
• Quality appraisal and synthesis: Appraise study quality, apply pre-defined criteria for benefit-risk, and conclude study findings accordingly.
• PRISMA output, traceability and version control: Produce a PRISMA flow diagram, an exportable study table and a traceability matrix linking claims to evidence and risk controls.

This approach reduces the human oversight regulators expect while automating the steps that typically consume the most time.

Mini Case Example

Consider a typical SLR for a Class IIa device that searches five databases and returns 3,500 records. In a manual workflow, title/abstract screening and full-text extraction might require four to six weeks of an SME’s time. With automated retrieval, de-duplication and assisted screening, the initial screening pool can be reduced by more than half within days. Assisted extraction then populates a structured dataset that SMEs can validate in a matter of days rather than weeks. Deliverables such as the PRISMA flow and an exportable study table. The net effect is savings of several weeks in SME time, faster responses to Notified Body queries and a cleaner audit record that documents reviewer verification of AI-extracted items.

Integrating Real-World and Decentralized Data

Regulatory reviewers increasingly expect real-world evidence, registries and decentralized trial outputs to support CER updates. AI can help harmonize heterogeneous inputs by tagging metadata, tracking sources and converting registry exports into structured records for appraisal. The same human-in-the-loop principles apply here, and the analytical validation and reviewer verification are required before RWE is used in benefit-risk conclusions.

Operational Benefits

Adopting this hybrid model delivers measurable improvements:

• Shorter cycles because searches, de-duplication and extraction are automated.
• Fewer data-entry inconsistencies due to structured extraction.
• Better audit readiness through consistent PRISMA outputs and per-item provenance.

These gains free the author and the subject experts to focus on interpretation and clinical judgment rather than repetitive data handling.

Governance and Team Readiness

Introducing AI in your workflow should include clear guidelines. Define standard operating procedures specifying where AI is permitted, which fields require mandatory human verification, and how AI determined scores should be interpreted. Train reviewers to identify common AI errors and record corrections. Periodic audits comparing AI outputs with manual benchmarks help maintain quality and build trust with internal stakeholders and external reviewers.

Below is a quick SLR Checklist when automation is used

• Pre-specify search strategy and inclusion/exclusion criteria in a protocol.
• Utilize exportable, audit-ready outputs including PRISMA flows and data dictionaries.
• Keep reviewers in the loop for screening and extraction verification.
• Maintain a traceability matrix linking claims, evidence and post-market outputs.
• Archive logs showing search timestamps, reviewer decisions and data sources.

How CAPTIS^® Can Help

Integrated platforms that combine literature search, collaborative review, structured extraction and automated reporting make this hybrid workflow practical on scale. CAPTIS^® automates extraction, generates audit-ready reports and preserves references while enabling simultaneous review and simple cross-verification. Features that accelerate compliance include an integrated citation manager that links each extraction to source documents, exportable audit logs for every reviewer decision, role-based review workflows and pre-built templates for traceability matrices. That mix helps teams shorten SLR cycles without sacrificing traceability or regulatory rigor. Read How AI Speeds Up Systematic Literature Reviews by 60% blog here.

Conclusion

A rigorous protocol, clear reviewer responsibilities and tools that produce verifiable outputs make it possible to utilize automation and reduce SLR timelines while improving consistency and auditability. Teams that adopt a balanced AI-plus-reviewer approach will be better positioned to meet Notified Body expectations and keep CERs current with high-quality evidence. By leveraging AI-powered tools like CAPTIS^®, medical device professionals can ensure compliance with regulatory requirements while saving time and resources. Stay ahead of the curve by embracing AI in your SLR process. See how our AI-powered solutions can transform your regulatory processes. Contact us at info@celegence.com to learn more.

As the EU MDR transition deadlines for legacy devices approach, dental device manufacturers face a heightened burden of clinical evidence. In a recent webinar hosted by Celegence, regulatory experts Priya Ray Chaudhuri and Dr. Manaswitha Boyanagari shared hard-earned lessons from working with dental clients through MDR transitions — and offered clear guidance on how to navigate the clinical evaluation process with confidence and precision.

Here are the key takeaways that regulatory and clinical leaders should prioritize when preparing dental device submissions under MDR.

Why Dental Devices Face Increased Scrutiny

Unlike many other device categories, dental products — particularly implants and restorations — directly interact with human tissue, integrate into bone, and often remain in the body permanently. This raises biological risks — such as inflammation, mechanical failure, or peri-implantitis and Bone loss, making robust clinical evidence not just a regulatory expectation, but a public health necessity.

Certain dental devices have also been reclassified under MDR compared to the earlier MDD framework. Devices previously considered low- to moderate-risk under MDD — for example: Dental implants, Bone replacement materials especially if they have a biological effect or are wholly or mainly absorbed, and certain software tools — are now Class IIb or even Class III. The result? New conformity assessments for all medical devices currently circulating within the European Union Member States, complying with the new regulation and new rules. No grandfathering. Manufacturers must justify safety and performance through new, MDR-aligned clinical evidence and additional requirements like submission of implant cards and summary of safety and clinical performance (SSCP) for implantable and Class III devices.

Clinical Evaluation: A Lifecycle, not a Checkbox

In the webinar, Celegence emphasized the need for a lifecycle approach to clinical evaluations, anchored in four key documents:

• Clinical Evaluation Plan (CEP): Defines the claims, population, data sources, and appraisal methods. It’s the foundation for all subsequent activities.
• Clinical Evaluation Report (CER): Synthesizes clinical data, assesses benefit-risk, and demonstrates alignment with the GSPRs.
• State of the Art (SOTA) Review: Establishes the baseline for comparison and benchmarks claims against current best practices.
• Post-Market Clinical Follow-up (PMCF): A must-have for most Class IIb and III devices, PMCF provides real-world evidence to support long-term safety and performance.

Building a Robust Evidence Strategy

Most manufacturers won’t have the luxury of new clinical trials, especially for legacy devices. That makes literature appraisal the backbone of many MDR submissions.

So, it’s important that manufacturers:

• Be precise in defining intended use and claims. Vague terms like “safe” or “effective” won’t pass. Quantify outcomes where possible — e.g., “98% survival at 7 years” — and ensure they match the indications and target population.
• Design a thorough literature strategy. Use smart filters, search across multiple databases, and include gray literature or implant registries. For dental products, state-of-the-art evidence is particularly critical due to variability in patient response and device longevity.
• Critically appraise sources. Not all literature is created equal. Use a scoring matrix based on relevance, quality, and alignment with the device in question. The MIDDEF 2.7/1 guidance remains a good starting point.

Common Pitfalls — and How to Avoid Them

Manufacturers frequently run into the same issues when preparing MDR-ready CERs:

• Claims not linked to evidence. Every claim should tie back to a data point. If the evidence is lacking, that gap must be addressed through PMCF — not ignored.
• Over-reliance on equivalence. MDR has raised the bar for demonstrating equivalence, especially in terms of material and technical characteristics. A titanium implant is not equivalent to zirconia just because they’re both biocompatible.
• Outdated SOTA reviews. Even legacy devices need updated benchmarking. SOTA evidence should typically be refreshed every 12–24 months.
• PMCF treated as an afterthought. PMCF should be risk-driven and strategic, not just a box-checking exercise. Well-designed clinician surveys, registry tracking, or focused case studies can provide meaningful insights — and address notified body feedback proactively.

What Executive Teams Should Take Away

For dental manufacturers, MDR compliance is more than just a regulatory obligation — it’s a strategic imperative. Clinical evaluations must now go beyond generic templates or legacy data. Success requires structured, defensible, and up-to-date documentation.

Leadership teams should ensure they’re resourcing regulatory functions appropriately — with expert partners, robust data collection systems, and cross-functional input from product development and clinical affairs. A well-executed clinical evaluation strategy not only satisfies regulators, it strengthens a company’s competitive standing in a market where performance, aesthetics, and safety all drive success.

Partner With Celegence

MDR clinical evaluations for dental devices don’t need to be overwhelming. With expert support and proven methodologies, you can deliver CERs, SOTAs, and PMCF strategies that align with regulatory expectations and stand up to Notified Body scrutiny.

Work with our regulatory specialists today and simplify your path to MDR compliance with confidence.