AI and Automation in Clinical Evaluation Reports (CERs): From Burden to Breakthrough

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.