Background/Objectives: Carboxylesterase 1 (CES1) is a key enzyme involved in the bioactivation of ester prodrugs. This study aimed to construct a mechanistic, whole-body, physiologically based pharmacokinetic (PBPK) model to simultaneously predict the pharmacokinetics of CES1-activated prodrugs and their metabolites across different age groups. Methods: A comprehensive whole-body prodrug–metabolite PBPK framework was constructed by integrating age-specific physiological parameters. Oseltamivir and enalapril were evaluated across adult, pediatric, and geriatric populations, whereas cilazapril validation was focused on adult and geriatric cohorts based on clinical data availability. The model was developed and validated in adults, and then extrapolated to pediatric and geriatric populations. Model performance was evaluated by comparing predicted and observed pharmacokinetic parameters, specifically the area under the curve (${AUC}_{0-t}$) and maximum plasma concentration ($C_{max}$), with an acceptance criterion of 0.5- to 2.0-fold error. Results: The majority of observed plasma concentrations fell within the 5th–95th percentiles of predicted profiles. Additionally, for most simulations, the ${AUC}_{0-t}$ and $C_{max}$ were within 0.5- to 2-fold of the observed values. Sensitivity analyses revealed that the exposure of their active metabolites was highly related to the plasma unbound fraction, glomerular filtration rate, and hepatic CES1-mediated bioactivation. Conclusions: This whole-body PBPK framework provides a mechanistic basis for predicting CES1-mediated prodrug disposition across age groups. The framework achieved clinical validation across pediatric, adult, and geriatric populations for oseltamivir and enalapril, and provided proof-of-concept support for extending the approach to cilazapril. This platform may serve as a basis for future pharmacokinetic/pharmacodynamic integration and model-informed dose optimization.

Background: Heart failure (HF), as the end stage of various cardiac diseases, alters blood flow to key organs responsible for drug clearance. This can lead to unpredictable and often suboptimal drug exposure, creating a critical need for quantitative tools to guide precise dosing in this vulnerable population. Methods: This study aimed to establish a whole-body physiologically based pharmacokinetic (PBPK) model for characterizing drug pharmacokinetics in both healthy subjects and patients across the HF severity spectrum. Eight commonly used drugs (digoxin, furosemide, bumetanide, torasemide, captopril, valsartan, felodipine and midazolam) for treating HF and its comorbidities were selected. Following successful validation against clinical data from healthy subjects, the PBPK model was extrapolated to HF patients. Pharmacokinetics of the eight drugs in 1000 virtual HF patients were simulated by replacing tissue blood flows and compared using clinical observations. Results: Most of the observed concentrations were encompassed within the 5th–95th percentiles of simulated values from 1000 virtual HF patients. Predicted area under the concentration–time curve and maximum plasma concentration fell within the 0.5~2.0-fold range relative to clinical observations. Sensitivity analysis demonstrated that intrinsic renal clearance, unbound fraction in blood, muscular blood flow, and effective permeability coefficient significantly impact plasma exposure of digoxin at a steady state. Oral digoxin dosing regimens for HF patients were optimized via the validated PBPK model to ensure that steady-state plasma concentrations in all HF patients remain below the toxicity threshold (2.0 ng/mL). Conclusions: A PBPK model was successfully developed to predict the plasma concentration–time profiles of the eight tested drugs in both healthy subjects and HF patients. Furthermore, this model may also be applied to guide digoxin dose optimization for HF patients.