Abstract
Calibration curves for ligand binding assays are generally characterized by a nonlinear relationship between the mean response and the analyte concentration. Typically, the response exhibits a sigmoidal relationship with concentration. The currently accepted reference model for these calibration curves is the 4-parameter logistic (4-PL) model, which optimizes accuracy and precision over the maximum usable calibration range. Incorporation of weighting into the model requires additional effort but generally results in improved calibration curve performance. For calibration curves with some asymmetry, introduction of a fifth parameter (5-PL) may further improve the goodness of fit of the experimental data to the algorithm. Alternative models should be used with caution and with knowledge of the accuracy and precision performance of the model across the entire calibration range, but particularly at upper and lower analyte concentration areas, where the 4- and 5-PL algorithms generally outperform alternative models. Several assay design parameters, such as placement of calibrator concentrations across the selected range and assay layout on multiwell plates, should be considered, to enable optimal application of the 4- or 5-PL model. The fit of the experimental data to the model should be evaluated by assessment of agreement of nominal and model-predicted data for calibrators.