Challenging the Database: Day-of-Analysis Calibration and UF Modeling for Reliable RRF Use in Medical Device Chemical Characterization
Michael Rush, J. David Ricker, Pramod Prasad Poudel, Nuwan Kothalawala, Cary Watterson, Dmitriy Pastarnak
TL;DR
This paper explores how to improve the accuracy of chemical analysis in medical devices by better using relative response factors.
Contribution
The study introduces a new approach for RRF determination using day-of-analysis calibration and uncertainty factor modeling.
Findings
RRFs are highly context-dependent and influenced by factors like ionization mode and instrument conditions.
Day-of-analysis calibration and uncertainty factor modeling improve reproducibility in quantitation.
The proposed method enhances the reliability of semiquantitative assessments in biocompatibility testing.
Abstract
Accurate quantitation during chemical characterizationalso 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…
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Taxonomy
TopicsEffects and risks of endocrine disrupting chemicals · Pesticide Residue Analysis and Safety · Analytical chemistry methods development