Ligand binding assay precision

The fundamental parameters for bioanalytical validations include accuracy, precision, selectivity, sensitivity, reproducibility, stability of the drug in the matrix under study storage conditions, range, recovery, and response function (see Section 8.2.1). These parameters are also applicable to microbiological and ligand-binding assays. However, these assays possess some unique characteristics that should be considered during method validation, such as selectivity and quantification issues. 

The ultimate goal of an assay or an analytical procedure is to measure accurately a quantity or a concentration of an analyte, or to measure a specific activity, as in some assays for biomarkers. However, many activity assays, such as cell-based and enzyme activity assays, may not be very sensitive, may lack precision, and/or do not include the use of definitive reference standards. Assays based on measurements of physicochemical (such as chromatographic methods) or biochemical (such as ligand-binding assays) attributes of the analyte assume that these quantifiable characteristics are reflective of the quantities, concentration, or biological activity of the analyte. For the purpose of bioanalytical method validation, we will follow the recently proposed classifications for assay data by Lee et al. [4,5]. These classifications, as summarized below, provide a clear distinction with respect to analytical validation practices and requirements. 

The primary performance measures of a ligand-binding assay are bias/trueness and precision. These measures along with the total error are then used to derive and evaluate several other performance characteristics such as sensitivity (LLOQ), dynamic range, and dilutional linearity. Estimation of the primary performance measures (bias, precision, and total error) requires relevant data to be generated from a number of independent runs (also termed as experiments or assay s). Within each run, a number of concentration levels of the analyte of interest are tested with two or more replicates at each level. The primary performance measures are estimated independently at each level of the analyte concentration. This is carried out within the framework of the analysis of variance (ANOVA) model with the experimental runs included as a random effect [23]. Additional terms such as analyst, instmment, etc., may be included in this model depending on the design of the experiment. This ANOVA model allows us to estimate the overall mean of the calculated concentrations and the relevant variance components such as the within-run variance and the between-run variance. 

Statistical evaluation should be considered, from its simplest form of assessment of the precision and accuracy to complex statistical analysis, as discussed by Kringle et al. [7]. Although Kringle s focus is on methods for analysis of pharmaceutical formulations, his application of statistics could be expanded to ligand-binding assays. He concludes that the acceptability of two methods should be evaluated using... 

Due to the method principle, ligand-binding assays are inherently non-linear. Thus, four- and five-parameter mathematic models are used to create calibration curves, and consequently a higher number of calibration points is needed to define the curve most accurately. Especially in the asymptotic parts of the calibration curve, a sufficient number of calibrators must be placed to define upper and lower limits of quantification with pre-defined accuracy and precision. Unless it is shown that matrix constituents have no impact on detection signals, calibration curves must be prepared in an authentic matrix. 

For each in-study run, the standard curve must satisfy criteria described in the standard-curve section however, run acceptance is based primarily on the performance of the QC samples. When using total error for ligand binding assays of macromolecules, the run acceptance criteria recommended in the precision and accuracy section requires that at least four of six (67%) QC results must be within 30% of their nominal values, with at least 50% of the values for each QC level satisfying the 30% limit. The recommended 4-6-30 rule imposes limits simultaneously on the allowable random error (imprecision) and systematic error (mean bias). If the application of an assay requires a QC target acceptance limit different than the 30% deviation from the nominal value, then prestudy acceptance criteria for precision and accuracy should be adjusted so that the limit for the sum of the interbatch imprecision and absolute mean RE is equal to the revised QC acceptance limit. 

A limitation of the flow cytometric binding assay has been the precise determination of the receptor affinity and calculation of the receptors per cell. This limitation appears to have been overcome by the development of fluorescein and phycoerythrin compensation-calibration standards (Flow Cytometry Standards Corp., Research Triangle Park, NC). These standards have made it possible to quantify the fluorescence intensity of samples labeled with fluorescein or phycoerythrin, and relate the intensity to molecules of equivalent soluble fluorochrome. These standards have been utilized in quantitative studies of neutrophil chemoattractant-ligand interaction (4). 

Values of 20% (25% at lower limit of quantification [LLOQ]) are recommended as default acceptance criteria for accuracy and inter-batch precision for ligand binding in practical use. Precision and accuracy should be established by analyzing four sets of QC samples at LLOQ, low, medium, and high levels in duplicate in six different batches during method development. In addition, a second proposed criterion for method acceptance takes into account the sum of inter-batch precision and the absolute value of accuracy be <30%. During practical application of such assays, the 4-6-30-rule may be applied - that is, for each batch four out of six QC samples must be within 30% of nominal concentration, but the two failed QC samples may not be at the same level. 

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