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With the intention to provide a robust and economical model that can be used for predicting particle interactions with the pulmonary surfactant, this study was aimed to find an artificial surfactant model that perfectly mimics the properties of the natural pulmonary surfactant. A surfactant model should be reproducible, robust, and able to predict interactions between the pulmonary surfactant and exogenous influences from air and the aqueous site. We compared three synthetic models with the natural bovine surfactant Alveofact. The lung conditions were simulated by spreading the surfactants at the air/aqueous interface on a Langmuir trough with movable barriers. All three artificial surfactant models showed properties very similar to that of Alveofact. Visualization of the monolayers by atomic force microscopy revealed very similar structures with domain formation. The Tanaka lipid mixture has already shown good results in vitro and in vivo in previous studies. The 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC)−1,2-dioleoyl-sn-glycero-3phosphocholine (DOPC) model has large conformations in the surface pressure isotherms and showed a biomimetic exclusion plateau, indicative of an effective lung surfactant formulation. Also, the equilibrium spreading pressure was similar. DPPC−1palmitoyl-2-oleoyl-sn-glycero-3-phospho-1′-rac-glycerol (POPG) had the greatest similarities with Alveofact in the hysteresis areas. The kinetic constants of the relaxation experiments during desorption showed that the PCPG model (at 30 mN/m) had almost identical diffusion and dissolution values as Alveofact. As a proof of concept, the interaction of the models with PLGA nanoparticles showed promising results in all experiments for all the three surfactant models. The results show that the choice of components in a model play a crucial role in obtaining reproducible results. The selected models can be used for further studies as synthetic in vitro lung models.

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