Background: Predicting local lung tissue pharmacodynamic (PD) responses of inhaled drugs is a longstanding challenge related to the lack of experimental techniques to determine local free drug concentrations. This has prompted the use of physiologically based pharmacokinetic (PBPK) modeling to potentially predict local concentration and response. A unique opportunity for PBPK model evaluation is provided by the clinical PD data for salbutamol, which in its inhaled dosage form (400 μg), produces a higher bronchodilatory effect than in its oral dosage form (2 mg) despite lower drug concentrations in blood. The present study aimed at evaluating whether inhalation PBPK model predictions of free drug in tissue would be predictive of these observations.
Methods: A PBPK model, including 24 airway generations, was parameterized to describe lung, plasma, and epithelial lining fluid concentrations of salbutamol administered intratracheally and intravenously to rats (100 nmol/kg). Plasma and lung tissue concentrations of unbound (R)-salbutamol, the active enantiomer, were predicted with a humanized version of the model and related to effect in terms of forced expiratory volume in 1 second (FEV1).
Results: In contrast to oral dosing, the model predicted inhalation to result in spatial heterogeneity in the target site concentrations (subepithelium) with higher free drug concentrations in the lung as compared with the plasma. FEV1 of inhaled salbutamol was accurately predicted from the PK/PD relationship derived from oral salbutamol and PBPK predictions of free concentration in airway tissue of high resistance (e.g., 6th generation).
Conclusion: An inhalation PBPK-PD model was developed and shown predictive of local pharmacology of inhaled salbutamol, thus conceptually demonstrating the validity of PBPK model predictions of free drug concentrations in lung tissue. This achievement unlocks the power of inhalation PBPK modeling to interrogate local pharmacology and guide optimization and development of inhaled drugs and their formulations.
Keywords: PBPK modeling; PK/PD; inhaled delivery; translation.