Reducing relative response factor variation using a multidetector approach for extractables and leachables (E&L) analysis to mitigate the need for uncertainty factors

Autor: Mark Anderson Jordi, Kaitlin Lerner, Weixi Liu, Zhu Liang, Xingluan Cao, Jie Zong, Kevin Rowland, Michael Louis, Yuan Ren, Xiao Zhou
Rok vydání: 2020
Předmět:
Zdroj: Journal of Pharmaceutical and Biomedical Analysis. 186:113334
ISSN: 0731-7085
Popis: Characterization of Extractables and Leachables (E&Ls) is an important aspect of product quality in important fields such as pharmaceuticals, medical devices and food contact materials. The main goal of an E&L study is identification and quantification of those species which may leach from packaging materials used to contain pharmaceuticals or which may leach directly out of a medical device or food contact material and thus may result in patient exposure. It is common practice to perform relative quantitation of extractables and leachables using surrogate standards due to the large diversity of species observed and the lack of available reference standards. A key problem in obtaining accurate E&L results arises due to response factor (RF) variation. Different compounds at the same concentration give different signal intensities and thus have different RF values. Two key aspects of study quality are affected by this problem. First, the evaluation of the number of compounds which are above the toxicologically relevant threshold (analytical evaluation threshold, (AET)) can be affected (RF Problem 1: AET Underreporting). Second, quantitative accuracy is affected which can reduce the reliability of the margin of safety (MOS) calculations which serves as the basis of the toxicological evaluation (RF Problem 2: Quantitative Error). RF databases have been the main solution proposed for solving these problems but do not reduce the underlying RF variation and lack the scope required to address quantitative error for compounds not contained in the database. In the absence of other solutions, large uncertainty factors (UF) have been applied in the AET calculations to account for RF Problem 1: AET Underreporting. These UF factors have been assigned values of 4 for GCMS and up to 10 for LCMS. Large uncertainty factors have a number of unintended negative consequences including the need for large amounts of sample concentration (>10X) prior to analysis resulting in potential compound loss or degradation and increased matrix effects. To overcome these problems, this publication demonstrates a multidetector approach using an HPLC system coupled with a Quadrupole Time of Flight Liquid Chromatography Mass Spectrometer (QTOF-LCMS), Charged Aerosol Detector (CAD) and an Ultraviolet-Visible Detector (UV) and a dual detection Gas Chromatography Mass Spectrometry (GCMS) system using a Polyarc Reactor system with Flame Ionization Detection (FID). Herein, it is demonstrated that this combination of methods (the multidetector approach) allowed detection and accurate surrogate standard quantitation of 217 unique extractables spanning a wide range of chemical properties (Mw, logP, pKa and boiling point). The combination of optimized detector selection with appropriate standard selection was verified to provide positive detection for 94% of the compounds at the AET level and a high level of quantitative accuracy (± 20% for 85% of the compounds and ±40% for 91% of the compounds) while using only a UF of 2. Unlike the RF database approach, the multidetector approach is not limited to only those compounds contained in the database but is applicable to the majority of extractables.
Databáze: OpenAIRE
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