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. 2025 Jul 13;15(7):1099.
doi: 10.3390/life15071099.

PBPK Modeling of Acetaminophen in Pediatric Populations: Incorporation of SULT Enzyme Ontogeny to Predict Age-Dependent Metabolism and Systemic Exposure

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PBPK Modeling of Acetaminophen in Pediatric Populations: Incorporation of SULT Enzyme Ontogeny to Predict Age-Dependent Metabolism and Systemic Exposure

Sonia Sharma et al. Life (Basel). .

Abstract

Sulfotransferase (SULT) enzymes contribute significantly to drug metabolism in pediatric patients. The purpose of this study was to develop a PBPK model for acetaminophen (APAP) in pediatric populations that accounts for the ontogeny of SULT isozymes that play a critical role in APAP metabolism. PBPK modeling and simulation were performed using the Simcyp® Simulator. The model incorporated the developmental ontogeny of three key hepatic SULT enzymes: SULT1A1, SULT1A3, and SULT2A1 using "best-fit" ontogeny equations for each isozyme as determined by nonlinear regression analysis of enzyme abundance versus age. PBPK model-simulated pharmacokinetic profiles for APAP captured observed clinical data for systemic exposure (Cmax, AUC) in neonates, infants, and children. SULTS accounted for ~60% APAP metabolism in neonates, with decreased contributions to infants and children. Model sensitivity analysis highlighted the potential for APAP metabolic DDIs, primarily through SULT1A1. The study demonstrates that the impact of SULT enzymes on drug metabolism is significant in neonates, which is an important clinical consideration for APAP. A PBPK model that incorporates SULT ontogeny has the potential to help inform dosing decisions in this special patient population.

Keywords: PBPK modeling; SULT; acetaminophen; neonates; ontogeny; pediatrics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Plots of enzyme abundance vs. postnatal age for SULT isozymes. Included in each plot are observed data (circles) and model-predicted SULT enzyme abundance (solid line) using the equations in Table 2.
Figure 2
Figure 2
Acetaminophen PBPK model verification in an adult Healthy Volunteer population following IV administration. The plots depicted simulated (solid line) and observed (open circles) mean plasma concentrations vs. time following IV administration at two doses (5 and 20 mg/kg infused over 2 h). The shaded area spans the 5th and 95th percentiles for concentrations.
Figure 3
Figure 3
PBPK model simulated systemic exposure profiles for acetaminophen in neonates, infants, and children following repeated administration over 48 h. The shaded area spans the 5th and 95th percentiles for concentrations. The circles represent clinically measured plasma concentrations [21] using WebPlotDigitizer [20], reflecting the 42–48 h post-infusion interval after the last administered dose.
Figure 4
Figure 4
Sensitivity analysis illustrating the impact of changes in Michaelis-Menten parameters (Km, Vmax) on APAP AUC Ratio in neonates, infants, and children. AUC Ratio is calculated as the predicted AUC relative to baseline model values. The arrows on the labels on the x-axis indicate whether the parameter value was increased (↑) or decreased (↓). The horizontal black line represents the “no changet” boundary (AUC Ratio = 1).
Figure 5
Figure 5
Pie charts depicting contributions of SULT isozymes, CYP, UGT, and renal excretion to APAP clearance in pediatric populations.

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