Evidence-based drug treatment for special patient populations through model-based approaches

Advances in pharmacokinetic-pharmacodynamic modelling for pediatric drug development: extrapolations and exposure-response analyses

INTRODUCTION

Pharmacokinetic (PK)-Pharmacodynamic (PD) and exposure-response (E-R) modeling are critical parts of pediatric drug development. By integrating available knowledge and supportive data to support the design of future studies and pediatric dose selection, these techniques increase the efficiency of pediatric drug development and lowers the risk of exposing pediatric study participants to suboptimal or unsafe dose regimens.

AREAS COVERED

The role of PK, PK-PD and E-R modeling within pediatric drug development and pediatric dose selection is discussed. These models allow investigation of the impact of age and bodyweight on PK and PD in children, despite the often sparse data on the pediatric population. Also discussed is how E-R analyses strengthen the evidence basis to support (full or partial) extrapolation of drug efficacy from adults to children, and between different pediatric age groups.

EXPERT OPINION

Accelerated pediatric drug development and optimized pediatric dosing guidelines are expected from three future developments: (1) Increased focus on E-R modeling of currently approved drugs in children resulting in (novel) E-R modeling techniques and best practices, (2) increased use of real-world data for E-R (3) increased implementation of available population PK and E-R information in pediatric drug dosing guidelines.

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.

Predictive performance and verification of physiologically based pharmacokinetic model of propylthiouracil

Background: Propylthiouracil (PTU) treats hyperthyroidism and thyroid crisis in all age groups. A variety of serious adverse effects can occur during clinical use and require attention to its pharmacokinetic and pharmacodynamic characteristics in various populations.

Objective: To provide information for individualized dosing and clinical evaluation of PTU in the clinical setting by developing a physiologically based pharmacokinetic (PBPK) model, predicting ADME characteristics, and extrapolating to elderly and pediatric populations.

Methods: Relevant databases and literature were retrieved to collect PTU’s pharmacochemical properties and ADME parameters, etc. A PBPK model for adults was developed using PK-Sim® software to predict tissue distribution and extrapolated to elderly and pediatric populations. The mean fold error (MFE) method was used to compare the differences between predicted and observed values to assess the accuracy of the PBPK model. The model was validated using PTU pharmacokinetic data in healthy adult populations.

Result: The MFE ratios of predicted to observed values of AUC0-t, Cmax, and Tmax were mainly within 0.5 and 2. PTU concentrations in various tissues are lower than venous plasma concentrations. Compared to healthy adults, the pediatric population requires quantitative adjustment to the appropriate dose to achieve the same plasma exposure levels, while the elderly do not require dose adjustments.

Conclusion: The PBPK model of PTU was successfully developed, externally validated, and applied to tissue distribution prediction and special population extrapolation, which provides a reference for clinical individualized drug administration and evaluation.

Current and future physiologically based pharmacokinetic (PBPK) modeling approaches to optimize pharmacotherapy in preterm neonates

INTRODUCTION

There is a need for structured approaches to inform on pharmacotherapy in preterm neonates. With their proven track record up to regulatory acceptance, physiologically based pharmacokinetic (PBPK) modeling and simulation provide such a structured approach, and hold the promise to support drug development in preterm neonates.

AREAS COVERED

Compared to the general and pediatric use of PBPK modeling, its use to inform pharmacotherapy in preterms is limited. Using a systematic search (PBPK + preterm), we retained 25 records (20 research papers, 2 letters, 3 abstracts). We subsequently collated the published information on PBPK software packages (PK-Sim®, Simcyp®), and their applications and optimization efforts in preterm neonates. It is encouraging that these applications cover a broad range of scenarios (pharmacokinetic-dynamic analyses, drug-drug interactions, developmental pharmacogenetics, lactation related exposure) and compounds (small molecules, proteins). Furthermore, specific compartments (cerebrospinal fluid, tissue) or (patho)physiologic processes (cardiac output, biliary excretion, first pass metabolism) are considered.

EXPERT OPINION

Knowledge gaps exist, giving rise to various levels of model uncertainty in PBPK applications in preterm neonates. To improve this setting, we need cross talk between clinicians and modelers to generate and integrate knowledge (PK datasets, system knowledge, maturational physiology and pathophysiology) to further refine PBPK models.

Ontogeny of Scaling Factors for Pediatric Physiology-Based Pharmacokinetic Modeling and Simulation: Microsomal Protein Per Gram of Liver

Microsomal protein per gram of liver (MPPGL) is an important scaling factor for bottom-up physiology-based pharmacokinetic modeling and simulation, but data in pediatrics are limited. Therefore, MPPGL was determined in 160 liver samples from pediatric (n = 129) and adult (n = 31) donors obtained from four sources: the University of Maryland Brain and Tissue Bank (UMBTB), tissue retrieval services at the University of Minnesota and University of Pittsburgh, and Sekisui-Xenotech. Tissues were homogenized and subjected to differential centrifugation to prepare microsomes, and cytochrome c reductase activities in tissue homogenates and microsomes were used to estimate cytochrome P450 reductase (POR) activity as a marker of microsomal recovery; microsomal POR content was also assessed by quantitative proteomics. MPPGL values varied 5- to 10-fold within various age groups/developmental stages, and tissue source was identified as a contributing factor. Using a "trimmed" dataset comprised of samples ranging from 3 to 18 years of age common to the four sources, POR protein abundance and activity in microsomes and POR activity in homogenates was lower in UMBTB samples (autopsy) compared with other sources (perfused/flash-frozen). Regression analyses revealed that the UMBTB samples were driving an apparent age effect as no effect of age on log-transformed MPPGL values was observed when the UMBTB samples were excluded. We conclude that a mean±SD MPPGL value of 30.4±1.7 mg/g is representative between one month postnatal age and early adulthood. Potential source effects should be considered for studies involving tissue samples from multiple sources with different procurement and processing procedures. SIGNIFICANCE STATEMENT: Microsomal protein per gram of liver (MPPGL) is an important scaling factor for bottom up PBPK modeling and simulation, but data in pediatrics are limited. Although MPPGL varies 5- to 10-fold at a given developmental stage, a value of 30.4 ± 1.7 mg/g (mean ± SD) is representative between one month postnatal age and early adulthood. However, when tissue samples are obtained from multiple sources, different procurement and processing procedures may influence the results and should be taken into consideration.

Pre- and Postnatal Maturation are Important for Fentanyl Exposure in Preterm and Term Newborns: A Pooled Population Pharmacokinetic Study

BACKGROUND AND OBJECTIVE

Fentanyl is an opioid commonly used to prevent and treat severe pain in neonates; however, its use is off label and mostly based on bodyweight. Given the limited pharmacokinetic information across the entire neonatal age range, we characterized the pharmacokinetics of fentanyl across preterm and term neonates to individualize dosing.

METHODS

We pooled data from two previous studies on 164 newborns with a median gestational age of 29.0 weeks (range 23.9-42.3), birthweight of 1055 g (range 390-4245), and postnatal age (PNA) of 1 day (range 0-68). In total, 673 plasma samples upon bolus dosing (69 patients; median dose 2.1 μg/kg, median 2 boluses per patient) or continuous infusions (95 patients; median dose 1.1 μg/kg/h for 30 h) with and without boluses were used for population pharmacokinetic modeling in NONMEM^® 7.4.

RESULTS

Clearance in neonates with birthweight of 2000 and 3000 g was 2.8- and 5.0-fold the clearance in a neonate with birthweight of 1000 g, respectively. Fentanyl clearance at PNA of 7, 14, and 21 days was 2.7-fold, 3.8-fold, and 4.6-fold the clearance at 1 day, respectively. Bodyweight-based dosing resulted in large differences in fentanyl concentrations. Depending on PNA and birthweight, fentanyl concentrations increased slowly after the start of therapy for both intermittent boluses and continuous infusion and reached a maximum concentration at 12-48 h.

CONCLUSIONS

As both prenatal and postnatal maturation are important for fentanyl exposure, we propose a birthweight- and PNA-based dosage regimen. To provide rapid analgesia in the first 24 h of treatment, additional loading doses need to be considered.

Translation of Pharmacodynamic Biomarkers of Antibiotic Efficacy in Specific Populations to Optimize Doses

Antibiotic efficacy determination in clinical trials often relies on non-inferiority designs because they afford smaller study sample sizes. These efficacy studies tend to exclude patients within specific populations or include too few patients to discern potential differences in their clinical outcomes. As a result, dosing guidance in patients with abnormal liver and kidney function, age across the lifespan, and other specific populations relies on drug exposure-matching. The underlying assumption for exposure-matching is that the disease course and the response to the antibiotic are similar in patients with and without the specific condition. While this may not be the case, clinical efficacy studies are underpowered to ensure this is true. The current paper provides an integrative review of the current approach to dose selection in specific populations. We review existing clinical trial endpoints that could be measured on a more continuous rather than a discrete scale to better inform exposure-response relationships. The inclusion of newer systemic biomarkers of efficacy can help overcome the current limitations. We use a modeling and simulation exercise to illustrate how an efficacy biomarker can inform dose selection better. Studies that inform response-matching rather than exposure-matching only are needed to improve dose selection in specific populations.

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.

Population pharmacokinetics of diethylcarbamazine in patients with lymphatic filariasis and healthy individuals

Diethylcarbamazine (DEC) is a drug of choice to treat lymphatic filariasis (LF) either used alone or in combination as mass drug administration (MDA) preventive strategies. The objective of this study was to develop a population pharmacokinetic model for DEC in subjects infected with lymphatic filariasis (LF) compared to healthy individuals, and to evaluate the effect of covariates on the volume of distribution (V/F) and oral clearance (CL/F) of DEC. This was an open-label cohort study of treatment naïve Wuchereria bancrofti-infected (n=32) and uninfected (n=24) adults residing in the Agboville district of Côte d'Ivoire. The population pharmacokinetic model for DEC was built using Phoenix NLME 8.0 software. The covariates included in the model building process were age, gender, bodyweight, infection status, creatinine clearance (CrCl), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels. A total of 56 adults were enrolled in the study and a total of 728 samples were obtained over 168 hours. A one-compartment linear pharmacokinetic model with first-order absorption with an absorption lag-time (Tlag) best described the data. After determining the pharmacokinetics (PK) parameters of DEC, body weight and gender were found to be the significant covariates for DEC V/F. The final population pharmacokinetic model adequately described the pharmacokinetics of DEC in the studied population. Model-based simulation indicated that the body weight significantly impacted the exposure in both the male and female population. This analysis may further support the drug-drug interaction model development of DEC with different co-administered drugs/agents in disease control programs.

The bioavailability and maturing clearance of doxapram in preterm infants

BACKGROUND

Doxapram is used for the treatment of apnea of prematurity in dosing regimens only based on bodyweight, as pharmacokinetic data are limited. This study describes the pharmacokinetics of doxapram and keto-doxapram in preterm infants.

METHODS

Data (302 samples) from 75 neonates were included with a median (range) gestational age (GA) 25.9 (23.9-29.4) weeks, bodyweight 0.95 (0.48-1.61) kg, and postnatal age (PNA) 17 (1-52) days at the start of continuous treatment. A population pharmacokinetic model was developed using non-linear mixed-effects modelling (NONMEM®).

RESULTS

A two-compartment model best described the pharmacokinetics of doxapram and keto-doxapram. PNA and GA affected the formation clearance of keto-doxapram (CL_{FORMATION KETO-DOXAPRAM}) and clearance of doxapram via other routes (CL_{DOXAPRAM OTHER ROUTES}). For a median individual of 0.95 kg, GA 25.6 weeks, and PNA 29 days, CL_{FORMATION KETO-DOXAPRAM} was 0.115 L/h (relative standard error (RSE) 12%) and CL_{DOXAPRAM OTHER ROUTES} was 0.645 L/h (RSE 9%). Oral bioavailability was estimated at 74% (RSE 10%).

CONCLUSIONS

Dosing of doxapram only based on bodyweight results in the highest exposure in preterm infants with the lowest PNA and GA. Therefore, dosing may need to be adjusted for GA and PNA to minimize the risk of accumulation and adverse events. For switching to oral therapy, a 33% dose increase is required to maintain exposure.

IMPACT

Current dosing regimens of doxapram in preterm infants only based on bodyweight result in the highest exposure in infants with the lowest PNA and GA. Dosing of doxapram may need to be adjusted for GA and PNA to minimize the risk of accumulation and adverse events. Describing the pharmacokinetics of doxapram and its active metabolite keto-doxapram following intravenous and gastroenteral administration enables to include drug exposure to the evaluation of treatment of AOP. The oral bioavailability of doxapram in preterm neonates is 74%, requiring a 33% higher dose via oral than intravenous administration to maintain exposure.

Qualifying drug dosing regimens in pediatrics using Gaussian processes

Drug development commonly studies an adult population first and then the pediatric population. The knowledge from the adult population is taken advantage of for the design of the pediatric trials. Adjusted drug doses for these are often derived from adult pharmacokinetic (PK) models which are extrapolated to patients with smaller body size. This extrapolation is based on scaling physiologic model parameters with a body size measure accounting for organ size differences. The inherent assumption is that children are merely small adults. However, children can be subject to additional effects such as organ maturation. These effects are not present in the adult population and are possibly overlooked at the design stage of the pediatric trials. It is thus crucial to qualify the extrapolation assumptions once the pediatric trial data are available. In this work, we propose a model based on a non-parametric regression method called Gaussian process (GP) to detect deviations from the made extrapolation assumptions. We introduce the theoretical background of this model and compare its performance to a parametric expansion of the adult model. The comparison includes simulations and a clinical study data example. The results show that the GP approach can reliably detect maturation trends from sparse pediatric data.

Concept and utility of population pharmacokinetic and pharmacokinetic/pharmacodynamic models in drug development and clinical practice

Due to frequent clinical trial failures and consequently fewer new drug approvals, the need for improvement in drug development has, to a certain extent, been met using model-based drug development. Pharmacometrics is a part of pharmacology that quantifies drug behaviour, treatment response and disease progression based on different models (pharmacokinetic - PK, pharmacodynamic - PD, PK/PD models, etc.) and simulations. Regulatory bodies (European Medicines Agency, Food and Drug Administration) encourage the use of modelling and simulations to facilitate decision-making throughout all drug development phases. Moreover, the identification of factors that contribute to variability provides a basis for dose individualisation in routine clinical practice. This review summarises current knowledge regarding the application of pharmacometrics in drug development and clinical practice with emphasis on the population modelling approach.

Stratified Management for Bacterial Infections in Late Preterm and Term Neonates: Current Strategies and Future Opportunities Toward Precision Medicine

Bacterial infections remain a major cause of morbidity and mortality in the neonatal period. Therefore, many neonates, including late preterm and term neonates, are exposed to antibiotics in the first weeks of life. Data on the importance of inter-individual differences and disease signatures are accumulating. Differences that may potentially influence treatment requirement and success rate. However, currently, many neonates are treated following a "one size fits all" approach, based on general protocols and standard antibiotic treatment regimens. Precision medicine has emerged in the last years and is perceived as a new, holistic, way of stratifying patients based on large-scale data including patient characteristics and disease specific features. Specific to sepsis, differences in disease susceptibility, disease severity, immune response and pharmacokinetics and -dynamics can be used for the development of treatment algorithms helping clinicians decide when and how to treat a specific patient or a specific subpopulation. In this review, we highlight the current and future developments that could allow transition to a more precise manner of antibiotic treatment in late preterm and term neonates, and propose a research agenda toward precision medicine for neonatal bacterial infections.

Compulsory and voluntary drug treatment models in China: A need for improved evidence-based policy and practice to reduce the loaded burden of substance use disorders

In China, the majority of people who use drugs (PWUD) identified by authorities are admitted to compulsory isolated detoxification centers in which their treatment is administered by administrative and judicial systems that restrict their freedom. China's compulsory isolated detoxification centers have been criticized as an abuse of human rights. The two other primary models of drug treatment in China include community-based treatment and medically-oriented voluntary treatment. This article presents an overview of the three primary treatment models for PWUD currently practiced in China. The existing compulsory and voluntary treatment models predominantly operate separately from each other, and lack evidence-based guidelines. A drug treatment system that embraces social support, psychosocial interventions and well-qualified health-based workforce is currently lacking. We propose that China needs to employ a localized model that is composed of well-facilitated and evidence-based treatment methods for both compulsory and voluntary treatment for PWUD to reduce the burden of illicit drug use. The implementation of these models of care, however, need to be tailored to the country's historical background, large population of PWUD and cultural settings in order to succeed. Urgent changes in drug treatment policies and practices are needed by the Chinese governments at different levels, organizations and front-line practitioners if we are to see a reduction in the incidence and impact of harms related to substance use in China.

Ontogeny of Phase I Metabolism of Drugs

Capturing ontogeny of enzymes involved in phase I metabolism is crucial to improve prediction of dose-concentration and concentration-effect relationships throughout infancy and childhood. Once captured, these patterns can be integrated in semiphysiologically or physiology-based pharmacokinetic models to support predictions in specific pediatric settings or to support pediatric drug development. Although these translational efforts are crucial, isoenzyme-specific ontogeny-based models should also incorporate data on variability of maturational and nonmaturational covariates (eg, disease, treatment modalities, pharmacogenetics). Therefore, this review provides a summary of the ontogeny of phase I drug-metabolizing enzymes, indicating current knowledge gaps and recent progresses. Furthermore, we tried to illustrate that straightforward translation of isoenzyme-specific ontogeny to predictions does not allow full exploration of scenarios of potential variability related to maturational (non-age-related variability, other isoenzymes or transporters) or nonmaturational (disease, pharmacogenetics) covariates, and necessitates integration in a "systems" concept.

Approaches to Dose Finding in Neonates, Illustrating the Variability between Neonatal Drug Development Programs

Drug dosing in neonates should be based on integrated knowledge concerning the disease to be treated, the physiological characteristics of the neonate, and the pharmacokinetics (PK) and pharmacodynamics (PD) of a given drug. It is critically important that all sources of information be leveraged to optimize dose selection for neonates. Sources may include data from adult studies, pediatric studies, non-clinical (juvenile) animal models, in vitro studies, and in silico models. Depending on the drug development program, each of these modalities could be used to varying degrees and with varying levels of confidence to guide dosing. This paper aims to illustrate the variability between neonatal drug development programs for neonatal diseases that are similar to those seen in other populations (meropenem), neonatal diseases related but not similar to pediatric or adult populations (clopidogrel, thyroid hormone), and diseases unique to neonates (caffeine, surfactant). Extrapolation of efficacy from older children or adults to neonates is infrequently used. Even if a disease process is similar between neonates and children or adults, such as with anti-infectives, additional dosing and safety information will be necessary for labeling, recognizing that dosing in neonates is confounded by maturational PK in addition to body size.

Nursing Personnel in the Era of Personalized Healthcare in Clinical Practice

Personalized, stratified, or precision medicine (PM) introduces a new era in healthcare that tries to identify and predict optimum treatment outcomes for a patient or a cohort. It also introduces new scientific terminologies regarding therapeutic approaches and the need of their adoption from healthcare providers. Till today, evidence-based practice (EBP) was focusing on population averages and their variances among cohorts for clinical values that are essential for optimizing healthcare outcome. It can be stated that EBP and PM are complementary approaches for a modern healthcare system. Healthcare providers through EBP often see the forest (population averages) but miss the trees (individual patients), whereas utilization of PM may not see the forest for the trees. Nursing personnel (NP) play an important role in modern healthcare since they are consulting, educating, and providing care to patients whose needs often needs to be individualized (personalized nursing care, PNC). Based on the clinical issues earlier addressed from clinical pharmacology, EBP, and now encompassed in PM, this review tries to describe the challenges that NP have to face in order to meet the requisites of the new era in healthcare. It presents the demands that should be met for upgrading the provided education and expertise of NP toward an updated role in a modern healthcare system.

Identifying the Characteristics of Patients With Cervical Degenerative Disease for Surgical Treatment From 17-Year Real-World Data: Retrospective Study

Background

Real-world data (RWD) play important roles in evaluating treatment effectiveness in clinical research. In recent decades, with the development of more accurate diagnoses and better treatment options, inpatient surgery for cervical degenerative disease (CDD) has become increasingly more common, yet little is known about the variations in patient demographic characteristics associated with surgical treatment.

Objective

This study aimed to identify the characteristics of surgical patients with CDD using RWD collected from electronic medical records.

Methods

This study included 20,288 inpatient surgeries registered from January 1, 2000, to December 31, 2016, among patients aged 18 years or older, and demographic data (eg, age, sex, admission time, surgery type, treatment, discharge diagnosis, and discharge time) were collected at baseline. Regression modeling and time series analysis were conducted to analyze the trend in each variable (total number of inpatient surgeries, mean age at surgery, sex, and average length of stay). A P value <.01 was considered statistically significant. The RWD in this study were collected from the Orthopedic Department at Peking University Third Hospital, and the study was approved by the institutional review board.

Results

Over the last 17 years, the number of inpatient surgeries increased annually by an average of 11.13%, with some fluctuations. In total, 76.4% (15,496/20,288) of the surgeries were performed in patients with CDD aged 41 to 65 years, and there was no significant change in the mean age at surgery. More male patients were observed, and the proportions of male and female patients who underwent surgery were 64.7% (13,126/20,288) and 35.3% (7162/20,288), respectively. However, interestingly, the proportion of surgeries performed among female patients showed an increasing trend (P<.001), leading to a narrowing sex gap. The average length of stay for surgical treatment decreased from 21 days to 6 days and showed a steady decline from 2012 onward.

Conclusions

The RWD showed its capability in supporting clinical research. The mean age at surgery for CDD was consistent in the real-world population, the proportion of female patients increased, and the average length of stay decreased over time. These results may be valuable to guide resource allocation for the early prevention and diagnosis, as well as surgical treatment of CDD.

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models

In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL_pop) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CL_pop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CL_pop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CL_pop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CL_pop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CL_TV) at a relevant weight to evaluate the precision of CL predictions.

Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap

Despite the application of advanced statistical and pharmacometric approaches to pediatric trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more data from children by using real-world data from electronic health records, mobile applications, wearables, and social media. The large datasets collected with these approaches enable and may demand the use of artificial intelligence and machine learning to allow the data to be analyzed for decision making. Applications of this approach are presented, which include the prediction of future clinical complications, medical image analysis, identification of new pediatric end points and biomarkers, the prediction of treatment nonresponders, and the prediction of placebo-responders for trial enrichment. Finally, we discuss how to bring machine learning from science to pediatric clinical practice. We conclude that advantage should be taken of the current opportunities offered by innovations in data science and machine learning to close the pediatric evidence gap.

Rapidly maturing fentanyl clearance in preterm neonates

BACKGROUND

Fentanyl is frequently used off-label in preterm newborns. Due to very limited pharmacokinetic and pharmacodynamic data, fentanyl dosing is mostly based on bodyweight. This study describes the maturation of the pharmacokinetics in preterm neonates born before 32 weeks of gestation.

METHODS

442 plasma samples from 98 preterm neonates (median gestational age: 26.9 (range 23.9-31.9) weeks, postnatal age: 3 (range 0-68) days, bodyweight 1.00 (range 0.39-2.37) kg) were collected in an opportunistic trial and fentanyl plasma levels were determined. NONMEM V.7.3 was used to develop a population pharmacokinetic model and to perform simulations.

RESULTS

Fentanyl pharmacokinetics was best described by a two-compartment model. A pronounced non-linear influence of postnatal and gestational age on clearance was identified. Clearance (L/hour/kg) increased threefold, 1.3-fold and 1.01-fold in the first, second and third weeks of life, respectively. In addition, clearance (L/hour/kg) was 1.4-fold and 1.7-fold higher in case of a gestational age of 28 and 31 weeks, respectively, compared with 25 weeks. Volume of distribution changed linearly with bodyweight and was 8.7 L/kg. To achieve similar exposure across the entire population, a continuous infusion (µg/kg/hour) dose should be reduced by 50% and 25% in preterm neonates with a postnatal age of 0-4 days and 5-9 days in comparison to 10 days and older.

CONCLUSION

Because of low clearance, bodyweight-based dosages may result in fentanyl accumulation in neonates with the lowest postnatal and gestational ages which may require dose reduction. Together with additional information on the pharmacodynamics, the results of this study can be used to guide dosing.

Pharmacokinetic modelling and Bayesian estimation-assisted decision tools to optimize vancomycin dosage in neonates: only one piece of the puzzle

Introduction: Vancomycin is commonly administered to neonates, while observational data on therapeutic drug monitoring (TDM, trough levels) suggest that vancomycin exposure and dosage remain substandard. Area covered: Data on vancomycin pharmacokinetics (PK) and its covariates are abundant. Consequently, modeling is an obvious tool to improve targeted exposure, with a shift from TDM trough levels to area under the curve (AUC_24h) targets, as in adults. Continuous administration appeared as a practice to facilitate AUC_24h target attainment, while Bayesian model-supported targeting emerged as a novel tool. However, the AUC_24h/MIC (minimal inhibitory concentration) target itself should consider neonate-specific aspects (bloodstream infections, coagulase-negative staphylococci, protein binding, underexplored causes of variability, like assays, preparation and administration inaccuracies, or missing covariates). Expert opinion: To improve targeted exposure in neonates, initial vancomycin prescription should be based on 'a priori model-based individual dosing' using validated dosing regimens, followed by further tailoring by dosing optimization applying Bayesian estimation-assisted TDM. Future research should focus on the feasibility to integrate these tools (individualized dosing, Bayesian models) in clinical practice, and to perform PK/PD studies in the relevant animal models and human neonatal setting (coagulase-negative staphylococci, bloodstream infections).

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

Almost half of recent pediatric trials failed to achieve labeling indications, in large part because of inadequate study design. Therefore, innovative study methods are crucial to optimizing trial design while also reducing the potential harms inherent with drug investigation. Several methods exist to optimize the amount of pharmacokinetic data collected from the smallest possible volume and with the fewest number of procedures, including the use of opportunistic and sparse sampling, alternative and noninvasive matrices, and microvolume assays. In addition, large research networks using master protocols promote collaboration, reduce regulatory burden, and increase trial efficiency for both early- and late-phase trials. Large pragmatic trials that leverage electronic health records can capitalize on central management strategies to reduce costs, enroll patients with rare diseases on a large scale, and augment study generalizability. Further, trial efficiency and safety can be optimized through Bayesian adaptive techniques that permit planned protocol changes based on analyses of prior and accumulated data. In addition to these trial design features, advances in modeling and simulation have paved the way for systems-based and physiologically based models that individualize pediatric dosing recommendations and support drug approval. Last, given the low prevalence of many pediatric diseases, collecting deidentified genetic and clinical data on a large scale is a potentially transformative way to augment clinical pharmacology research in children.

Rational Use of Medicines in Neonates: Current Observations, Areas for Research and Perspectives

A focused reflection on rational medicines use in neonates is valuable and relevant, because indicators to assess rational medicines use are difficult to apply to neonates. Polypharmacy and exposure to antibiotics are common, while dosing regimens or clinical guidelines are only rarely supported by robust evidence in neonates. This is at least in part due to the extensive variability in pharmacokinetics and subsequent effects of medicines in neonates. Medicines utilization research informs us on trends, on between unit variability and on the impact of guideline implementation. We illustrate these aspects using data on drugs for gastroesophageal reflux, analgesics or anti-epileptic drugs. Areas for additional research are drug-related exposure during breastfeeding (exposure prediction) and how to assess safety (tools to assess seriousness, causality, and severity tailored to neonates) since both efficacy and safety determine rational drug use. To further improve rational medicines use, we need more data and tools to assess efficacy and safety in neonates. Moreover, we should facilitate access to such data, and explore strategies for effective implementation. This is because prescription practices are not only rational decisions, but also have psychosocial aspects that may guide clinicians to irrational practices, in part influenced by the psychosocial characteristics of this population.

Buprenorphine and pain treatment in pediatric patients: an update

Introduction

The usual management of moderate to severe pain is based on the use of opioids. Buprenorphine (BPN) is an opioid with an analgesic potency 50 times greater than that of morphine. It is widely used in various pain models and has demonstrated efficacy and safety in adult patients; however, there are insufficient clinical trials in pediatric populations.

Purpose

The aim of this study was to perform an updated meta-analysis on the implementation of BPN in the treatment of pain in the pediatric population.

Methods

A bibliographic search was carried out in different biomedical databases to identify scientific papers and clinical trials with evidence of BPN use in children and adolescents.

Results

A total of 89 articles were found, of which 66 were selected. Analysis of these items revealed additional sources, and the final review included a total of 112 publications.

Conclusion

Few studies were found regarding the efficacy and safety of BPN use in children. In recent years, the use of this drug in the pediatric population has become widespread, so it is imperative to perform clinical trials and pharmacological and pharmacovigilance studies, which will allow researchers to develop dosage schemes based on the evidence and minimize the risk of adverse effects.

Obesity and drug pharmacology: a review of the influence of obesity on pharmacokinetic and pharmacodynamic parameters

INTRODUCTION

The rising prevalence of obesity confronts clinicians with dosing problems in the (extreme) overweight population. Obesity has a great impact on key organs that play a role in the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs, however the ultimate impact of these changes on how to adapt the dose may not always be known. Areas covered: In this review, physiological changes associated with obesity are discussed. An overview is provided on the alterations in absorption, distribution, drug metabolism and clearance in (morbid) obesity focusing on general principles that can be extracted from pharmacokinetic studies. Also, relevant pharmacodynamic considerations in obesity are discussed. Expert opinion: Over the last two decades, increased knowledge is generated on PK and PD in obesity. Future research should focus on filling in the knowledge gaps that remain, especially in connecting obesity-related physiological changes with changes in PK and/or PD and vice versa. Ultimately, this knowledge can be used to develop physiologically based PK and PD models on the basis of quantitative systems pharmacology principles. Moreover, efforts should focus on thorough prospective evaluation of developed model-based doses with subsequent implementation of these dosing recommendations in clinical practice.