Fentanyl is an intravenously administered sedative during tracheal intubation in neonates with respiratory distress. Overdose of fentanyl leads to oversedation, as there is a direct concentration-effect relationship between the fentanyl serum concentration and respiratory depression in adults [1]. However, the relationship between serum fentanyl concentration and oxygen desaturation with oversedation in neonates still unclear. Our aim is to evaluate the association between serum fentanyl concentrations and oxygen desaturation with oversedation in neonates receiving artificial ventilation. Patients Our retrospective study included neonate patients given fentanyl for sedation during tracheal intubation. The patients were considered eligible if we could obtain the serum sample during the fentanyl therapeutic period. Measurement of serum fentanyl concentrations Blood samples were collected from the neonates as a routine care. Serum fentanyl concentrations were measured by liquid chromatography-tandem mass spectrometry. Oxygen desaturation Oxygen desaturation (ODS) was defined as percutaneous oxygen saturation less than 90%. During the fentanyl therapeutic period, All serum samples were collected during this period (the points with the highest concentrations were adopted) The occurrence of ODS (%SpO2<90%) was observed. Bayesian estimation Bayesian estimations were performed using the MwPharm++ software. The population pharmacokinetic parameters for fentanyl were established based on a previous report [2]. Volume of distribution (Vd)= 5.26 L/Kg Clearance (CL)= 3.6 L/h. There were no significant differences in patient characteristics between patients with and without ODS. The median fentanyl initial dose tended to be lower in patients with ODS compared to non-ODS patients. There was no significant difference in fentanyl concentration between patients with and without ODS. The fentanyl concentration per dose (C/D) in patients with ODS was significantly higher than in those with non-ODS. Time to incidence of ODS had a trend to be shorter than the entire fentanyl therapeutic period in the patients with non-ODS. Exposure time may not contribute to the incidence of ODS.
Purpose: Physiologically based pharmacokinetic (PBPK) analyses have been frequently used in the clinical pharmacology section of regulatory applications. However, whether models developed and validated in healthy populations can be extrapolated to untested populations is not well known. This study aimed to determine whether a drug-specific PBPK model validated in a healthy population could be used to predict drug disposition in populations with different ethnicities, ages, genetic phenotypes, and pregnant population considering an example for risperidone and its active metabolite, paliperidone. Methods: PBPK modeling and simulation were performed using Simcyp Population-based ADME Simulator version 20. The risperidone and paliperidone compound models were developed based on physicochemical and pharmacokinetic parameters reported in the literature. The model was validated using observed values from 25 clinical studies including 15 in the adult population (8 Caucasian, 5 Chinese, and 2 Japanese), 8 in the pediatric population (5 Caucasian, 2 Chinese, and 1 Japanese), and 2 in the pregnant population. Visual predictive checks (VPC) for predicted and observed plasma concentrations, goodness-of-fit plots, prediction fold error, mean error (ME), and root-mean-square error (RMSE) were used for the graphical and statistical analyses. Results: Almost all (98.9%) of observed serum risperidone and paliperidone concentrations werewithin the 90% prediction intervals of each concentration by the PBPK simulation. All predicted values of serum risperidone concentration and AUC values in adult, pediatric, and pregnant populations met the 2fold acceptance criterion. A 91.8% of predicted values of paliperidone concentration and 97.4% of AUC values fall within the 2-fold criterion in all populations. The mean error (ME) and root-mean-square error (RMSE) for all predicted Cmax for risperidone were 0.61±0.4%, and 2.85%, respectively. Regarding paliperidone, the values were -0.038±0.45% and 3.16%, respectively. Conclusion: This study successfully shows an experimental application of PBPK modeling for the adaptation of ethnic variety and pediatric population.
Background: Fentanyl is widely used for sedation in preterm neonates requiring artificial ventilation. Neonates are especially vulnerable to side effects such as respiratory depression with oversedation which has a direct concentration-effect relation. The dosage regimen is usually derived from adults employing an extrapolation based on body weight which cannot accurately determine organ maturation in neonates. There is a necessity for model-based precision dosing of fentanyl that includes maturation. This study aimed to develop a pragmatic physiologically based pharmacokinetic (PBPK) model of fentanyl and to evaluate its prediction accuracy in neonates. Methods: PBPK modeling and simulation were performed using SimCYP Population-based ADME Simulator version 20. The fentanyl compound model was developed based on physicochemical and pharmacokinetic parameters reported in the literature. The model was validated using observed values from 25 clinical studies on adults and 4 on pediatrics. Serum samples of 14 neonates were collected as routine care. Serum fentanyl concentration was measured by liquid chromatography-mass spectrometry. Results: 100% of the predicted values of serum fentanyl concentration in adult and pediatric patients met the 2-fold acceptance criterion. Mean error (ME) and root-mean-square error (RMSE) for all predicted values were 0.28±0.15%, and 1.16%, respectively. In our neonatal patients, 95.5% of the predicted values were within the 2-fold acceptance criterion with ME and RMSE of 0.05±0.075%, and 0.34%, respectively. Median predicted fentanyl AUC value in patients with severe oxygen desaturation (sODS) (percutaneous oxygen saturation <80%) was higher than non- or moderate- ODS (nmODS) patients (ODS: 213 ng/mL·h, nmODS:25.2 ng/mL·h, P=0.043), while no significant difference was observed in fentanyl clearance depending on ODS (sODS: 1.33 L/h, nmODS: 1.39 L/h, P=0.35). Conclusion: This study shows that PBPK modeling can provide a precise prediction of serum fentanyl concentration in neonates. This model may be a useful tool for dose optimization and individualization strategies to avoid oversedation.