Age- and Bodyweight-dependent Allometric Exponent Model for Scaling Clearance and Maintenance Dose of Theophylline From Neonates to Adults

BACKGROUND: In population pharmacokinetic modeling, bodyweight is often incorporated as an important covariate using fixed (0.75) or single-exponent model. In recent years, several variations of allometric models have been suggested for the prediction of drug clearance across a wide age range. The objective of this study is to develop and evaluate single-exponent, bodyweight-dependent allometric exponent (BDE), age-dependent exponent (ADE), and segmented regression models for predicting clearance and maintenance dose of theophylline. METHODS: The BDE model was described by the following equation: (Equation is included in full-text article.), where L × BW defines the BDE for clearance. The coefficient and the exponents L and M were estimated. The ADE model consisted of several empirical exponents based on age and ranged from 0.75 (children >5 years and adults) to 1.2 (premature neonates). Data for model development and validation were based on 52 subjects each. RESULTS: All structural and statistical parameters were estimated with acceptable precision for single-exponent and BDE models (<30%); however, the BDE model was superior in describing theophylline clearance across a wide age range for the training data. The segmented regression model on log-transformed data also adequately described theophylline clearance. When models were evaluated with validation data, a single-exponent model overpredicted clearance and dosing rate in premature neonates and adults with a mean prediction error of ≥50%. For premature neonates and adults, mean clearance and dosing rate were predicted within a 30% prediction error using the BDE, ADE, and segmented models. CONCLUSIONS: This study demonstrates that the BDE, ADE, and segmented models performed better than a single-exponent model for predicting clearance and dose of theophylline across a wide age range.