Optimality assessment in the enzyme-linked immunosorbent assay (ELISA).

An optimality criterion is proposed for evaluating the precision of alternative designs in the enzyme-linked immunosorbent assay. Assay profiles are represented as four-parameter logistic functions with parameter estimation based on either a weighted nonlinear regression or a simple nonlinear regression after a logarithmic transformation. Assay design changes are characterized in terms of their effects on parameters in the four-parameter logistic model. General optimality results are derived for the variance of relative potency estimates in routine assay applications.