Developing an Inhaled NEU1 Inhibitor for Cystic Fibrosis via Pharmacokinetic and Biophysical Modeling

Background: Cystic fibrosis (CF) airway mucus exhibits reduced mucin sialylation, increasing viscosity and impairing mucociliary clearance (MCC). NEU1 inhibition has been proposed to restore MCC, but its quantitative pharmacokinetic and rheological effects, particularly with inhaled delivery, remain uncharacterized. Objective: To develop an integrated pharmacokinetic/pharmacodynamic (PK/PD) and biophysical model to assess the efficacy of an inhaled NEU1 inhibitor. Methods: Empirical and preclinical NEU1 inhibition data were combined with inhalation PK/PD modeling and a biophysical viscosity framework linking mucin sialylation and extracellular DNA. Synthetic cohort simulations (N = 200) were reconciled with empirical PK benchmarks using Latin hypercube parameter sampling. Cross-validation, hold-out testing, and causal inference methods (inverse probability of treatment weighting and targeted maximum likelihood estimation) quantified predicted effects on lung function (delta FEV1). Results: With reconciled parameters (F_dep = 0.12; k_abs = 0.21 per hour; k_muc = 0.24 per hour), epithelial lining fluid drug levels reached a peak concentration of 7.5 micromolar (95 percent CI: 6 to 10 micromolar), achieving IC50 coverage for approximately 10 hours per day and greater than 80 percent modeled NEU1 inhibition. Predicted mucus viscosity reduction averaged 25 to 28 percent. Causal inference estimated delta FEV1 improvement of +0.13 liters (95 percent CI: 0.10 to 0.15 liters), with about 70 percent mediated via MCC. Conclusions: Empirically anchored PK/PD and biophysical modeling support the feasibility of inhaled NEU1 inhibition as a rheology-targeting strategy in CF, projecting clinically realistic efficacy while maintaining pharmacological viability. This calibrated proof of concept warrants in vivo validation in CF models.