A maturation model for midazolam clearance

Characterization of Pediatric Rectal Absorption, Drug Disposition, and Sedation Level for Midazolam Gel Using Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling

This study aims to explore and characterize the role of pediatric sedation via rectal route. A pediatric physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) model of midazolam gel was built and validated to support dose selection for pediatric clinical trials. Before developing the rectal PBPK model, an intravenous PBPK model was developed to determine drug disposition, specifically by describing the ontogeny model of the metabolic enzyme. Pediatric rectal absorption was developed based on the rectal PBPK model of adults. The improved Weibull function with permeability, surface area, and fluid volume parameters was used to extrapolate pediatric rectal absorption. A logistic regression model was used to characterize the relationship between the free concentrations of midazolam and the probability of sedation. All models successfully described the PK profiles with absolute average fold error (AAFE) < 2, especially our intravenous PBPK model that extended the predicted age to preterm. The simulation results of the PD model showed that when the free concentrations of midazolam ranged from 3.9 to 18.4 ng/mL, the probability of "Sedation" was greater than that of "Not-sedation" states. Combined with the rectal PBPK model, the recommended sedation doses were in the ranges of 0.44-2.08 mg/kg for children aged 2-3 years, 0.35-1.65 mg/kg for children aged 4-7 years, 0.24-1.27 mg/kg for children aged 8-12 years, and 0.20-1.10 mg/kg for adolescents aged 13-18 years. Overall, this model mechanistically quantified drug disposition and effect of midazolam gel in the pediatric population, accurately predicted the observed clinical data, and simulated the drug exposure for sedation that will inform dose selection for following pediatric clinical trials.

Model-Informed Vancomycin Dosing Optimization to Address Delayed Renal Maturation in Infants and Young Children with Critical Congenital Heart Disease

Ensuring safe and effective drug therapy in infants and young children often requires accounting for growth and organ development; however, data on organ function maturation are scarce for special populations, such as infants with congenital diseases. Children with critical congenital heart disease (CCHD) often require multiple staged surgeries depending on their age and disease severity. Vancomycin (VCM) is used to treat postoperative infections; however, the standard pediatric dose (60-80 mg/kg/day) frequently results in overexposure in children with CCHD. In this study, we characterized the maturation of VCM clearance in pediatric patients with CCHD and determined the appropriate dosing regimen using population pharmacokinetic (PK) modeling and simulations. We analyzed 1,254 VCM serum concentrations from 152 postoperative patients (3 days-13 years old) for population PK analysis. The PK model was developed using a two-compartment model with allometrically scaled body weight, estimated glomerular filtration rate (eGFR), and postmenstrual age as covariates. The observed clearance in patients aged ≤ 1 year and 1-2 years was 33% and 40% lower compared with that of non-CCHD patients, respectively, indicating delayed renal maturation in patients with CCHD. Simulation analyses suggested VCM doses of 25 mg/kg/day (age ≤ 3 months, eGFR 40 mL/min/1.73 m2 ) and 35 mg/kg/day (3 months < age ≤ 3 years, eGFR 60 mL/min/1.73 m2 ). In conclusion, this study revealed delayed renal maturation in children with CCHD, could be due to cyanosis and low cardiac output. Model-informed simulations identified the lower VCM doses for children with CCHD compared with standard pediatric guidelines.

Dabigatran pharmacokinetic-pharmacodynamic in sheep: Informing dose for anticoagulation during cardiopulmonary bypass

BACKGROUND

The effect of the anticoagulant, dabigatran, and its antagonist, idarucizumab, on coagulation remains poorly quantified. There are few pharmacokinetic-pharmacodynamic data available to determine dabigatran dose in humans or animals undergoing cardiopulmonary bypass.

METHODS

Five sheep were given intravenous dabigatran 4 mg/kg. Blood samples were collected for thromboelastometric reaction time (R-time) and drug assay at 5, 15, 30, 60, 120, 240, 480 min, and 24 h. Plasma dabigatran concentrations and R-times were analyzed using an integrated pharmacokinetic-pharmacodynamic model using non-linear mixed effects. The impact of idarucizumab 15 mg/kg administered 120 min after dabigatran 4 mg/kg and its effect on R-time was observed.

RESULTS

A 2-compartment model described dabigatran pharmacokinetics with a clearance (CL 0.0453 L/min/70 kg), intercompartment clearance (Q 0.268 L/min/70 kg), central volume of distribution (V1 2.94 L/70 kg), peripheral volume of distribution (V2 9.51 L/70 kg). The effect compartment model estimates for a sigmoid EMAX model using Reaction time had an effect site concentration (Ce50 64.2 mg/L) eliciting half of the maximal effect (EMAX 180 min). The plasma-effect compartment equilibration half time (T1/2keo) was 1.04 min. Idarucizumab 15 mg/kg reduced R-time by approximately 5 min.

CONCLUSIONS

Dabigatran reversibly binds to the active site on the thrombin molecule, preventing activation of coagulation factors. The pharmacologic target concentration strategy uses pharmacokinetic-pharmacodynamic information to inform dose. A loading dose of dabigatran 0.25 mg/kg followed by a maintenance infusion of dabigatran 0.0175 mg/kg/min for 30 min and a subsequent infusion dabigatran 0.0075 mg/kg/min achieves a steady state target concentration of 5 mg/L in a sheep model.

Machine learning in medication prescription: A systematic review

BACKGROUND

Medication prescription is a complex process that could benefit from current research and development in machine learning through decision support systems. Particularly pediatricians are forced to prescribe medications "off-label" as children are still underrepresented in clinical studies, which leads to a high risk of an incorrect dose and adverse drug effects.

METHODS

PubMed, IEEE Xplore and PROSPERO were searched for relevant studies that developed and evaluated well-performing machine learning algorithms following the PRISMA statement. Quality assessment was conducted in accordance with the IJMEDI checklist. Identified studies were reviewed in detail, including the required variables for predicting the correct dose, especially of pediatric medication prescription.

RESULTS

The search identified 656 studies, of which 64 were reviewed in detail and 36 met the inclusion criteria. According to the IJMEDI checklist, five studies were considered to be of high quality. 19 of the 36 studies dealt with the active substance warfarin. Overall, machine learning algorithms based on decision trees or regression methods performed superior regarding their predictive power than algorithms based on neural networks, support vector machines or other methods. The use of ensemble methods like bagging or boosting generally enhanced the accuracy of the dose predictions. The required input and output variables of the algorithms were considerably heterogeneous and differ strongly among the respective substance.

CONCLUSIONS

By using machine learning algorithms, the prescription process could be simplified and dosing correctness could be enhanced. Despite the heterogenous results among the different substances and cases and the lack of pediatric use cases, the identified approaches and required variables can serve as an excellent starting point for further development of algorithms predicting drug doses, particularly for children. Especially the combination of physiologically-based pharmacokinetic models with machine learning algorithms represents a great opportunity to enhance the predictive power and accuracy of the developed algorithms.

Interactions of the protease inhibitor, ritonavir, with common anesthesia drugs

The protease inhibitor, ritonavir, is a strong inhibitor of CYP 3A. The drug is used for management of the human immunovirus and is currently part of an oral antiviral drug combination (nirmatrelvir-ritonavir) for the early treatment of SARS-2 COVID-19-positive patients aged 12 years and over who have recognized comorbidities. The CYP 3A enzyme system is responsible for clearance of numerous drugs used in anesthesia (e.g., alfentanil, fentanyl, methadone, rocuronium, bupivacaine, midazolam, ketamine). Ritonavir will have an impact on drug clearances that are dependent on ritonavir concentration, anesthesia drug intrinsic hepatic clearance, metabolic pathways, concentration-response relationship, and route of administration. Drugs with a steep concentration-response relationship (ketamine, midazolam, rocuronium) are mostly affected because small changes in concentration have major changes in effect response. An increase in midazolam concentration is observed after oral administration because CYP 3A in the gastrointestinal wall is inhibited, causing a large increase in relative bioavailability. Fentanyl infusion may be associated with a modest increase in plasma concentration and effect, but the large between subject variability of pharmacokinetic and pharmacodynamic concentration changes suggests it will have little impact on an individual patient, especially when used with adverse effect monitoring. It has been proposed that drugs that have no or only a small metabolic pathway involving the CYP 3A enzyme be used during anesthesia, for example, propofol, atracurium, remifentanil, and the volatile agents. That anesthesia approach denies children of drugs with considerable value. It is better that the inhibitory changes in clearance of these drugs are understood so that rational drug choices can be made to tailor drug use to the individual patient. Altered drug dose, anticipation of duration of effect, timing of administration, use of reversal agents and perioperative monitoring would better behoove children undergoing anesthesia.

Inflammation and cardiovascular status impact midazolam pharmacokinetics in critically ill children: An observational, prospective, controlled study

Altered physiology caused by critical illness may change midazolam pharmacokinetics and thereby result in adverse reactions and outcomes in this vulnerable patient population. This study set out to determine which critical illness-related factors impact midazolam pharmacokinetics in children using population modeling. This was an observational, prospective, controlled study of children receiving IV midazolam as part of routine care. Children recruited into the study were either critically-ill receiving continuous infusions of midazolam or otherwise well, admitted for elective day-case surgery (control) who received a single IV bolus dose of midazolam. The primary outcome was to determine the population pharmacokinetics and identify covariates that influence midazolam disposition during critical illness. Thirty-five patients were recruited into the critically ill arm of the study, and 54 children into the control arm. Blood samples for assessing midazolam and 1-OH-midazolam concentrations were collected opportunistically (critically ill arm) and in pre-set time windows (control arm). Pharmacokinetic modeling demonstrated a significant change in midazolam clearance with acute inflammation (measured using C-Reactive Protein), cardio-vascular status, and weight. Simulations predict that elevated C-Reactive Protein and compromised cardiovascular function in critically ill children result in midazolam concentrations up to 10-fold higher than in healthy children. The extremely high concentrations of midazolam observed in some critically-ill children indicate that the current therapeutic dosing regimen for midazolam can lead to over-dosing. Clinicians should be aware of this risk and intensify monitoring for oversedation in such patients.

Allometric Scaling in Pharmacokinetic Studies in Anesthesiology

A clinical review is presented of basic allometric scaling theory and its application to pharmacokinetic models in anesthesia and other fields in the biologic sciences.

Intranasal Dexmedetomidine in Elderly Patients (Aged > 65 Years) During Maxillofacial Surgery: Sedative Properties and Safety Analysis

PURPOSE

Light sedation rather than intravenous sedation is preferred when patients have a low heart rate and blood pressure during maxillofacial surgery. Intranasal administration of dexmedetomidine is reported to be efficacious and safe in adults. However, dexmedetomidine could be unsuitable for routine clinical use in elderly patients because many of these patients take β-blockers, which increase the cardiovascular effects of dexmedetomidine. The objectives of the study were to evaluate the sedative properties and safety of intranasal dexmedetomidine, regardless of concurrent β-blocker treatment, in elderly patients who underwent maxillofacial surgery.

METHODS

This study was a retrospective analysis of 535 patients aged > 65 years (American Society of Anesthesiologists physical status I or II) who were undergoing maxillofacial surgery. Very anxious patients and those with hypertension received intranasal 1 µg/kg dexmedetomidine through an intranasal mucosal atomization device before anesthesia (local ropivacaine).

RESULTS

Intranasal administration of dexmedetomidine decreased the requirement for midazolam before surgery (18 of 252 vs 63 of 283, P < .0001), but increased the requirement for norepinephrine (102 of 252 vs 8 of 283, P < .0001) during or after the surgery. A combination of a β-blocker and intranasal administration of dexmedetomidine reduced the hemodynamic parameters for an extended period. Intranasal administration of dexmedetomidine resulted in bradycardia and hypotension, regardless of concurrent β-blocker treatment.

CONCLUSIONS

Intranasal 1 µg/kg dexmedetomidine was associated with a high sedation score during the operation, but also with bradycardia and hypotension.

LPS-Induced Inflammation Affects Midazolam Clearance in Juvenile Mice in an Age-Dependent Manner

Purpose

Inflammation has a significant impact on CYP3A activity. We hypothesized that this effect might be age dependent. Our objective was to conduct a population pharmacokinetic study of midazolam in mice at different developmental stages with varying degrees of inflammation to verify our hypothesis.

Methods

Different doses (2 and 5 mg/kg) of lipopolysaccharide (LPS) were used to induce different degrees of systemic inflammation in Swiss mice (postnatal age 9–42 days, n = 220). The CYP3A substrate midazolam was selected as the pharmacological probe to study CYP3A activity. Postnatal age, current body weight, serum amyloid A protein 1 (SAA1) levels and LPS doses were collected as covariates to perform a population pharmacokinetic analysis using NONMEM 7.2.

Results

A population pharmacokinetic model of midazolam in juvenile and adult mice was established. Postnatal age and current body weight were the most significant and positive covariates for clearance and volume of distribution. LPS dosage was the most significant and negative covariate for clearance. LPS dosage can significantly reduce the clearance of midazolam by 21.8% and 38.7% with 2 mg/kg and 5 mg/kg, respectively. Moreover, the magnitude of the reduction was higher in mice with advancing postnatal age.

Conclusion

Both inflammation and ontogeny have an essential role in CYP3A activity in mice. The effect of LPS-induced systemic inflammation on midazolam clearance in mice is dependent on postnatal age.

Population pharmacokinetics of unbound valproic acid in pediatric epilepsy patients in China: a protein binding model

PURPOSE

The purpose of this study was to establish a protein binding model of unbound valproic acid (VPA) based on Chinese pediatric patients with epilepsy and provide a reference for clinical medication.

METHODS

A total of 313 patients were included and both their total and unbound VPA concentrations (375 pairs of concentrations) were measured. NONMEM software was used for population pharmacokinetic modeling. The stepwise method was used to screen the potential covariates. Goodness-of-fit plot, bootstrap, and visual predictive check were used for model evaluation. In addition, dose recommendations for typical patients aged 0 to 16 years were proposed by Monte Carlo simulations.

RESULTS

A one-compartment model of first-order absorption and first-order elimination was used to describe the pharmacokinetic characteristics of unbound VPA, and the linear non-saturable binding equation was introduced to describe the protein binding. Body weight, age-based maturation, and co-medicated with lamotrigine could affect the CL/F of unbound and bound VPA. Model evaluation showed satisfactory robustness of the final model. The dosing regimens for children aged 0 to 16 years were proposed based on the final established model.

CONCLUSION

We developed a population pharmacokinetic model of unbound and bound VPA that took account of protein binding. The VPA dosing regimen in pediatric patients with epilepsy needs to be optimized by the body weight, age, and co-medications.

Precision Dosing Management with Intelligent Computing in Digital Health

Pediatric dosing is not only critical for successful pediatric trials in drug development but also paramount to safety and effective treatment at bedside. Due to the complex pharmacokinetic of children compared to adults, several challenges are posed in managing dosing precisely during drug development and after drug approval to clinicians. In particular, given the real-world practice, understanding the impact of development on the dose-exposure-response relationship is essential in optimizing the dosing to children of different ages. In this paper we propose a novel intelligent computing framework to examine how the growth and maturation create size- and age-dependent variability in pharmacokinetics and pharmacodynamics, and summarize the use of modeling-based approaches for dose finding in pediatric drug development, allowing clinicians to anticipate probable treatment effects and to have a higher likelihood of achieving optimal dose regimens early, as well as reducing the drug development cycling time and cost.

First dose in neonates: pharmacokinetic bridging study from juvenile mice to neonates for drugs metabolized by CYP3A

First dose prediction is challenging in neonates. Our objective in this proof-of-concept study was to perform a pharmacokinetic (PK) bridging study from juvenile mice to neonates for drugs metabolized by CYP3A. We selected midazolam and clindamycin as model drugs. We developed juvenile mice population PK models using NONMEM. The PK parameters of these two drugs in juvenile mice were used to bridge PK parameters in neonates using different correction methods. The bridging results were evaluated by the fold-error of 0.5- to 1.5-fold. Simple allometry with and without a correction factor for maximum lifespan potential could be used for a bridging of clearance (CL) and volume of distribution (V_d), respectively, from juvenile mice to neonates. Simulation results demonstrated that for midazolam, 100% of clinical studies for which both the predictive CL and V_d were within 0.5- to 1.5-fold of the observed. For clindamycin, 75% and 100% of clinical studies for which the predictive CL and V_d were within 0.5- to 1.5-fold of the observed. A PK bridging of drugs metabolized by CYP3A is feasible from juvenile mice to neonates. It could be a complement to the ADE and PBPK models to support the first dose in neonates.

A Novel Study Design Using Continuous Intravenous and Intraduodenal Infusions of Midazolam and Voriconazole for Mechanistic Quantitative Assessment of Hepatic and Intestinal CYP3A Inhibition

The extent of a drug-drug interaction (DDI) mediated by cytochrome P450 (CYP) 3A inhibitors is highly variable during a dosing interval, as it depends on the temporal course of victim and perpetrator drug concentrations at intestinal and hepatic CYP3A expression sites. Capturing the time course of inhibition is therefore difficult using standard DDI studies assessing changes in area under the curve; thus, a novel design was developed. In a 4-period changeover pilot study, 6 healthy men received intraduodenal or intravenous infusions of the CYP3A substrate midazolam (MDZ) at a rate of 0.26 mg/h for 24 hours. This was combined with intraduodenal or intravenous infusion of the CYP3A inhibitor voriconazole (VRZ), administered at rates of 7.5 mg/h from 8 to 16 hours and of 15 mg/h from 16 to 24 hours, after starting midazolam administration. Plasma and urine concentrations of VRZ, MDZ, and its major metabolites were quantified by liquid chromatography-tandem mass spectrometry and analyzed by semiphysiological population pharmacokinetic nonlinear mixed-effects modeling. A model including mechanism-based inactivation of the metabolizing enzymes (maximum inactivation rate constant k_inact , 2.83 h^-1 ; dissociation rate constant K I , 9.33 μM) described the pharmacokinetics of VRZ well. By introducing competitive inhibition by VRZ on primary and secondary MDZ metabolism, concentration-time profiles, MDZ and its metabolites were captured appropriately. The model provides estimates of local concentrations of substrate and inhibitor at the major CYP3A expression sites and thus of the respective dynamic extent of inhibition. A combination of intravenous and intraduodenal infusions of inhibitors and substrates has the potential to provide a more accurate assessment of DDIs occurring in both gut wall and liver.

Midazolam Dose Optimization in Critically Ill Pediatric Patients With Acute Respiratory Failure: A Population Pharmacokinetic-Pharmacogenomic Study

OBJECTIVES

To develop a pharmacokinetic-pharmacogenomic population model of midazolam in critically ill children with primary respiratory failure.

DESIGN

Prospective pharmacokinetic-pharmacogenomic observational study.

SETTING

Thirteen PICUs across the United States.

PATIENTS

Pediatric subjects mechanically ventilated for acute respiratory failure, weight greater than or equal to 7 kg, receiving morphine and/or midazolam continuous infusions.

INTERVENTIONS

Serial blood sampling for drug quantification and a single blood collection for genomic evaluation.

MEASUREMENTS AND MAIN RESULTS

Concentrations of midazolam, the 1' (1`-hydroxymidazolam metabolite) and 4' (4`-hydroxymidazolam metabolite) hydroxyl, and the 1' and 4' glucuronide metabolites were measured. Subjects were genotyped using the Illumina HumanOmniExpress genome-wide single nucleotide polymorphism chip. Nonlinear mixed effects modeling was performed to develop the pharmacokinetic-pharmacogenomic model. Body weight, age, hepatic and renal functions, and the UGT2B7 rs62298861 polymorphism are relevant predictors of midazolam pharmacokinetic variables. The estimated midazolam clearance was 0.61 L/min/70kg. Time to reach 50% complete mature midazolam and 1`-hydroxymidazolam metabolite/4`-hydroxymidazolam metabolite clearances was 1.0 and 0.97 years postmenstrual age. The final model suggested a decrease in midazolam clearance with increase in alanine transaminase and a lower clearance of the glucuronide metabolites with a renal dysfunction. In the pharmacogenomic analysis, rs62298861 and rs28365062 in the UGT2B7 gene were in high linkage disequilibrium. Minor alleles were associated with a higher 1`-hydroxymidazolam metabolite clearance in Caucasians. In the pharmacokinetic-pharmacogenomic model, clearance was expected to increase by 10% in heterozygous and 20% in homozygous for the minor allele with respect to homozygous for the major allele.

CONCLUSIONS

This work leveraged available knowledge on nonheritable and heritable factors affecting midazolam pharmacokinetic in pediatric subjects with primary respiratory failure requiring mechanical ventilation, providing the basis for a future implementation of an individual-based approach to sedation.

Maturation of midazolam clearance in critically ill children with severe bronchiolitis: A population pharmacokinetic analysis

PURPOSE

The aim of the present study was to develop a population pharmacokinetic model of midazolam, and to evaluate the influence of maturation process and other variability factors in critically ill children with severe acute bronchiolitis, who received a long-term intravenous infusion of midazolam.

METHODS

In the study were included 49 critically ill children of both genders (from 0 to 130 weeks of age) with severe acute bronchiolitis hospitalised in intensive care units. Nonlinear mixed effects modelling approach was applied for data analyses and simulations.

RESULTS

The final model is a two-compartment model that includes the effects of body weight using allometric scaling with fixed exponents and maturation of clearance. For a typical subject, scaled to the adult body weight of 70 kg, population pharmacokinetic values were estimated at 8.52 L/h for clearance (when maturation function was 1), 25.5 L/h for intercompartmental clearance, and 5.71 L and 39.8 L for the volume of the central and peripheral compartment, respectively. Based on the final model, maturation reaches 50% of the adult clearance in 45.9 weeks of postmenstrual age. The influence of gender, ABCB1 genotype and biochemical parameters on midazolam clearance was not detected. Results of simulations indicate the need for reduced dosing in certain groups of patients in order to maintain plasma concentrations of midazolam within recommended values.

CONCLUSIONS

The developed population pharmacokinetic model can contribute to the dosing optimisation of midazolam, especially in critically ill children as it includes the influence of size and maturation of clearance, which are important parameters for achieving the desired plasma concentrations of midazolam.

Evaluation of the effects of ontogenetic or maturation functions and chronic heart failure on the model analysis for the dose-response relationship of warfarin in Japanese children

PURPOSE

We previously demonstrated that the rational pediatric dosage of warfarin can be well-described by a SIZE parameter that includes an allometry exponent of weight. On the other hand, allometry alone is considered to be insufficient to predict drug clearance in neonates and infants. The primary purpose of the present study was to evaluate the effects of incorporation of the maturation process into the analysis model for the dose-response relationship of warfarin in Japanese children. In addition, we evaluated the effect of chronic heart failure (CHF) on the response to warfarin as an independent risk factor for increased anticoagulant effects.

METHODS

Thirty-eight patients with stable anticoagulation by warfarin were enrolled. During a mean follow-up period of 4.74 ± 3.51 years, 1092 data points including prothrombin time-international normalized ratio (PT-INR) were obtained. The data were subjected to multiple regression analysis to identify covariates related to the anticoagulant effects.

RESULTS

Two different models describing the maturation process did not improve the predictive performance for the dose-response relationship in pediatric patients. In addition to the SIZE-normalized daily dose, the vitamin K epoxide reductase complex 1 (VKORC1) genotype, and concomitant use of bosentan, CHF was identified as a covariate increasing the anticoagulant effects of warfarin to 118%.

CONCLUSION

The SIZE parameter was useful even without incorporation of maturation models to describe the response to warfarin in pediatric patients, and our longitudinal follow-up study design with multiple observations was beneficial to detect changes within individual subjects.

Extrapolation of praziquantel pharmacokinetics to a pediatric population: a cautionary tale

L-praziquantel (PZQ) pharmacokinetic data were analyzed from two relative bioavailability Phase 1 studies in adult, healthy subjects with two new oral dispersion tablet (ODT) formulations of L-PZQ administered under various combinations of co-administration with food, water, and/or crushing. Linear mixed effects models adequately characterized the noncompartmental estimates of the pharmacokinetic profiles in both studies. Dose, food, and formulation were found to significantly affect L-PZQ exposure in both studies. The model for AUC was then extrapolated to children 2–5 years old accounting for enzyme maturation and weight. The predicted exposures were compared to an external Phase 1 study conducted by the Swiss Tropical and Public Health Institute using a currently marketed formulation (Cesol 600 mg immediate-release tablets) and found to be substantially lower than observed. A root cause analysis was completed to identify the reason for failure of the models. Various scenarios were proposed and tested. Two possible reasons for the failure were identified. One reason was that the model did not account for the reduced hepatic clearance seen in patients compared to the healthy volunteer population used to build the model. The second possible reason was that PZQ absorption appears sensitive to meal composition and the model did not account for differences in meals between a standardized Phase 1 unit and clinical sites in Africa. Further studies are needed to confirm our hypotheses.

Multistep Unified Models Using Prior Knowledge for the Prediction of Drug Clearance in Neonates and Infants

Allometric approaches are widely used for interspecies scaling for the prediction of pharmacokinetic (PK) parameters during drug development. The concept of allometry can also be extended to predict PK parameters from adults to children. Three methods for extrapolating pediatric clearance were developed and evaluated using the clearance values of 4 drugs. The first method was established using a simple allometric (SA) model with estimated coefficient and exponent based on data ranging from children older than 2 years to adult. Then we developed a unified multistep single-exponent (MSE) and multistep body-weight-dependent exponent (MBDE) models. The major steps in these 2 new methods include generating pseudopredicted clearance for unobserved new populations such as preterm neonates, term neonates, and infants. Subsequent steps involve incorporating the pseudopredicted clearance with the actual PK data from older children and adults. All 3 models were then used to predict drug clearance in children ≤2 years old (N = 278). Drug clearance was predicted with mean absolute error of 29.6, 14.2, and 12.9 using SA, MSE, MBDE, respectively. The root mean square error was 65.9, 29.8, 24.7 for SA, MSE, MBDE, respectively. Approximately 41%, 72%, and 74% of the children's clearance data were within 0.5 to 1.5-fold of the observed values when drug clearance was extrapolated using SA, MSE, and MBDE models, respectively. The present multistep unified extrapolation approaches improved the prediction of clearance from preterm neonates to 2 years of age and may have practical use for first-in-pediatric dose selection.

Predicting CYP3A-mediated midazolam metabolism in critically ill neonates, infants, children and adults with inflammation and organ failure

AIMS

Inflammation and organ failure have been reported to have an impact on cytochrome P450 (CYP) 3A-mediated clearance of midazolam in critically ill children. Our aim was to evaluate a previously developed population pharmacokinetic model both in critically ill children and other populations, in order to allow the model to be used to guide dosing in clinical practice.

METHODS

The model was evaluated externally in 136 individuals, including (pre)term neonates, infants, children and adults (body weight 0.77-90 kg, C-reactive protein level 0.1-341 mg l^-1 and 0-4 failing organs) using graphical and numerical diagnostics.

RESULTS

The pharmacokinetic model predicted midazolam clearance and plasma concentrations without bias in postoperative or critically ill paediatric patients and term neonates [median prediction error (MPE) <30%]. Using the model for extrapolation resulted in well-predicted clearance values in critically ill and healthy adults (MPE <30%), while clearance in preterm neonates was over predicted (MPE >180%).

CONCLUSION

The recently published pharmacokinetic model for midazolam, quantifying the influence of maturation, inflammation and organ failure in children, yields unbiased clearance predictions and can therefore be used for dosing instructions in term neonates, children and adults with varying levels of critical illness, including healthy adults, but not for extrapolation to preterm neonates.

Prediction of Apparent Oral Clearance of Small-Molecule Inhibitors in Pediatric Patients

The purpose of this study was to build regression models for the prediction of apparent oral clearance (CL/F) for small-molecule inhibitors in the pediatric population using data obtained from adults. Two approaches were taken; a simple allometric regression model which considers no interdrug or interindividual variability and an allometric regression model with mixed-effects modeling where some variability parameters are included in the model. Average CL/F values were obtained for 15 drugs at various dosages from 31 literatures (a total of 139 data sets) conducted in adults and for 15 drugs from 26 literatures (62 data sets) conducted in children. Data were randomly separated into the "modeling" or "validation" data set, and the 2 allometric regression models were applied to the modeling data set. The predictive ability of the models was examined by comparing the observed and model-predicted CL/F in children using the validation data set. The percentage root mean square error was 17.2% and 26.3% in the simple allometric regression model and the allometric regression model with mixed-effects modeling, respectively. The predictive ability of the 2 models seems acceptable, suggesting that they could be useful for predicting the CL/F of new small-molecule inhibitors and for determining adequate doses in clinical pharmacotherapy for children.

Sufentanil and Midazolam Dosing and Pharmacogenetic Factors in Pediatric Analgosedation and Withdrawal Syndrome

Our aim was to describe the effect of dosing and genetic factors on sufentanil- and midazolam-induced analgosedation and withdrawal syndrome (WS) in pediatric population. Analgosedation and withdrawal syndrome development were monitored using COMFORT-neo/-B scores and SOS score. Length of therapy, dosing of sufentanil and midazolam were recorded. Genotypes of selected candidate polymorphisms in CYP3A5, COMT, ABCB1, OPRM1 and PXR were analysed. In the group of 30 neonates and 18 children, longer treatment duration with midazolam of 141 h (2 – 625) vs. 88 h (7 – 232) and sufentanil of 326.5 h (136 – 885) vs. 92 h (22 – 211) (median; range) was found in the patients suffering from WS vs. non-WS group, respectively. Median midazolam cumulative doses were in the respective values of 18.22 mg/kg (6.93 – 51.25) vs. 9.94 mg/kg (2.12 – 49.83); P=0.03, and the respective values for sufentanil were 88.60 µg/kg (20.21 – 918.52) vs. 21.71 µg/kg (4.5 – 162.29); P<0.01. Cut off value of 177 hours for sufentanil treatment duration represented predictive factor for WS development with 81 % sensitivity and 94 % specificity. SNPs in the candidate genes COMT, PXR and ABCB1 affected the dosing of analgosedative drugs, but were not associated with depth of analgosedation or WS. Cumulative dose and length of analgosedative therapy with sufentanil significantly increases the risk of WS in critically ill neonates and children.

Understanding and applying pharmacometric modelling and simulation in clinical practice and research

Understanding the dose–concentration–effect relationship is a fundamental component of clinical pharmacology. Interpreting data arising from observations of this relationship requires the use of mathematical models; i.e. pharmacokinetic (PK) models to describe the relationship between dose and concentration and pharmacodynamic (PD) models describing the relationship between concentration and effect. Drug development requires several iterations of pharmacometric model‐informed learning and confirming. This includes modelling to understand the dose–response in preclinical studies, deriving a safe dose for first‐in‐man, and the overall analysis of Phase I/II data to optimise the dose for safety and efficacy in Phase III pivotal trials. However, drug development is not the boundary at which PKPD understanding and application stops. PKPD concepts will be useful to anyone involved in the prescribing and administration of medicines for purposes such as determining off‐label dosing in special populations, individualising dosing based on a measured biomarker (personalised medicine) and in determining whether lack of efficacy or unexpected toxicity maybe solved by adjusting the dose rather than the drug. In clinical investigator‐led study design, PKPD can be used to ensure the optimal dose is used, and crucially to define the expected effect size, thereby ensuring power calculations are based on sound prior information. In the clinical setting the most likely people to hold sufficient expertise to advise on PKPD matters will be the pharmacists and clinical pharmacologists. This paper reviews fundamental PKPD principles and provides some real‐world examples of PKPD use in clinical practice and applied clinical research.

Characterizing the Developmental Trajectory of Sirolimus Clearance in Neonates and Infants

Sirolimus is increasingly being used in neonates and infants, but the mechanistic basis of age‐dependent changes in sirolimus disposition has not been fully addressed yet. In order to characterize the age‐dependent changes, serial sirolimus clearance (CL) estimates in individual young pediatric patients were collected and analyzed by population modeling analysis. In addition, sirolimus metabolite formation was also investigated to further substantiate the corresponding age‐dependent change in CYP3A activity. The increasing pattern over time of allometrically size‐normalized sirolimus CL estimates vs. age was well described by a sigmoidal E_max model. This age‐dependent increase was also observed within each individual patient over a 4‐year study period. CYP3A‐dependent sirolimus metabolite formation changed in a similar fashion. This study clearly demonstrates the rapid increase of sirolimus CL over time in neonates and infants, indicating the developmental change. This developmental pattern can be explained by a parallel increase in CYP3A metabolic activity.

Prediction of Human Glomerular Filtration Rate from Preterm Neonates to Adults: Evaluation of Predictive Performance of Several Empirical Models

The objective of this study was to evaluate the predictive performance of several allometric empirical models (body weight dependent, age dependent, fixed exponent 0.75, a data-dependent single exponent, and maturation models) to predict glomerular filtration rate (GFR) in preterm and term neonates, infants, children, and adults without any renal disease. In this analysis, the models were developed from GFR data obtained from inulin clearance (preterm neonates to adults; n = 93) and the predictive performance of these models were evaluated in 335 subjects (preterm neonates to adults). The primary end point was the prediction of GFR from the empirical allometric models and the comparison of the predicted GFR with measured GFR. A prediction error within ±30% was considered acceptable. Overall, the predictive performance of the four models (BDE, ADE, and two maturation models) for the prediction of mean GFR was good across all age groups but the prediction of GFR in individual healthy subjects especially in neonates and infants was erratic and may be clinically unacceptable.

Pharmacokinetic-pharmacodynamic modelling in anaesthesia

Anaesthesiologists adjust drug dosing, administration system and kind of drug to the characteristics of the patient. They then observe the expected response and adjust dosing to the specific requirements according to the difference between observed response, expected response and the context of the surgery and the patient. The approach above can be achieved because on one hand quantification technology has made significant advances allowing the anaesthesiologist to measure almost any effect by using noninvasive, continuous measuring systems. On the other the knowledge on the relations between dosing, concentration, biophase dynamics and effect as well as detection of variability sources has been achieved as being the benchmark specialty for pharmacokinetic-pharmacodynamic (PKPD) modelling. The aim of the review is to revisit the most common PKPD models applied in the field of anaesthesia (i.e. effect compartmental, turnover, drug-receptor binding and drug interaction models) through representative examples. The effect compartmental model has been widely used in this field and there are multiple applications and examples. The use of turnover models has been limited mainly to describe respiratory effects. Similarly, cases in which the dissociation process of the drug-receptor complex is slow compared with other processes relevant to the time course of the anaesthetic effect are not frequent in anaesthesia, where in addition to a rapid onset, a fast offset of the response is required. With respect to the characterization of PD drug interactions different response surface models are discussed. Relevant applications that have changed the way modern anaesthesia is practiced are also provided.

Pharmacokinetics of sufentanil during long-term infusion in critically ill pediatric patients

The aim of this study was to develop a population pharmacokinetic model of sufentanil and to assess the influence of covariates in critically ill children admitted to a pediatric intensive care unit. After institutional approval, 41 children were enrolled in the study. Blood samples for pharmacokinetic (PK) assessment were collected from routinely placed arterial catheters during and after discontinuation of infusion. Population nonlinear mixed-effects modeling was performed using NONMEM. A 2-compartment model described sufentanil PK sufficiently. Typical values of the central and peripheral volume of distribution and the metabolic and intercompartmental clearance for a theoretical patient weighing 70 kg were VC = 7.90 l, VT  = 481 L, Cl =  5.3 L/h, and Q = 38.3 L/h, respectively. High interindividual variability of all PK parameters was noted. Allometric/isometric principles to scale sufentanil PK revealed that to achieve the same steady-state sufentanil concentrations in plasma for pediatric patients of different body weights, the infusion rate should follow the formula (infusion rate for a 70-kg adult patient, μg/h) × (body weight/70 kg)(0.75). Severity of illness described by PRISM score, the monitored physiological and laboratory parameters, and coadministered drugs such as vasopressors were not found to be significant covariates.

The interplay between drugs and the kidney in premature neonates

The kidney plays a central role in the clearance of drugs. However, renal drug handling entails more than glomerular filtration and includes tubular excretion and reabsorption, and intracellular metabolization by cellular enzyme systems, such as the Cytochrome P450 isoenzymes. All these processes show maturation from birth onwards, which is one of the reasons why drug dosing in children is not simply similar to dosing in small adults. As kidney development normally finishes around the 36th week of gestation, being born prematurely will result in even more immature renal drug handling. Environmental effects, such as extra-uterine growth restriction, sepsis, asphyxia, or drug treatments like caffeine, aminoglycosides, or non-steroidal anti-inflammatory drugs, may further hamper drug handling in the kidney. Dosing in preterm neonates is therefore dependent on many factors that need to be taken into account. Drug treatment may significantly hamper postnatal kidney development in preterm neonates, just like renal immaturity has an impact on drug handling. The restricted kidney development results in a lower number of nephrons that may have several long-term sequelae, such as hypertension, albuminuria, and renal failure. This review focuses on the interplay between drugs and the kidney in premature neonates.

Prediction of drug clearance in children: an evaluation of the predictive performance of several models

The objective of this study is to evaluate the predictive performance of several models to predict drug clearance in children ≤5 years of age. Six models (allometric model (data-dependent exponent), fixed exponent of 0.75 model, maturation model, body weight-dependent model, segmented allometric model, and age-dependent exponent model) were evaluated in this study. From the literature, the clearance values for six drugs from neonates to adults were obtained. External data were used to evaluate the predictive performance of these models in children ≤5 years of age. With the exception of a fixed exponent of 0.75, the mean predicted clearance in most of the age groups was within ≤50% prediction error. Individual clearance prediction was erratic by all models and cannot be used reliably to predict individual clearance. Maturation, body weight-dependent, and segmented allometric models to predict clearances of drugs in children ≤5 years of age are of limited practical value during drug development due to the lack of availability of data. Age-dependent exponent model can be used for the selection of first-in-children dose during drug development.

Changes in individual drug-independent system parameters during virtual paediatric pharmacokinetic trials: introducing time-varying physiology into a paediatric PBPK model

Although both POPPK and physiologically based pharmacokinetic (PBPK) models can account for age and other covariates within a paediatric population, they generally do not account for real-time growth and maturation of the individuals through the time course of drug exposure; this may be significant in prolonged neonatal studies. The major objective of this study was to introduce age progression into a paediatric PBPK model, to allow for continuous updating of anatomical, physiological and biological processes in each individual subject over time. The Simcyp paediatric PBPK model simulator system parameters were reanalysed to assess the impact of re-defining the individual over the study period. A schedule for re-defining parameters within the Simcyp paediatric simulator, for each subject, over a prolonged study period, was devised to allow seamless prediction of pharmacokinetics (PK). The model was applied to predict concentration-time data from multiday studies on sildenafil and phenytoin performed in neonates. Among PBPK system parameters, CYP3A4 abundance was one of the fastest changing covariates and a 1-h re-sampling schedule was needed for babies below age 3.5 days in order to seamlessly predict PK (<5% change in abundance) with subject maturation. The re-sampling frequency decreased as age increased, reaching biweekly by 6 months of age. The PK of both sildenafil and phenytoin were predicted better at the end of a prolonged study period using the time varying vs fixed PBPK models. Paediatric PBPK models which account for time-varying system parameters during prolonged studies may provide more mechanistic PK predictions in neonates and infants.

Use of benzodiazepines as anxiolytics in neonates: are we there yet?

Few controlled trials exist to demonstrate the efficacy and the risks of pharmacologic agents used in treating pediatric, and more specifically neonatal patients. It is not different for the central nervous system altering class of drugs, benzodiazepines (BZDs). Little information is known about the long-term effects of BZDs use in neonates as anxiolytics and sedatives causing trepidation with their use in the clinical setting. Insufficient data related to the use of BZDs result in a lack of clear recommendations to guide caregivers at the bedside on the safest administration patterns to avoid long-term adverse effects. However, caring for ill neonates, in particular surgical patients and infants requiring prolonged hospitalizations, necessitates the use of these agents. A literature search within the electronic database, PubMed, of English language, full-text articles published between 2007 and 2012 was undertaken to determine the state of the science regarding the use of BZDs in neonates. These medications cause unwanted effects in neonates with immature hepatic function (primary site of metabolism) and during a developmental period of tremendous neuroplasticity. It benefits caregivers to recognize the need for improved monitoring of stress experienced by infants in the NICU and understand the impact of prolonged agitation and subacute pain on infant development.

Clinical pharmacology of midazolam in neonates and children: effect of disease-a review

Midazolam is a benzodiazepine with rapid onset of action and short duration of effect. In healthy neonates the half-life (t_1/2) and the clearance (Cl) are 3.3-fold longer and 3.7-fold smaller, respectively, than in adults. The volume of distribution (Vd) is 1.1 L/kg both in neonates and adults. Midazolam is hydroxylated by CYP3A4 and CYP3A5; the activities of these enzymes surge in the liver in the first weeks of life and thus the metabolic rate of midazolam is lower in neonates than in adults. Midazolam acts as a sedative, as an antiepileptic, for those infants who are refractory to standard antiepileptic therapy, and as an anaesthetic. Information of midazolam as an anaesthetic in infants are very little. Midazolam is usually administered intravenously; when minimal sedation is required, intranasal administration of midazolam is employed. Disease affects the pharmacokinetics of midazolam in neonates; multiple organ failure reduces the Cl of midazolam and mechanical ventilation prolongs the t_1/2 of this drug. ECMO therapy increases t_1/2, Cl, and Vd of midazolam several times. The adverse effects of midazolam in neonates are scarce: pain, tenderness, and thrombophlebitis may occur. Respiratory depression and hypotension appear in a limited percentage of infants following intravenous infusion of midazolam. In conclusion, midazolam is a safe and effective drug which is employed as a sedative, as antiepileptic agent, for infants who are refractory to standard antiepileptic therapy, and as an anaesthetic.

A novel maturation function for clearance of the cytochrome P450 3A substrate midazolam from preterm neonates to adults

BACKGROUND AND OBJECTIVE

Major changes in cytochrome P450 (CYP) 3A activity may be expected in the first few months of life with, later, relatively limited changes. In this analysis we studied the maturation of in vivo CYP3A-mediated clearance of midazolam, as model drug, from preterm neonates of 26 weeks gestational age (GA) to adults.

METHODS

Pharmacokinetic data after intravenous administration of midazolam were obtained from six previously reported studies. Subjects were premature neonates (n = 24; GA 26-33.5 weeks, postnatal age (PNA) 3-11 days, and n = 24; GA 26-37 weeks, PNA 0-1 days), 23 children after elective major craniofacial surgery (age 3-23 months), 18 pediatric intensive-care patients (age 2 days-17 years), 18 pediatric oncology patients (age 3-16 years), and 20 healthy male adults (age 20-31 years). Population pharmacokinetic modeling with systematic covariate analysis was performed by use of NONMEM v6.2.

RESULTS

Across the entire lifespan from premature neonates to adults, bodyweight was a significant covariate for midazolam clearance. The effect of bodyweight was best described by use of an allometric equation with an exponent changing with bodyweight in an exponential manner from 0.84 for preterm neonates (0.77 kg) to 0.44 for adults (89 kg), showing that the most rapid maturation occurs during the youngest age range.

CONCLUSIONS

An in-vivo maturation function for midazolam clearance from premature neonates to adults has been developed. This function can be used to derive evidence-based doses for children, and to simulate exposure to midazolam and possibly other CYP3A substrates across the pediatric age range in population pharmacokinetic models or physiologically based pharmacokinetic models.

Neonatal clinical pharmacology

Effective and safe drug administration in neonates should be based on integrated knowledge on the evolving physiological characteristics of the infant who will receive the drug and the pharmacokinetics (PK) and pharmacodynamics (PD) of a given drug. Consequently, clinical pharmacology in neonates is as dynamic and diverse as the neonates we admit to our units while covariates explaining the variability are at least as relevant as median estimates. The unique setting of neonatal clinical pharmacology will be highlighted based on the hazards of simple extrapolation of maturational drug clearance when only based on 'adult' metabolism (propofol, paracetamol). Second, maturational trends are not at the same pace for all maturational processes. This will be illustrated based on the differences between hepatic and renal maturation (tramadol, morphine, midazolam). Finally, pharmacogenetics should be tailored to neonates, not just mirror adult concepts. Because of this diversity, clinical research in the field of neonatal clinical pharmacology is urgently needed and facilitated through PK/PD modeling. In addition, irrespective of already available data to guide pharmacotherapy, pharmacovigilance is needed to recognize specific side effects. Consequently, pediatric anesthesiologists should consider to contribute to improved pharmacotherapy through clinical trial design and collaboration, as well as reporting on adverse effects of specific drugs.

Assessing circadian rhythms during prolonged midazolam infusion in the pediatric intensive care unit (PICU) children

BACKGROUND

This study evaluates possible circadian rhythms during prolonged midazolam infusion in 27 pediatric intensive care unit (PICU) children under mechanical ventilation.

METHODS

Blood samples for midazolam and 1-OH-midazolam assay were collected throughout the infusion at different times of the day. The blood pressure, heart rate and body temperature were recorded every hour for the rhythms analysis. Population nonlinear mixed-effect modeling with NONMEM was used for data analysis.

RESULTS

A two-compartment model for midazolam pharmacokinetics and a one-compartment model for midazolam metabolite adequately described the data. The 24 h profiles of all monitored physiological parameters were greatly disturbed/abolished in comparison with the well-known 24 h rhythmic patterns in healthy subjects. There was no significant circadian rhythm detected with respect to midazolam pharmacokinetics, its active metabolite pharmacokinetics and all monitored parameters.

CONCLUSIONS

We concluded that the light-dark cycle did not influence midazolam pharmacokinetics in intensive care units children. Also, endogenous rhythms in critically ill and sedated children are severely disturbed and desynchronized. Our results confirmed that it is necessary to adjust the dose of midazolam to the patient's body weight. The low value of midazolam clearances observed in our study was probably caused by mechanical ventilation, which was shown to decrease the cardiac output.

A pharmacokinetic standard for babies and adults

The pharmacokinetic behavior of medicines used in humans follows largely predictable patterns across the human age range from premature babies to elderly adults. Most of the differences associated with age are in fact due to differences in size. Additional considerations are required to describe the processes of maturation of clearance processes and postnatal changes in body composition. Application of standard approaches to reporting pharmacokinetic parameters is essential for comparative human pharmacokinetic studies from babies to adults. A standardized comparison of pharmacokinetic parameters obtained in children and adults is shown for 46 drugs. Appropriate size scaling shows that children (over 2 years old) are similar to adults. Maturation changes are generally completed within the first 2 years of postnatal life; consequently babies may be considered as immature children, whereas children are just small adults.

Critical illness is a major determinant of midazolam clearance in children aged 1 month to 17 years

BACKGROUND

In children, a large variability in pharmacokinetics of midazolam, a cytochrome P450 3A4/5 (CYP3A4/5) enzyme substrate, has been described, which cannot be explained by age-related changes alone. In this study, these age-related changes are studied in relation to other covariates to explain the variability in the pharmacokinetics of midazolam in children.

METHODS

Population pharmacokinetic modeling was performed using a joint dataset of 3 studies conducted previously: study 1: pediatric intensive care patients requiring sedation in the intensive care unit; study 2: pediatric oncology patients undergoing an invasive procedure; study 3: otherwise healthy infants admitted for postoperative monitoring after elective major craniofacial surgery. Midazolam, 1-hydroxymidazolam, and 1-hydroxymidazolam glucuronide concentrations were considered to determine the pharmacokinetics of midazolam and metabolites using NONMEM 6.2. SimCYP pediatric simulator was used for simulation.

RESULTS

Fifty-four children aged between 1 month and 17 years who received intravenous midazolam (bolus and/or continuous infusion) for sedation were included in this study. A reduction of 93% for CYP3A4/5 (midazolam to 1-hydroxymidazolam) and 86% for uridine diphosphate glucuronosyltransferase (1-hydroxymidazolam to 1-hydroxymidazolam glucuronide) mediated clearance was found in pediatric intensive care patients compared with the other 2 patient groups. We did not find a significant influence of age or bodyweight on CYP3A4/5-mediated total clearance. For uridine diphosphate glucuronosyltransferase-mediated clearance, bodyweight explained 41.5% of the variability.

CONCLUSIONS

From infancy to adolescence, critical illness seems to be a major determinant of midazolam clearance, which may result from reduced CYP3A4/5 activity due to inflammation. This may have important implications for dosing of midazolam and other CYP3A drug substrates in critically ill children.

Neonatal pharmacology: extensive interindividual variability despite limited size

Providing safe and effective drug therapy to neonates requires knowledge of the impact of development on the pharmacokinetics and pharmacodynamics of drugs. Although maturational changes are observed throughout childhood, they are most prominent during the first year of life. Several of these processes overlap, making development an extremely dynamic system in the newborn compared with that in infants, children, or adults. Changes in body composition and porportions, liver mass, metabolic activity, and renal function collectively affect the pharmacokinetic behavior of medications. Instead of simply adapting doses by scaling adult or pediatric doses on the basis of a patient's weight and/or body surface area, integrated knowledge of clinical maturation and developmental pharmacology is critical to the safe and effective use of medications in neonates. Unfortunately, the effects of human ontogeny on both pharmacokinetics and pharmacodynamics have not been well established in these early stages of life, and information regarding the influence of developmental changes on the pharmacodynamics of medications is even more limited. Theoretically, age-dependent variations in receptor number and affinity for drugs have significant potential to influence an individual's response to drug therapy. In this review, some of the relevant covariates of pharmacokinetics and pharmacodynamics in neonates are reviewed and illustrated based on the published literature.

Clinical implications of pharmacokinetics and pharmacodynamics of procedural sedation agents in children

PURPOSE OF REVIEW

Procedural sedation has become the standard of care for managing pain and anxiety in children in the emergency department.

RECENT FINDINGS

Numerous articles have been published on pediatric procedural sedation with, however, little in-depth discussion of the pharmacodynamics and pharmacokinetics of the sedation agents utilized.

SUMMARY

We review the pharmacokinetics and pharmacodynamics of the pediatric procedural sedation pharmacopeia from a clinical perspective with emphasis on the practical implications for drug titration and dosing.

Profound changes in drug metabolism enzymes and possible effects on drug therapy in neonates and children

INTRODUCTION

There are profound changes that take place in drug metabolism enzymes during fetal and postnatal development. These changes may significantly impact drug therapy in children.

AREAS COVERED

A combination of focused and comprehensive literature searches using PubMed and reference lists (from inception to 7 November 2009) is undertaken to identify reports on in vitro and in vivo development of drug metabolism enzymes as well disposition of selected drugs and their effect in children. The article provides an update on development of drug metabolism enzymes and their impact on drug substrate disposition and disease, which may aid to improve clinical practice and optimally design clinical trials in children.

EXPERT OPINION

Drug metabolism enzyme activity changes profoundly throughout the continuum of postnatal development and often results in different disposition pathways than in adults. Genetics and co-morbidity interact significantly with these developmental changes. Translation of existing knowledge into age-adjusted dosing guidelines and clinical trial design is highly needed for there to be an improvement in drug therapy in children.

A comparison of simple allometric and maturation models for the prediction of morphine clearance in pediatrics

BACKGROUND

The objective of this study is to predict morphine clearance in children (preterm neonates to 10-month-old infants) by maturation models that include age and weight and to compare the predictive performance of morphine maturation models with simple allometric models.

METHODS

Age, weight, and morphine clearance data were obtained from the literature. A maturation model (n=60) for morphine was developed using data from preterm and term neonates to 5-year-old children. The allometric models were developed using the same data as the maturation model. The predictive performance of the models was tested in 88 children of different age groups.

RESULTS

The maturation and allometric models predicted morphine clearance in children with the same degree of accuracy or error. Out of 88 subjects, the prediction error of 50% or less was observed in slightly >60% of the subjects. Almost 40% of the subjects showed a prediction error >50%, 20% of which showed an error ≥ 100%. Although both the maturation and allometric models provided a good prediction of morphine clearance in many children, they were less accurate for many others.

CONCLUSIONS

High intersubject variability in morphine clearance probably led to less than adequate performance of the models. However, there could be many drugs for which intersubject variability in clearance might not be as high as morphine clearance and in those situations these models could perform reasonably well.