Findlay J W, Smith W C, Lee J W, Nordblom G D, Das I, DeSilva B S, Khan M N, Bowsher R R
Metabolism and Safety Evaluation, Searle, Skokie, IL 60077, USA.
J Pharm Biomed Anal. 2000 Jan;21(6):1249-73. doi: 10.1016/s0731-7085(99)00244-7.
Immunoassays are bioanalytical methods in which quantitation of the analyte depends on the reaction of an antigen (analyte) and an antibody. Although applicable to the analysis of both low molecular weight xenobiotic and macromolecular drugs, these procedures currently find most consistent application in the pharmaceutical industry to the quantitation of protein molecules. Immunoassays are also frequently applied in such important areas as the quantitation of biomarker molecules which indicate disease progression or regression, and antibodies elicited in response to treatment with macromolecular therapeutic drug candidates. Currently available guidance documents dealing with the validation of bioanalytical methods address immunoassays in only a limited way. This review highlights some of the differences between immunoassays and chromatographic assays, and presents some recommendations for specific aspects of immunoassay validation. Immunoassay calibration curves are inherently nonlinear, and require nonlinear curve fitting algorithms for best description of experimental data. Demonstration of specificity of the immunoassay for the analyte of interest is critical because most immunoassays are not preceded by extraction of the analyte from the matrix of interest. Since the core of the assay is an antigen-antibody reaction, immunoassays may be less precise than chromatographic assays; thus, criteria for accuracy (mean bias) and precision, both in pre-study validation experiments and in the analysis of in-study quality control samples, should be more lenient than for chromatographic assays. Application of the SFSTP (Societe Francaise Sciences et Techniques Pharmaceutiques) confidence interval approach for evaluating the total error (including both accuracy and precision) of results from validation samples is recommended in considering the acceptance/rejection of an immunoassay procedure resulting from validation experiments. These recommendations for immunoassay validation are presented in the hope that their consideration may result in the production of consistently higher quality data from the application of these methods.
免疫测定是一种生物分析方法,其中分析物的定量取决于抗原(分析物)与抗体的反应。尽管适用于低分子量外源性物质和大分子药物的分析,但这些方法目前在制药行业中最常用于蛋白质分子的定量。免疫测定还经常应用于诸如指示疾病进展或消退的生物标志物分子的定量,以及针对大分子治疗药物候选物治疗产生的抗体等重要领域。目前可用的涉及生物分析方法验证的指导文件仅有限地涉及免疫测定。本综述强调了免疫测定与色谱测定之间的一些差异,并针对免疫测定验证的具体方面提出了一些建议。免疫测定校准曲线本质上是非线性的,需要非线性曲线拟合算法来最佳描述实验数据。证明免疫测定对目标分析物的特异性至关重要,因为大多数免疫测定在从感兴趣的基质中提取分析物之前进行。由于该测定的核心是抗原 - 抗体反应,免疫测定可能不如色谱测定精确;因此,在研究前验证实验以及研究中质量控制样品分析中,准确性(平均偏差)和精密度的标准应该比色谱测定更宽松。在考虑验证实验产生的免疫测定程序的接受/拒绝时,建议应用法国制药科学与技术协会(SFSTP)置信区间方法来评估验证样品结果的总误差(包括准确性和精密度)。提出这些免疫测定验证建议的目的是希望对其进行考虑可能会使这些方法的应用产生始终更高质量的数据。