Pharmacokinetic models of morphine and its metabolites in neonates:: Systematic comparisons of models from the literature, and development of a new meta-model

Population Pharmacokinetic Model of Adalimumab Based on Prior Information Using Real World Data

Adalimumab is a fully human monoclonal antibody used for the treatment of inflammatory bowel disease (IBD). Due to its considerably variable pharmacokinetics and the risk of developing antibodies against adalimumab, it is highly recommended to use a model-informed precision dosing approach. The aim of this study is to develop a population pharmacokinetic (PopPK) model of adalimumab for patients with IBD based on a literature model (reference model) to be used in the clinical setting. A retrospective observational study with 54 IBD patients was used to develop two different PopPK models based on the reference model. One of the developed models estimated the pharmacokinetic population parameters (estimated model), and the other model incorporated informative priors (prior model). The models were evaluated with bias and imprecision. Clinical impact was also assessed, evaluating the differences in dose interventions. The developed models included the albumin as a continuous covariate on apparent clearance. The prior model was superior to the estimated model in terms of bias, imprecision and clinical impact on the target population. In conclusion, the prior model adequately characterized adalimumab PK in the studied population and was better than the reference model in terms of predictive performance and clinical impact.

External validation of population pharmacokinetic models of gentamicin in paediatric population from preterm newborns to adolescents

The aim of this study was to externally validate the predictive performance of published population pharmacokinetic models of gentamicin in all paediatric age groups, from preterm newborns to adolescents. We first selected published population pharmacokinetic models of gentamicin developed in the paediatric population with a wide age range. The parameters of the literature models were then re-estimated using the PRIOR subroutine in NONMEM^®. The predictive ability of the literature and the tweaked models was evaluated. Retrospectively collected data from a routine clinical practice (512 concentrations from 308 patients) were used for validation. The models with covariates characterising developmental changes in clearance and volume of distribution had better predictive performance, which improved further after re-estimation. The tweaked model by Wang 2019 performed best, with suitable accuracy and precision across the complete paediatric population. For patients treated in the intensive care unit, a lower proportion of patients would be expected to reach the target trough concentration at standard dosing. The selected model could be used for model-informed precision dosing in clinical settings where the entire paediatric population is treated. However, for use in clinical practice, the next step should include additional analysis of the impact of intensive care treatment on gentamicin pharmacokinetics, followed by prospective validation.

External evaluation and systematic review of population pharmacokinetic models for high-dose methotrexate in cancer patients

Several population pharmacokinetic (PPK) models have been established to optimize the therapeutic regimen and reduce the toxicity of high-dose methotrexate (HDMTX) in patients with cancer. However, their predictive performance when extrapolated to different clinical centers was unknown. In this study, we aimed to externally evaluate the predictive ability of HDMTX PPK models and determine the potential influencing factors. We searched the literature and determined the predictive performance of the selected models using methotrexate concentrations in 721 samples from 60 patients in the First Affiliated Hospital of the Navy Medical University. Prediction-based diagnostics and simulation-based normalized prediction distribution errors (NPDE) were used to evaluate the predictive performance of the models. The influence of prior information was also assessed using Bayesian forecasting, and the potential factors affecting model predictability were investigated. Thirty models extracted from published PPK studies were assessed. Prediction-based diagnostics showed that the number of compartments potentially influenced model transferability, and simulation-based NPDE indicated model misspecification. Bayesian forecasting significantly improved the predictive performance of the models. Various factors, including bioassays, covariates, and population diagnosis, influence model extrapolation. The published models were unsatisfactory for all prediction-based diagnostics, except for the 24 h methotrexate concentration monitoring and simulation-based diagnostics, making them inappropriate for direct extrapolation. Moreover, Bayesian forecasting combined therapeutic drug monitoring could improve the predictive performance of the models.

Current knowledge, challenges and innovations in developmental pharmacology: A combined conect4children Expert Group and European Society for Developmental, Perinatal and Paediatric Pharmacology White Paper

Developmental pharmacology describes the impact of maturation on drug disposition (pharmacokinetics, PK) and drug effects (pharmacodynamics, PD) throughout the paediatric age range. This paper, written by a multidisciplinary group of experts, summarizes current knowledge, and provides suggestions to pharmaceutical companies, regulatory agencies and academicians on how to incorporate the latest knowledge regarding developmental pharmacology and innovative techniques into neonatal and paediatric drug development. Biological aspects of drug absorption, distribution, metabolism and excretion throughout development are summarized. Although this area made enormous progress during the last two decades, remaining knowledge gaps were identified. Minimal risk and burden designs allow for optimally informative but minimally invasive PK sampling, while concomitant profiling of drug metabolites may provide additional insight in the unique PK behaviour in children. Furthermore, developmental PD needs to be considered during drug development, which is illustrated by disease- and/or target organ-specific examples. Identifying and testing PD targets and effects in special populations, and application of age- and/or population-specific assessment tools are discussed. Drug development plans also need to incorporate innovative techniques such as preclinical models to study therapeutic strategies, and shift from sequential enrolment of subgroups, to more rational designs. To stimulate appropriate research plans, illustrations of specific PK/PD-related as well as drug safety-related challenges during drug development are provided. The suggestions made in this joint paper of the Innovative Medicines Initiative conect4children Expert group on Developmental Pharmacology and the European Society for Developmental, Perinatal and Paediatric Pharmacology, should facilitate all those involved in drug development.

The PHARMACOM-EPI Framework for Integrating Pharmacometric Modelling Into Pharmacoepidemiological Research Using Real-World Data: Application to Assess Death Associated With Valproate

In pharmacoepidemiology, it is usually expected that the observed association should be directly or indirectly related to the pharmacological effects of the drug/s under investigation. Pharmacological effects are, in turn, strongly connected to the pharmacokinetic and pharmacodynamic properties of a drug, which can be characterized and investigated using pharmacometric models. Recently, the use of pharmacometrics has been proposed to provide pharmacological substantiation of pharmacoepidemiological findings derived from real-world data. However, validated frameworks suggesting how to combine these two disciplines for the aforementioned purpose are missing. Therefore, we propose PHARMACOM-EPI, a framework that provides a structured approach on how to identify, characterize, and apply pharmacometric models with practical details on how to choose software, format dataset, handle missing covariates/dosing data, how to perform the external evaluation of pharmacometric models in real-world data, and how to provide pharmacological substantiation of pharmacoepidemiological findings. PHARMACOM-EPI was tested in a proof-of-concept study to pharmacologically substantiate death associated with valproate use in the Danish population aged ≥ 65 years. Pharmacological substantiation of death during a follow-up period of 1 year showed that in all individuals who died (n = 169) individual predictions were within the subtherapeutic range compared with 52.8% of those who did not die (n = 1,084). Of individuals who died, 66.3% (n = 112) had a cause of death possibly related to valproate and 33.7% (n = 57) with well-defined cause of death unlikely related to valproate. This proof-of-concept study showed that PHARMACOM-EPI was able to provide pharmacological substantiation for death associated with valproate use in the study population.

Toward personalized medicine for pharmacological interventions in neonates using vital signs

Vital signs, such as heart rate and oxygen saturation, are continuously monitored for infants in neonatal care units. Pharmacological interventions can alter an infant's vital signs, either as an intended effect or as a side effect, and consequently could provide an approach to explore the wide variability in pharmacodynamics across infants and could be used to develop models to predict outcome (efficacy or adverse effects) in an individual infant. This will enable doses to be tailored according to the individual, shifting the balance toward efficacy and away from the adverse effects of a drug. Pharmacological analgesics are frequently not given in part due to the risk of adverse effects, yet this exposes infants to the short‐ and long‐term effects of painful procedures. Personalized analgesic dosing will be an important step forward in providing safer effective pain relief in infants. The aim of this paper was to describe a framework to develop predictive models of drug outcome from analysis of vital signs data, focusing on analgesics as a representative example. This framework investigates changes in vital signs in response to the analgesic (prior to the painful procedure) and proposes using machine learning to examine if these changes are predictive of outcome—either efficacy (with pain response measured using a multimodal approach, as changes in vital signs alone have limited sensitivity and specificity) or adverse effects. The framework could be applied to both preterm and term infants in neonatal care units, as well as older children. Sharing vital signs data are proposed as a means to achieve this aim and bring personalized medicine rapidly to the forefront in neonatology.

Model-Informed Bayesian Estimation Improves the Prediction of Morphine Exposure in Neonates and Infants

BACKGROUND

Pain control in infants is an important clinical concern, with potential long-term adverse neurodevelopmental effects. Intravenous morphine is routinely administered for postoperative pain management; however, its dose-concentration-response relationship in neonates and infants has not been well characterized. Although the current literature provides dosing guidelines for the average infant, it fails to control for the large unexplained variability in morphine clearance and response in individual patients. Bayesian estimation can be used to control for some of this variability. The authors aimed to evaluate morphine pharmacokinetics (PKs) and exposure in critically ill neonates and infants receiving standard-of-care morphine therapy and compare a population-based approach to the model-informed Bayesian techniques.

METHODS

The PKs and exposure of morphine and its active metabolites were evaluated in a prospective opportunistic PK study using 221 discarded blood samples from 57 critically ill neonates and infants in the neonatal intensive care unit. Thereafter, a population-based PK model was compared with a Bayesian adaptive control strategy to predict an individual's PK profile and morphine exposure over time.

RESULTS

Among the critically ill neonates and infants, morphine clearance showed substantial variability with a 40-fold range (ie, 2.2 to 87.1, mean 23.7 L/h/70 kg). Compared with the observed morphine concentrations, the population-model based predictions had an R of 0.13, whereas the model-based Bayesian predictions had an R of 0.61.

CONCLUSIONS

Model-informed Bayesian estimation is a better predictor of morphine exposure than PK models alone in critically ill neonates and infants. A large variability was also identified in morphine clearance. A further study is warranted to elucidate the predictive covariates and precision dosing strategies that use morphine concentration and pain scores as feedbacks.

Quantifying the pharmacodynamics of morphine in the treatment of postoperative pain in preverbal children

While the pharmacokinetics of morphine in children have been studied extensively, little is known about the pharmacodynamics of morphine in this population. Here, we quantified the concentration‐effect relationship of morphine for postoperative pain in preverbal children between 0 and 3 years of age. For this, we applied item response theory modeling in the pharmacokinetic/pharmacodynamic analysis of COMFORT‐Behavior (COMFORT‐B) scale data from 2 previous clinical studies. In the model, we identified a sigmoid maximal efficacy model for the effect of morphine and found that in 26% of children, increasing morphine concentrations were not associated with lower pain scores (nonresponders to morphine up‐titration). In responders to morphine up‐titration, the COMFORT‐B score slowly decreases with increasing morphine concentrations at morphine concentrations >20 ng/mL. In nonresponding children, no decrease in COMFORT‐B score is expected. In general, lower baseline COMFORT‐B scores (2.1 points on average) in younger children (postnatal age <10.3 days) were found. Based on the model, we conclude that the percentage of children at a desirable COMFORT‐B score is maximized at a morphine concentration between 5 and 30 ng/mL for children aged <10 days, and between 5 and 40 ng/mL for children >10 days. These findings support a dosing regimen previously suggested by Krekels et al, which would put >95% of patients within this morphine target concentration range at steady state. Our modeling approach provides a promising platform for pharmacodynamic research of analgesics and sedatives in children.

Safety and effectiveness of parent- or nurse-controlled analgesia in neonates: a systematic review

OBJECTIVE

The aim of this systematic review was to determine the safety and effectiveness of parent- or nurse-controlled analgesia on neonatal patient outcomes. More specifically, the objective was to determine the effect of parent- or nurse-controlled analgesia on neonatal pain scores, analgesic use, and incidence of iatrogenic withdrawal syndrome, as well as any opioid-associated adverse events.

INTRODUCTION

Despite recent innovations in neonatology leading to significant improvements in short- and long-term outcomes for newborns requiring intensive care, optimal management of pain and distress remains a challenge for the treating multidisciplinary team. The inability of neonates to communicate pain easily, inconsistent practice among health professionals, insufficient analgesic prescriptions, and delays in medical reviews all impact effective pain management. Exploring the effect of parent- or nurse-controlled analgesia may identify a modality that negates these concerns and improves the pharmacological management of pain in newborns.

INCLUSION CRITERIA

This review considered experimental and observational studies evaluating the safety and effectiveness of parent- or nurse-controlled analgesia that included babies born at 23 weeks' gestation to four weeks post-term. The interventions considered for inclusion were any type of analgesia delivered by an infusion pump that allowed bolus dosing or a continuous analgesic infusion with bolus dosing as required. Studies using algorithms and protocols to guide timing and dosage were eligible for inclusion. Comparators included the standard management of pain for neonates in the newborn intensive care unit. A modification to the a priori protocol was made to include all neonates nursed outside of a neonatal intensive care unit to ensure all studies that examined the use of parent- or nurse-controlled analgesia in the neonatal population were included in the review.

METHODS

An extensive search of six major databases was conducted (CINAHL, Cochrane Library, Embase, PubMed, PsycINFO, and Web of Science). Studies published from 1997 to 2020 in English were considered for inclusion in this review. Databases searched for unpublished studies included MedNar and ProQuest Dissertations and Theses.

RESULTS

Fourteen studies were included in this review: two randomized controlled trials, six quasi-experimental studies, one case-control study, and five case series. There was considerable heterogeneity in the interventions and study outcome measures within the studies, resulting in an inability to statistically pool results. The small sample sizes and inability to distinguish data specific to neonates in six of the studies resulted in low quality of evidence for the safety and effectiveness of parent- or nurse-controlled analgesia in neonates. However, studies reporting neonatal data demonstrated low pain scores and a trend in reduced opioid consumption when parent- or nurse-controlled analgesia was used.

CONCLUSIONS

The use of parent- or nurse-controlled analgesia in the neonatal population has shown some effect in reducing the amount of opioid analgesia required without compromising pain relief or increasing the risk of adverse events. Due to the paucity of evidence available, certainty of the results is compromised; therefore, larger trials exploring the use of parent- or nurse-controlled analgesia in neonates and the development of nurse-led models for analgesia delivery are needed.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO CRD42018114382.

Population pharmacokinetics of clofarabine for allogeneic hematopoietic cell transplantation in paediatric patients

AIMS

Clofarabine has recently been evaluated as part of the conditioning regimen for allogeneic hematopoietic stem cell transplantation (HCT) in children. Pharmacokinetic (PK) exposure of different agents commonly used in conditioning regimens is strongly related to HCT outcome. Consequently, the PK of clofarabine may be important for outcome. This report describes the population PK of clofarabine in paediatric patients and one adult.

METHODS

From 80 paediatric (0.5-18 years) and 1 adult patient (37 years), 805 plasma concentrations were included in pharmacokinetic analyses using nonlinear mixed effects modelling.

RESULTS

A two-compartment model adequately described the PK of clofarabine. Body weight and estimated glomerular filtration rate (eGFR) were included as covariates. Clearance was differentiated into nonrenal and renal clearance (approximately 55% of total clearance), resulting in population estimates of 24.0 L/h (95% confidence interval [CI] 13.7-34.4) and 29.8 L/h (95% CI 23.9-36.1) for a patient of 70 kg with normal renal function, respectively. Unexplained interindividual variability in clearance was 17.8% (95% CI 14.6-22.4). A high variability in exposure was observed (range area under the curveT0-inf 1.8-6.0 mg/L*h) after body surface area (BSA) based dosing. Interestingly, children with low body weight had a lower exposure than children with a higher body weight, which indicates that the currently practised BSA-based dosing is not adequate for clofarabine.

CONCLUSION

A clofarabine dosing algorithm based on this PK model, using body weight and eGFR, results in a more predictable exposure than BSA-based dosing. However, the exact target exposure needs to be further investigated.

Considerations for Drug Dosing in Premature Infants

In premature infants, effective and safe drug therapy depends on optimal dose selection and requires a thorough understanding of the underlying disease(s) of these fragile infants as well as the pharmacokinetics and pharmacodynamics of the drugs selected to treat their diseases. Differences in gestational and postnatal age or weight are the major determinants of the observed variability in drug disposition and effect in these infants. This article presents an outline on how to translate the results of a population pharmacokinetic/pharmacodynamic study into rational dosing regimens, and how physiologically based pharmacokinetic modeling, electronic health records, and the abundantly available data of vital functions of premature infants during their stay in the neonatal intensive care unit for evaluation of their pharmacotherapy can be used to tailor the most safe and effective dose in these infants.

Pharmacotherapy of neonatal opioid withdrawal syndrome: a review of pharmacokinetics and pharmacodynamics

INTRODUCTION

Neonatal opioid withdrawal syndrome (NOWS) often arises in infants born to mothers who used opioids during pregnancy. Morphine, methadone, and buprenorphine are the most common first-line treatments, whereas clonidine and phenobarbital are generally reserved for adjunctive therapy. These drugs exhibit substantial pharmacokinetic (PK) and pharmacodynamic (PD) variability. Current pharmacological treatments for NOWS are based on institutional protocols and largely rely on empirical treatment of patient symptoms.

AREAS COVERED

This article reviews the PK/PD of NOWS pharmacotherapies with a focus on the implication of physiological development and maturation. Body size-standardized clearance is consistently low in neonates, except for methadone. This can be ascribed to underdeveloped metabolic and elimination pathways. The effects of pharmacogenetics have been clarified especially for morphine. The PK/PD relationship of medications used in the treatment of NOWS is generally understudied.

EXPERT OPINION

Providing an appropriate opioid dose in neonates is challenging. Advancements in quantitative pharmacology and PK/PD modeling approaches facilitate identification of key factors driving PK/PD variability and characterization of exposure-response relationships. PK/PD model-informed simulations have been widely employed to define age-appropriate pediatric dosing regimens. The model-informed approach holds promise to aid more rational use of medications in the treatment of NOWS.

Prediction of Drug Exposure in Critically Ill Encephalopathic Neonates Treated With Therapeutic Hypothermia Based on a Pooled Population Pharmacokinetic Analysis of Seven Drugs and Five Metabolites

Drug dosing in encephalopathic neonates treated with therapeutic hypothermia is challenging; exposure is dependent on body size and maturation but can also be influenced by factors related to disease and treatment. A better understanding of underlying pharmacokinetic principles is essential to guide drug dosing in this population. The prospective multicenter cohort study PharmaCool was designed to investigate the pharmacokinetics of commonly used drugs in neonatal encephalopathy. In the present study, all data obtained in the PharmaCool study were combined to study the structural system specific effects of body size, maturation, recovery of organ function, and temperature on drug clearance using nonlinear mixed effects modeling. Data collected during the first 5 days of life from 192 neonates treated with therapeutic hypothermia were included. An integrated population pharmacokinetic model of seven drugs (morphine, midazolam, lidocaine, phenobarbital, amoxicillin, gentamicin, and benzylpenicillin) and five metabolites (morphine-3-glucuronide, morphine-6-glucuronide, 1-hydroxymidazolam, hydroxymidazolam glucuronide, and monoethylglycylxylidide) was successfully developed based on previously developed models for the individual drugs. For all compounds, body size was related to clearance using allometric relationships and maturation was described with gestational age in a fixed sigmoidal Hill equation. Organ recovery after birth was incorporated using postnatal age. Clearance increased by 1.23%/hours of life (95% confidence interval (CI) 1.03-1.43) and by 0.54%/hours of life (95% CI 0.371-0.750) for high and intermediate clearance compounds, respectively. Therapeutic hypothermia reduced clearance of intermediate clearance compounds only, by 6.83%/°C (95% CI 5.16%/°C-8.34%/°C). This integrated model can be used to facilitate drug dosing and future pharmacokinetic studies in this population.

Prior information for population pharmacokinetic and pharmacokinetic/pharmacodynamic analysis: overview and guidance with a focus on the NONMEM PRIOR subroutine

Abstract

Population pharmacokinetic analysis is used to estimate pharmacokinetic parameters and their variability from concentration data. Due to data sparseness issues, available datasets often do not allow the estimation of all parameters of the suitable model. The PRIOR subroutine in NONMEM supports the estimation of some or all parameters with values from previous models, as an alternative to fixing them or adding data to the dataset. From a literature review, the best practices were compiled to provide a practical guidance for the use of the PRIOR subroutine in NONMEM. Thirty-three articles reported the use of the PRIOR subroutine in NONMEM, mostly in special populations. This approach allowed fast, stable and satisfying modelling. The guidance provides general advice on how to select the most appropriate reference model when there are several previous models available, and to implement and weight the selected parameter values in the PRIOR function. On the model built with PRIOR, the similarity of estimates with the ones of the reference model and the sensitivity of the model to the PRIOR values should be checked. Covariates could be implemented a priori (from the reference model) or a posteriori, only on parameters estimated without prior (search for new covariates).

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s10928-020-09695-z) contains supplementary material, which is available to authorized users.

Clinical implementation of pharmacogenetics and model-informed precision dosing to improve patient care

Providing maximal therapeutic efficacy without toxicity is a universal goal of rational drug therapy. However, substantial between-patient variability in drug response often impedes such successful treatments and brings the necessity of tailoring drug dose to individual needs for more precise therapy. In many cases plenty of patient characteristics, such as body size, genetic makeup and environmental factors, need to be taken into consideration to find the optimal dose in clinical practice. A pharmacokinetics and pharmacodynamics (PK/PD) model-informed approach offers integration of various patient information to provide an expectation of drug response and derive practical dose estimates to support clinicians' dosing decisions. Such an approach was pioneered in the late 1970s, but its broad clinical acceptance and implementation have been hampered by the lack of widespread computer technology, including user-friendly software tools. This has significantly changed in recent years. With the advent of electronic health records (EHRs) and the ubiquity of user-friendly software tools, we now experience a convergence of clinical information, pharmacogenetics, systems pharmacology and pharmacometrics, and technology. Advanced pharmacometrics research is now more appliable and implementable to improve health care. This article presents examples of successful development and implementation of pharmacogenetics-guided and PK/PD model-informed decision support to facilitate precision dosing, including the development of an EHR-embedded decision support tool. Through the integration of clinical decision support tools in EHRs, clinical pharmacometrics support can be brought directly to the clinical team and the bedside.

Software Tools for Model-Informed Precision Dosing: How Well Do They Satisfy the Needs?

Model-informed precision dosing (MIPD) software tools are used to optimize dosage regimens in individual patients, aiming to achieve drug exposure targets associated with desirable clinical outcomes. Over the last few decades, numerous MIPD software tools have been developed. However, they have still not been widely integrated into clinical practice. This study focuses on identifying the requirements for and evaluating the performance of the currently available MIPD software tools. First, a total of 22 experts in the field of precision dosing completed a web survey to assess the importance (from 0; do not agree at all, to 10; completely agree) of 103 pre-established software tool criteria organized in eight categories: user-friendliness and utilization, user support, computational aspects, population models, quality and validation, output generation, privacy and data security, and cost. Category mean ± pooled standard deviation importance scores ranged from 7.2 ± 2.1 (user-friendliness and utilization) to 8.5 ± 1.8 (privacy and data security). The relative importance score of each criterion within a category was used as a weighting factor in the subsequent evaluation of the software tools. Ten software tools were identified through literature and internet searches: four software tools were provided by companies (DoseMeRx, InsightRX Nova, MwPharm++, and PrecisePK) and six were provided by non-company owners (AutoKinetics, BestDose, ID-ODS, NextDose, TDMx, and Tucuxi). All software tools performed well in all categories, although there were differences in terms of in-built software features, user interface design, the number of drug modules and populations, user support, quality control, and cost. Therefore, the choice for a certain software tool should be made based on these differences and personal preferences. However, there are still improvements to be made in terms of electronic health record integration, standardization of software and model validation strategies, and prospective evidence for the software tools’ clinical and cost benefits.

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

OBJECTIVE

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

DESIGN

Prospective pharmacokinetic-pharmacogenomic observational study.

SETTING

Thirteen PICUs across the United States.

PATIENTS

Pediatric subjects (n = 66) 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 morphine, the two main metabolites, morphine-3-glucuronide and morphine-6-glucuronide, were quantified by high-performance liquid chromatography tandem mass spectrometry/mass spectroscopy. 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. A two-compartment model with linear elimination and two individual compartments for metabolites best describe morphine disposition in this population. Our analysis demonstrates that body weight and postmenstrual age are relevant predictors of pharmacokinetic parameters of morphine and its metabolites. Furthermore, our research shows that a duration of mechanical ventilation greater than or equal to 10 days reduces metabolite formation and elimination upwards of 30%. However, due to the small sample size and relative heterogeneity of the population, no heritable factors associated with uridine diphosphate glucuronyl transferase 2B7 metabolism of morphine were identified.

CONCLUSIONS

The results provide a better understanding of the disposition of morphine and its metabolites in critically ill children with acute respiratory failure requiring mechanical ventilation due to nonheritable factors. It also provides the groundwork for developing additional studies to investigate the role of heritable factors.

Influence of MRP3 Genetics and Hepatic Expression Ontogeny for Morphine Disposition in Neonatal and Pediatric Patients

We have previously reported the influences of OCT1 ontogeny and genetic variation on morphine clearance in neonatal and pediatric patients. In the latter study, plasma morphine-glucuronide levels correlated with patient genotype for the rs4793665 single-nucleotide polymorphism (SNP) at the locus of MRP3, an efflux transporter of morphine glucuronides between hepatocytes and circulating blood. The link between MRP3 activity and overall morphine clearance has not been thoroughly investigated however, and the developmental profile of hepatic MRP3 protein expression remains thinly defined between neonates and adults. In the current study, previously determined morphine clearance values for neonatal (24-58 weeks postmenstrual age, N = 57) and pediatric (5-16 years, n = 85) patients were reanalyzed for correlation to the SNP genotype of patient rs4793665. Among OCT1 wild-type patients, pediatric morphine clearance showed a significant decreasing trend by MRP3 genotypes in the order of CC > CT > TT (P = .014), whereas for neonates, an identical but nonsignificant trend was observed. Pharmacogenetic differences in MRP3 and OCT1 ontogeny were evaluated by Western blot of hepatic membrane fractions from 50 subjects aged 1 day postnatal to 33 years old. Hepatic MRP3 protein level did not vary by rs4793665 genotype, and followed an atypical developmental pattern of increase up to 1-2 years of age, thereafter decreasing during preadolescence before increasing again to adult levels at maturity (17-33 years). By comparison, OCT1 expression was significantly decreased in OCT1 *1/*3 genotyped patients older than 1 year and followed a trajectory consistent with prior studies. Our results suggest that consideration of MRP3 pharmacogenetics and ontogeny may aid in identifying pediatric patients having different/atypical morphine requirements.

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.

Lidocaine as treatment for neonatal seizures: Evaluation of previously developed population pharmacokinetic models and dosing regimen

AIMS

Lidocaine is used to treat neonatal seizures refractory to other anticonvulsants. It is effective, but also associated with cardiac toxicity. Previous studies have reported on the pharmacokinetics of lidocaine in preterm and term neonates and proposed a dosing regimen for effective and safe lidocaine use. The objective of this study was to evaluate the previously developed pharmacokinetic models and dosing regimen. As a secondary objective, lidocaine effectiveness and safety were assessed.

METHODS

Data from preterm neonates and (near-)term neonates with and without therapeutic hypothermia receiving lidocaine were included. Pharmacokinetic analyses were performed using non-linear mixed effects modelling. Simulations were performed to evaluate the proposed dosing regimen. Lidocaine was considered effective if no additional anticonvulsant was required and safe if no cardiac adverse events occurred.

RESULTS

Data were available for 159 neonates; 50 (31.4%) preterm and 109 term neonates, of whom 49 (30.8%) were treated with therapeutic hypothermia. Lidocaine clearance increased with postmenstrual age by 0.69%/day (95% confidence interval 0.54-0.84%). During therapeutic hypothermia (33.5°C), lidocaine clearance was reduced by 21.8% (7.26%/°C, 95% confidence interval 1.63-11.2%) compared to normothermia (36.5°C). Simulations demonstrated that the proposed dosing regimen leads to adequate average lidocaine plasma concentrations. Effectiveness and safety were assessed in 92 neonates. Overall effectiveness was 53.3% (49/92) and 56.5% (13/23) for neonates receiving the proposed dosing regimen. No cardiac toxicity was observed.

CONCLUSION

Lidocaine pharmacokinetics was adequately described across the entire neonatal age range. With the proposed dosing regimen, lidocaine can provide effective and safe treatment for neonatal seizures.

Electronic Health Record-Embedded Decision Support Platform for Morphine Precision Dosing in Neonates

Morphine is the opioid most commonly used for neonatal pain management. In intravenous form, it is administered as continuous infusions and intermittent injections, mostly based on empirically established protocols. Inadequate pain control in neonates can cause long-term adverse consequences; however, providing appropriate individualized morphine dosing is particularly challenging due to the interplay of rapid natural physiological changes and multiple life-sustaining procedures in patients who cannot describe their symptoms. At most institutions, morphine dosing in neonates is largely carried out as an iterative process using a wide range of starting doses and then titrating to effect based on clinical response and side effects using pain scores and levels of sedation. Our background data show that neonates exhibit large variability in morphine clearance resulting in a wide range of exposures, which are poorly predicted by dose alone. Here, we describe the development and implementation of an electronic health record-integrated, model-informed decision support platform for the precision dosing of morphine in the management of neonatal pain. The platform supports pharmacokinetic model-informed dosing guidance and has functionality to incorporate real-time drug concentration information. The feedback is inserted directly into prescribers' workflows so that they can make data-informed decisions. The expected outcomes are better clinical efficacy and safety with fewer side effects in the neonatal population.

Analgesics and Sedatives in Critically Ill Newborns and Infants: The Impact on Long-Term Neurodevelopment

Inadequate pain and/or stress management in preterm- and term-born infants has been associated with increased morbidity and even mortality. However, exposure to analgosedatives during early infancy may also be one of the risk factors for subsequent neurodevelopmental impairment, at least in animal studies. Because infants admitted to neonatal or pediatric intensive care units may receive high amounts of these drugs for prolonged periods of time and the majority of these infants nowadays survive to discharge, this is of major concern. A balanced approach that incorporates the assessment and quantification of both wanted effects as well as unwanted side effects is therefore needed. In this article, the optimal dose determination of commonly used analgosedative drugs as well as their potential long-term effects on the developing human brain and neuropsychological functioning are reviewed.

Pharmacokinetics of morphine in encephalopathic neonates treated with therapeutic hypothermia

OBJECTIVE

Morphine is a commonly used drug in encephalopathic neonates treated with therapeutic hypothermia after perinatal asphyxia. Pharmacokinetics and optimal dosing of morphine in this population are largely unknown. The objective of this study was to describe pharmacokinetics of morphine and its metabolites morphine-3-glucuronide and morphine-6-glucuronide in encephalopathic neonates treated with therapeutic hypothermia and to develop pharmacokinetics based dosing guidelines for this population.

STUDY DESIGN

Term and near-term encephalopathic neonates treated with therapeutic hypothermia and receiving morphine were included in two multicenter cohort studies between 2008-2010 (SHIVER) and 2010-2014 (PharmaCool). Data were collected during hypothermia and rewarming, including blood samples for quantification of morphine and its metabolites. Parental informed consent was obtained for all participants.

RESULTS

244 patients (GA mean (sd) 39.8 (1.6) weeks, BW mean (sd) 3,428 (613) g, male 61.5%) were included. Morphine clearance was reduced under hypothermia (33.5°C) by 6.89%/°C (95% CI 5.37%/°C- 8.41%/°C, p<0.001) and metabolite clearance by 4.91%/°C (95% CI 3.53%/°C- 6.22%/°C, p<0.001) compared to normothermia (36.5°C). Simulations showed that a loading dose of 50 μg/kg followed by continuous infusion of 5 μg/kg/h resulted in morphine plasma concentrations in the desired range (between 10 and 40 μg/L) during hypothermia.

CONCLUSIONS

Clearance of morphine and its metabolites in neonates is affected by therapeutic hypothermia. The regimen suggested by the simulations will be sufficient in the majority of patients. However, due to the large interpatient variability a higher dose might be necessary in individual patients to achieve the desired effect.

TRIAL REGISTRATION

www.trialregister.nl NTR2529.

Pharmacokinetic considerations for pediatric patients receiving analgesia in the intensive care unit; targeting postoperative, ECMO and hypothermia patients

INTRODUCTION

Adequate postoperative analgesia in pediatric patients in the intensive care unit (ICU) matters, since untreated pain is associated with negative outcomes. Compared to routine postoperative patients, children undergoing hypothermia (HT) or extracorporeal membrane oxygenation (ECMO), or recovering after cardiac surgery likely display non-maturational differences in pharmacokinetics (PK) and pharmacodynamics (PD). These differences warrant additional dosing recommendations to optimize pain treatment. Areas covered: Specific populations within the ICU will be discussed with respect to expected variations in PK and PD for various analgesics. We hereby move beyond maturational changes and focus on why PK/PD may be different in children undergoing HT, ECMO or cardiac surgery. We provide a stepwise manner to develop PK-based dosing regimens using population PK approaches in these populations. Expert opinion: A one-dose to size-fits-all for analgesia is suboptimal, but for several commonly used analgesics the impact of HT, ECMO or cardiac surgery on average PK parameters in children is not yet sufficiently known. Parameters considering both maturational and non-maturational covariates are important to develop population PK-based dosing advices as part of a strategy to optimize pain treatment.

Drug metabolism in early infancy: opioids as an illustration

INTRODUCTION

Drug dosing in infants frequently depends on body weight as a crude indicator for maturation. Fentanyl (metabolized by Cytochrome P450 3A4) and morphine (glucuronidated by UDP-glucuronosyltransferase-2B7) served as model drugs to provide insight in maturation patterns of these enzymes and provide understanding of the impact of non-maturational factors to optimize dosing in infants. Areas covered: Systematic searches on metabolism and population pharmacokinetic (Pop-PK) models for fentanyl and morphine were performed. Pre- and post-model selection criteria were applied to assess and evaluate the validity of these models. It was observed that maturational changes have been rather well investigated, be it with variability in the maturational function estimates. The same holds true for Pop-PK models, where non-maturational covariates have also been reported (pharmacogenetics, disease state or external influences), although less incorporated in the PK models and with limited knowledge on mechanisms involved. Expert opinion: PK models for fentanyl and morphine are currently available. Consequently, we suggest that researchers should not continue to develop new models, but should investigate whether collected data fit in already existing models and provide additional value concerning the impact of (non)-maturational factors like drug-drug interactions or pharmacogenetics.

Paracetamol and morphine for infant and neonatal pain; still a long way to go?

INTRODUCTION

Pharmacologic pain management in newborns and infants is often based on limited scientific data. To close the knowledge gap, drug-related research in this population is increasingly supported by the authorities, but remains very challenging. This review summarizes the challenges of analgesic studies in newborns and infants on morphine and paracetamol (acetaminophen). Areas covered: Aspects such as the definition and multimodal character of pain are reflected to newborn infants. Specific problems addressed include defining pharmacodynamic endpoints, performing clinical trials in this population and assessing developmental changes in both pharmacokinetics and pharmacodynamics. Expert commentary: Neonatal and infant pain management research faces two major challenges: lack of clear biomarkers and very heterogeneous pharmacokinetics and pharmacodynamics of analgesics. There is a clear call for integral research addressing the multimodality of pain in this population and further developing population pharmacokinetic models towards physiology-based models.