In this webinar, presented by our Senior Technical Advisor, Philippe Verlinde, PhD, you’ll gain more insights into the latest FDA recommendations and how the CLAP-List can be leveraged to enhance chemical characterization studies.
The “Chemical List of Analytical Performance” (CLAP) published by the FDA (CDRH) could be a significant catalyst for improving and harmonizing chemical analyses for Biocompatibility assessment of medical devices.
Non-Target Analytical Methods (NTA-Methods) that are used for these types of analyses can exhibit a high level of variance and uncertainty and henceforth the CLAP can be considered a large step forward to address these inter- and intra-lab variability issues.
Nelson Labs has populated an extractable database with analytical information (MS, RT/RI, RRF) obtained through the analysis of 5000+ authentic reference standards and has evaluated the alignment of that chemical space with the chemical space of the CLAP compounds. A comparative evaluation of the distribution of the physico-chemical properties shows that for most parameters, the CLAP-compounds are a generally good cross-section of the broader population of extractable compounds present in the Nelson database. However, when comparing the CLAP list compounds to Nelson’s most frequently reported extractable compounds, it was observed that the CLAP compounds are not consistently among the most frequently reported compounds. This exercise supports the relevancy of the selected compounds from both sides and allows us to present scientific quality improvement opportunities in extractable testing in terms of how a lab could use the CLAP list to set the basis for:
- Optimizing analytical methodologies to obtain the broadest coverage by minimizing gaps and addressing the uncertainty in detectability of a relevant set of compounds.
- Understanding variability of responses per technique
- Providing the basis to calculate Uncertainty Factors (UF) based on a reference set of compounds.
- Calculating the coverage for a methodology, using the derived UF.
- Providing the basis of a new way of generating Quantitative data: the RRF-approach.
- Minimizing inter-lab variability in Chemical Characterization results.
