<p><strong>OBJECTIVE: </strong>Furosemide renal clearance is slow after very preterm (VP) birth and increases with postnatal maturation. We compared furosemide dose frequency and total daily dose between postmenstrual age (PMA) groups in VP infants.</p>

<p><strong>STUDY DESIGN: </strong>Observational cohort study of VP infants exposed to a repeated-dose course of furosemide in Pediatrix neonatal intensive care units (NICU) from 1997 to 2016.</p>

<p><strong>RESULTS: </strong>We identified 6565 furosemide courses among 4638 infants. There were no statistically significant differences between PMA groups on the odds of receiving more frequent furosemide dosing. Furosemide courses initiated at &lt;28 weeks PMA were associated with a higher total daily dose than those initiated at a later PMA.</p>

<p><strong>CONCLUSIONS: </strong>Furosemide dosing practices in the NICU are similar across PMA groups, despite maturational changes in drug disposition. Research is needed to identify and test rational dosing strategies across the PMA spectrum for this commonly used but unproven pharmacotherapy.</p>

<p>Currently employed methods for qualifying population physiologically-based pharmacokinetic (Pop-PBPK) model predictions of continuous outcomes (e.g., concentration-time data) fail to account for within-subject correlations and the presence of residual error. In this study, we propose a new method for evaluating Pop-PBPK model predictions that account for such features. The approach focuses on deriving Pop-PBPK-specific normalized prediction distribution errors (NPDE), a metric that is commonly used for population pharmacokinetic model validation. We describe specific methodological steps for computing NPDE for Pop-PBPK models and define three measures for evaluating model performance: mean of NPDE, goodness-of-fit plots, and the magnitude of residual error. Utility of the proposed evaluation approach was demonstrated using two simulation-based study designs (positive and negative control studies) as well as pharmacokinetic data from a real-world clinical trial. For the positive-control simulation study, where observations and model simulations were generated under the same Pop-PBPK model, the NPDE-based approach denoted a congruency between model predictions and observed data (mean of NPDE =  - 0.01). In contrast, for the negative-control simulation study, where model simulations and observed data were generated under different Pop-PBPK models, the NPDE-based method asserted that model simulations and observed data were incongruent (mean of NPDE =  - 0.29). When employed to evaluate a previously developed clindamycin PBPK model against prospectively collected plasma concentration data from 29 children, the NPDE-based method qualified the model predictions as successful (mean of NPDE = 0). However, when pediatric subpopulations (e.g., infants) were evaluated, the approach revealed potential biases that should be explored.</p>

<p><strong>OBJECTIVE: </strong>Examine the effect of off-label surfactant on mortality and morbidity in more mature and larger premature infants diagnosed with respiratory distress syndrome (RDS).</p>

<p><strong>STUDY DESIGN: </strong>Cohort study of premature infants born at 30-36 weeks, birth weight &gt; 2 kg, and a diagnosis of RDS. We compared the odds of mortality and morbidity between infants who were exposed vs unexposed to surfactant. We used a treatment effects model to balance covariates between groups.</p>

<p><strong>RESULTS: </strong>Of 54,964 included infants, 25,278 (46%) were exposed to surfactant. The frequency of mortality and morbidities were higher in the exposed group in unadjusted analyses. Following adjustment with a doubly robust treatment effects model, we found no significant treatment effect of surfactant on mortality or morbidity.</p>

<p><strong>CONCLUSION: </strong>Surfactant exposure is not associated with reduced or increased mortality or morbidity in more mature premature infants with RDS.</p>