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Mucus is a natural barrier with a protective role that hinders drug diffusion, representing a steric and interactive barrier to overcome for an effective drug delivery to target sites. In diseases like cystic fibrosis (CF), pulmonary mucus exhibits altered features, which hamper clearance mechanisms and drug diffusion, ultimately leading to lung failure. Effectively modelling the passage through mucus still represents an unmet challenge. An airway CF mucus model is herein proposed to disassemble the complexity of the mucus barrier following a modular approach. A hydrogel, mainly composed of mucin in an alginate (Alg) network, is proposed to specifically model the chemical-physical properties of CF mucus. The steric retention of pathological mucus was reproduced by targeting its mesh size (approximately 50 nm) and viscoelastic properties. The interactive barrier was reproduced by a composition inspired from the CF mucus. Optimized mucus models, composed of 3 mg ml-1 Alg and 25 mg ml-1 mucin, exhibited a G' increasing from ∼21.2 to 55.2 Pa and a G'' ranging from ∼5.26 to 28.8 Pa in the frequency range of 0.1 to 20 Hz. Drug diffusion was tested using three model drugs. The proposed mucus model was able to discriminate between the mucin-drug interaction and the steric barrier of a mucus layer with respect to the parallel artificial membrane permeability (PAMPA) that models the phospholipidic cell membrane, the state-of-the-art screening tool for passive drug diffusion. The mucus model can be proposed as an in vitro tool for early drug discovery, representing a step forward to model the mucus layer. Additionally, the proposed methodology allows to easily include other molecules present within mucus, as relevant proteins, lipids and DNA.

Disassembling the complexity of mucus barriers to develop a fast screening tool for early drug discovery