Mastering Clinical Literature Evaluation: From PICO Frameworks to AI Automation

Mastering Clinical Literature Evaluation: From PICO Frameworks to AI Automation

Literature evaluation is not just a regulatory hurdle; it is a foundational part of any Clinical Evaluation Report (CER) and Post-Market Clinical Follow-up (PMCF). As medical devices become more complex, the volume of clinical data is surging, making structured, reproducible search strategies more critical than ever.

The Structured Journey of Data Identification

A compliant literature review begins with identifying relevant clinical data through precise, Boolean-based queries. To maintain objectivity and reproducibility, regulatory professionals rely on established frameworks:

• PICO Method: Defining the Population, Intervention, Comparison, and Outcomes.
• PRISMA/MOOSE: Structured reporting methods to ensure transparency.
• Database Selection: Utilizing high-quality sources such as PubMed (NLM), Cochrane, ClinicalTrials.gov, and ScienceDirect.

Screening and Appraisal: The Core of Quality

Once results are retrieved, the focus shifts to screening based on pre-defined inclusion and exclusion criteria. Following screening, the Appraisal phase verifies that the selected data is:

• Relevant: Directly applicable to the device under evaluation.
• Valid: Scientifically and statistically sound.
• Sufficient: Providing enough volume to support conclusions.
• Unbiased: Minimally influenced by commercial or methodological conflicts.

The Role of AI in Reducing Regulatory Workload

Manual literature evaluation is notoriously time-consuming. However, emerging automation tools—validated under ISO/TR 80002-2—are transforming clinical workflows. Features like AI screening support for excluding non-human studies and agentic data extraction can reduce processing time by up to 56%. These tools provide "Audit Assurance," ensuring that critical data is not missed even beyond initial queries.

Analysis and Compliance with GSPR

With validated data in hand, the analysis must align with General Safety and Performance Requirements (GSPR) 1, 6, and 8. A clinical expert must review the findings to ensure conclusions are evidence-based and reflect the current State of the Art (SOTA). Where data gaps appear, they must be addressed through strategic PMCF planning.

Conclusion

Literature evaluation is a continuous loop. Every new SOTA assessment or PMCF update requires a fresh dive into the data. By combining rigorous scientific frameworks like PICO with modern AI automation, manufacturers can maintain high compliance standards while significantly accelerating their time to market.