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Abstract

The inhibitory capacity of a competitive antagonist is measured using the pA2 (the negative logarithm of the antagonist dissociation constant). The conventional two-step procedure, based on Schild's regression, neglects a portion of the errors. New single step methods are proposed based on nonlinear regression on dose-effect. Whereas verification of the competition hypothesis often interferes with pA2 estimation, the development of improved nonlinear models could explain and partially incorporate the reasons for noncompetition. The improvements are of two kinds: 1. Pharmacological, based on the inclusion of suspected pharmacological mechanisms such as spare receptors or transduction into a nonlinear fixed-effects model (with examples from the literature); and 2. Experimental, incorporating biovariability as a random effect into a mixed-effects model.

Keywords

pA2 Competitive inhibition Schild's regression Nonlinear regression mixed models

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Competitive Antagonism in Pharmacology: A Proposed Single Step Evaluation *

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