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Challenging the Database: Day-of-Analysis Calibration and UF Modeling for Reliable RRF Use in Medical Device Chemical Characterization

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Challenging_the_Database_Day-of-Analysis_Calibration_and_UF_Modeling_for_Reliable_RRF_Use_in_Medical_Device_Chemical_Characterization/30305427
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Accurate quantitation during chemical characterizationalso referred to as extractables and leachables (E&L)within a toxicological risk assessment for medical device biocompatibility hinges on the appropriate application of relative response factors (RRFs). This study investigates the variability of RRFs across a chemically diverse set of compounds and evaluates the implications of quantitation model selection on analytical outcomes. Using gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS), we demonstrate that RRFs are highly context-dependent and influenced by factors such as ionization mode, compound class, concentration, and instrument conditions. We propose an approach to RRF determination, emphasizing day-of-analysis calibration and uncertainty factor modeling to improve reproducibility. Our findings support a statistically grounded application of analytical evaluation thresholds, enhancing the reliability of semiquantitative assessments in medical device biocompatibility.
创建时间:
2025-10-08
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