Abstract
The ex vivo isolated perfused rat lung (IPL) model has been demonstrated to be a useful tool during drug development for studying pulmonary drug absorption. This study aims to investigate the potential use of IPL data to predict rat in vivo lung absorption. Absorption parameters determined from IPL data (ex vivo input parameters) in combination with intravenously determined pharmacokinetic data were used in a biopharmaceutics model to predict experimental rat in vivo plasma concentration-time profiles and lung amount after inhalation of five different inhalation compounds. The performance of simulations using ex vivo input parameters was compared with simulations using in vitro input parameters, to determine whether and to what extent predictability could be improved by using input parameters determined from the more complex ex vivo model. Simulations using ex vivo input parameters were within twofold average difference (AAFE < 2) from experimental in vivo data for all compounds except one. Furthermore, simulations using ex vivo input parameters performed significantly better than simulations using in vitro input parameters in predicting in vivo lung absorption. It could therefore be advantageous to base predictions of drug performance on IPL data rather than on in vitro data during drug development to increase mechanistic understanding of pulmonary drug absorption and to better understand how different substance properties and formulations might affect in vivo behavior of inhalation compounds.
Highlights
Pulmonary drug delivery is the preferred administration route for the treatment of lung diseases such as asthma, chronic obstructive lung disease, and cystic fibrosis [1]
The simulations using ex vivo input parameters were within twofold average difference (AAFE < 2) from the experimental in vivo data for all active pharmaceutical ingredients (APIs) except FP (Fig. 2, Table III)
The simulations with higher bronchial permeabilities and a higher Al:Tb ratio gave a comparatively similar plasma concentration-time profile (Fig. 2, Table III). With these modified simulation settings, the predicted Cmax improved for AZD5423, FP, and salmeterol, and average fold error (AAFE) improved for AZD5423, FP, and salbutamol compared with the initial simulation settings (Table III)
Summary
Pulmonary drug delivery is the preferred administration route for the treatment of lung diseases such as asthma, chronic obstructive lung disease, and cystic fibrosis [1]. Optimal pulmonary drug delivery of locally acting active pharmaceutical ingredients (APIs) includes high local concentration, extended lung residence time, and low systemic concentration [2]. These properties enhance the pharmacological effect and decrease the dosing frequency, which improves compliance and reduces the risk of systemically adverse effects [2]. The drug absorption rate for solutes has previously been shown to correlate well between the IPL model and in vivo studies, which suggest that parameters obtained from the IPL model are potentially in vivo predictive [9]. These advantages suggest that the IPL model may offer better opportunities than the more complex in vivo method for investigating drug absorption rate and mechanisms for solutes and different inhalation formulations
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