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IVDR Performance Evaluation: NB Review Explained

Bioexcel News

  1. Scientific validity
  2. Analytical performance
  3. Clinical performance

  • Does the evidence clearly support the intended purpose?
  • Are performance claims defensible?
  • Is the evidence internally consistent?
  • Can regulatory decisions be made confidently using this data?

  • Clear linkage between the analyte and the clinical condition
  • Robust literature or guideline support
  • Justification that the biological rationale is accepted
  • Weak or outdated literature
  • Overreliance on internal rationale
  • Poor alignment between scientific validity and claimed clinical utility

  • Are analytical studies appropriate for the intended use?
  • Are performance characteristics (e.g., sensitivity, specificity, precision) relevant and justified?
  • Are acceptance criteria clinically and statistically defensible?
  • Acceptance criteria chosen without clinical justification
  • Studies conducted correctly but designed without regulatory context
  • Results that cannot be clearly linked to performance claims

  • Does the clinical evidence demonstrate performance in the target population?
  • Are study populations representative of intended users and settings?
  • Can results be generalized to real-world use?
  • Study populations not aligned with intended use
  • Endpoints that do not directly support claims
  • Difficulty integrating study data into the PER narrative

  • Scientific validity, analytical performance, and clinical performance are coherent
  • Conclusions are supported by data not assumptions
  • Gaps are identified and justified
  • Residual uncertainty is acknowledged and controlled

  • Disconnected evidence across the three pillars
  • Overconfidence in completed studies
  • Lack of clear justification for design choices
  • Poor traceability between claims, data, and conclusions

  • Early alignment between intended purpose and evidence strategy
  • Performance studies designed with PER integration in mind
  • Clear justification of endpoints, populations, and acceptance criteria
  • Transparent handling of limitations and residual risks

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