Physiologically Based Pharmacokinetic Modeling of Digoxin in Adult and Pediatric Patients with Heart Failure

Background/Objectives: Digoxin is a cardiotonic agent with a narrow therapeutic window and a high risk of toxicity. The current clinical use is based on an empirically FDA-recommended regimen which has wide dosing ranges, introducing the risk of inappropriate dosing and related adverse events. This study aims to develop a physiologically based pharmacokinetic (PBPK) model to characterize digoxin pharmacokinetics in adult and pediatric patients with heart failure, and then to evaluate the FDA-recommended regimen. Methods: The PBPK model was initially developed in healthy adults using PK-Sim^®. Then, it was translated to adults with heart failure by incorporating disease factors. Next, it was further translated to pediatrics by scaling age-related parameters. Finally, through two-step translations, the model was used to evaluate current dosing regimens to inform safety and effectiveness based on observing predicted trough concentrations at a steady state. Results: This PBPK model has strong predicting ability, where observed concentrations and key PK metrics (C_max, AUC_0-t) were within 0.5-2.0-fold of predictions in healthy adults, adults with heart failure, neonates, and infants. The model prediction work on the evaluation of recommended dosing regimens from the FDA shows that the current regimen may not achieve the lowest boundary of the therapeutic window (0.5-2 ng/mL) in neonates (0-30 days), whereas infants (1-2 months) and children (<18 years) are generally good within it. Conclusions: This PBPK model explained major physiological and pathological contributors to differences in digoxin pharmacokinetics across populations and showed good performance in pediatric extrapolation. It also pointed out the shortage of empirical dosing regimens for such a drug with a narrow therapeutic window. The model may assist in optimizing the pediatric dosing strategies of digoxin, and suggests that current neonatal dosing regimens need refinement.