Validation and use of a multiplex assay for the measurement of cytokine concentrations in non-human primate serum

Abstract

Because of the complexity of the cytokine network, an individual cytokine measurement may be difficult to interpret or may provide insufficient information to inform conclusions. Multiplexing technology, which allows for the simultaneous measurement of multiple analytes, has advanced the study of cytokine secretion patterns. However, if cytokines are to be measured and used to make conclusions on research studies, we must understand the variability around the measurement and the potential for errors associated with testing. Method validation procedures generate data that reflect assay performance and identify the inherent measurement uncertainty, allowing data to be accurately interpreted. This study included the design and performance of a multiplex assay validation assessment for the simultaneous measurement of 23 cytokines in non-human primate (NHP) serum. The validation included analysis of serum samples from 36 healthy cynomolgus macaques in order to determine if the method could be used to detect cytokine concentrations in healthy NHP. Although sensitivity and precision data were generally acceptable, recovery and linearity data were highly variable. Of the 23 cytokines tested, 11 met acceptance criteria, 5 were marginal and 7 were rejected. The ability of the method to detect cytokine concentrations was demonstrated and cytokine concentration ranges were presented for 15 cytokines as measured in serum from healthy cynomolgus macaques. If the validation studies had not been performed, false conclusions could be made (overestimated or underestimated cytokine values) contributing to errors within the Total Testing Process. It would be appropriate to continue to evaluate the impact of pre-analytical error (e.g. storage time and temperature, blood collection steps) on the measurement of cytokines in serum from cynomolgus macaques. Because this work demonstrates significant variability among measurements within and between animals, other important next steps include the description of typical variation levels within and between animals, followed by the generation of appropriate (population- or subject-based) reference intervals for healthy animals. It is clear after performing this validation study, that clinical and research investment in multi-analyte methods is not warranted without demonstration of method validity for each analyte of interest.