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Level A in vivo-in vitro correlation: nonlinear models and statistical methodology.

Some new nonlinear models for the relationship between the fraction of drug dose dissolved (absorbed) in vivo and that dissolved in vitro are described. The models are empirical in nature and are generalizations of the linear model that, at present, is the most commonly used model. The modeling approach is based on considering the time at which a drug molecule goes into solution (in vitro or in vivo) to be a random variable and relating the distribution functions using proportional odds, proportional hazards, and proportional reversed hazards models. The models are further extended by allowing the parameter that relates in vivo and in vitro to be a function of time. A statistical model for the data is developed and used as the basis for a statistical methodology for fitting these models. The methods are shown to be generalized linear mixed effects model (GLMM) methods. The models are fitted to some data sets, and the results demonstrate that these models have potential.