Godage Nipunika H, Qian Song S, Cudjoe Erasmus, Gionfriddo Emanuela
Department of Chemistry and Biochemistry, College of Natural Sciences and Mathematics, The University of Toledo, Toledo, Ohio 43606, United States.
School of Green Chemistry and Engineering, The University of Toledo, Toledo, Ohio 43606, United States.
ACS Meas Sci Au. 2023 Dec 5;4(1):127-135. doi: 10.1021/acsmeasuresciau.3c00049. eCollection 2024 Feb 21.
This study addresses the challenges of matrix effects and interspecies plasma protein binding (PPB) on measurement variability during method validation across diverse plasma types (human, rat, rabbit, and bovine). Accurate measurements of small molecules in plasma samples often require matrix-matched calibration approaches with the use of specific plasma types, which may have limited availability or affordability. To mitigate the costs associated with human plasma measurements, we explore in this work the potential of cross-matrix-matched calibration using Bayesian hierarchical modeling (BHM) to correct for matrix effects associated with PPB. We initially developed a targeted quantitative approach utilizing biocompatible solid-phase microextraction coupled with liquid chromatography-mass spectrometry for xenobiotic analysis in plasma. The method was evaluated for absolute matrix effects across human, bovine, rat, and rabbit plasma comparing pre- and postmatrix extraction standards. Absolute matrix effects from 96 to 108% for most analytes across plasma sources indicate that the biocompatibility of the extraction phase minimizes interference coextraction. However, the extent of PPB in different media can still affect the accuracy of the measurement when the extraction of small molecules is carried out via free concentration, as in the case of microextraction techniques. In fact, while matrix-matched calibration revealed high accuracy, cross-matrix calibration (e.g., using a calibration curve generated from bovine plasma) proved inadequate for precise measurements in human plasma. A BHM was used to calculate correction factors for each analyte within each plasma type, successfully mitigating the measurement bias resulting from diverse calibration curve types used to quantify human plasma samples. This work contributes to the development of cost-effective, efficient calibration strategies for biofluids. Leveraging easily accessible plasma sources, like bovine plasma, for method optimization and validation prior to analyzing costly plasma (e.g., human plasma) holds substantial advantages applicable to biomonitoring and pharmacokinetic studies.
本研究探讨了在跨多种血浆类型（人、大鼠、兔和牛）的方法验证过程中，基质效应和种间血浆蛋白结合（PPB）对测量变异性的挑战。血浆样本中小分子的准确测量通常需要使用特定血浆类型的基质匹配校准方法，而这些血浆类型可能可用性有限或成本过高。为了降低与人类血浆测量相关的成本，我们在这项工作中探索了使用贝叶斯层次模型（BHM）进行跨基质匹配校准以校正与PPB相关的基质效应的潜力。我们最初开发了一种靶向定量方法，利用生物相容性固相微萃取结合液相色谱 - 质谱法进行血浆中外源性物质的分析。通过比较基质提取前后的标准品，评估了该方法在人、牛、大鼠和兔血浆中的绝对基质效应。大多数分析物在不同血浆来源中的绝对基质效应为96%至108%，这表明萃取相的生物相容性使干扰共萃取最小化。然而，当通过游离浓度进行小分子萃取时，如在微萃取技术中，不同介质中PPB的程度仍会影响测量的准确性。事实上，虽然基质匹配校准显示出高精度，但跨基质校准（例如，使用从牛血浆生成的校准曲线）在人血浆的精确测量中被证明是不足的。使用BHM计算每种血浆类型中每种分析物的校正因子，成功减轻了用于量化人血浆样本的不同校准曲线类型导致的测量偏差。这项工作有助于开发具有成本效益、高效的生物流体校准策略。在分析昂贵的血浆（如人血浆）之前，利用易于获取的血浆来源（如牛血浆）进行方法优化和验证，具有适用于生物监测和药代动力学研究的显著优势。
