Pulmonary drug absorption and systemic exposure in human: Predictions using physiologically based biopharmaceutics modeling

Abstract

Systemic exposure of inhaled drugs is used to estimate the local lung exposure and assess systemic side effects for drugs with local pharmacological targets. Predicting systemic exposure is therefore central for successful development of drugs intended to be inhaled. Currently, these predictions are based mainly on data from in vitro experiments, but the accuracy of these predictions might be improved if they were based on data with higher physiological relevance. In this study, systemic exposure was simulated by applying biopharmaceutics input parameters from isolated perfused rat lung (IPL) data to a lung model developed in MoBi® as an extension to the full physiologically-based pharmacokinetic (PBPK) model in PK-Sim®. These simulations were performed for a set of APIs with a variety of physicochemical properties and formulation types. Simulations based on rat IPL data were also compared to simulations based on in vitro data. The predictive performances of the simulations were evaluated by comparing simulated plasma concentration-time profiles to clinical observations after pulmonary administration. Simulations using IPL-based input parameters predicted systemic exposure well, with predicted AUCs within two-fold of the observed value for nine out of ten drug compounds/formulations, and predicted Cmax values within two-fold for eight out of ten drug compounds/formulations. Simulations using input parameters based on IPL data performed generally better than simulations based on in vitro input parameters. These results suggest that the developed model in combination with IPL data can be used to predict human lung absorption for compounds with different physicochemical properties and types of inhalation formulations.