Developmental age and clinical illness drive <i>in vivo</i> variability of CYP1A2 ontogeny and caffeine metabolism in preterm neonates.

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Background: Caffeine is the standard therapy for apnea of prematurity and used near-universally in preterm infants. Interindividual variability in clearance, exposure, and clinical responses persists in neonates. CYP1A2 is the primary enzyme responsible for caffeine metabolism in adults, but the enzyme activity in neonates has historically been considered negligible.Methods: Scavenged plasma samples from neonates receiving caffeine therapy in a neonatal intensive care unit were analyzed to quantify caffeine and paraxanthine concentrations. The caffeine metabolic ratio (CMR) was used as a functional biomarker of in vivo CYP1A2 activity. Associations between CMR, postmenstrual age, and clinical covariates were evaluated using univariate analyses, linear mixed-effects modeling, and longitudinal analyses. To compare our data to model predictions, caffeine concentrations were simulated in preterm infants using two previously published physiologically based pharmacokinetic (PBPK) models: the default Simcyp preterm infant model and a 2025 modified model.Results: Thirty-one neonates (186 plasma samples) were recruited for this study. Paraxanthine was detectable in all samples, demonstrating measurable CYP1A2 activity. CMR increased with postmenstrual age even after adjusting for clinical covariates (β = 0.05, p = 0.01). Interindividual variability was observed and longitudinal analyses showed heterogeneous CMR trajectories, indicating modulation by clinical factors beyond age alone. Both PBPK models tested demonstrated systematic overprediction of caffeine exposure, consistent with underestimation of clearance, although the modified model showed better concordance with observed data.Conclusion: These findings provide the first in vivo evidence of quantifiable CYP1A2 activity in neonates and demonstrate the feasibility of using caffeine as a probe drug to study enzyme ontogeny. Current published PBPK models do not accurately capture caffeine concentrations in our cohort, likely reflecting differences between our population and the preterm models. Integrating empirically derived neonatal pharmacokinetic data into PBPK models that more accurately reflect a preterm NICU population may better inform individualized dosing based on developmental age and clinical illness severity. By anchoring neonatal drug dosing in empirically derived physiology rather than adult extrapolation, these models have the potential to transform dosing practice and advance pharmacoequity for one of the most vulnerable and historically understudied populations.