Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians.

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

Applying Neural ODEs to Derive a Mechanism-Based Model for Characterizing Maturation-Related Serum Creatinine Dynamics in Preterm Newborns.

Serum creatinine in neonates follows complex dynamics due to maturation processes, most pronounced in the first few weeks of life. The development of a mechanism-based model describing complex dynamics requires high expertise in pharmacometric (PMX) modeling and substantial model development time. A recently published machine learning (ML) approach of low-dimensional neural ordinary differential equations (NODEs) is capable of modeling such data from newborns automatically. However, this efficient data-driven approach in itself does not result in a clinically interpretable model. In this work, an approach to deriving an interpretable model with reasonable PMX-type functions is presented. This "translation" was applied to derive a PMX model for serum creatinine in neonates considering maturation processes and covariates. The developed model was compared to a previously published mechanism-based PMX model whereas both models had similar mechanistic structures. The developed model was then utilized to simulate serum creatinine concentrations in the first few weeks of life considering different covariate values for gestational age and birth weight. The reference serum creatinine values derived from these simulations are consistent with observed serum creatinine values and previously published reference values. Thus, the presented NODE-based ML approach to model complex serum creatinine dynamics in newborns and derive interpretable, mathematical-statistical components similar to those in a conventional PMX model demonstrates a novel, viable approach to facilitate the modeling of complex dynamics in clinical settings and pediatric drug development.

Determining the exposure of maternal medicines through breastfeeding: the UmbrelLACT study protocol-a contribution from the ConcePTION project.

INTRODUCTION: Breastfeeding is beneficial for the health of the mother and child. However, at least 50% of postpartum women need pharmacotherapy, and this number is rising due to the increasing prevalence of chronic diseases and pregnancies at a later age. Making informed decisions on medicine use while breastfeeding is often challenging, considering the extensive information gap on medicine exposure and safety during lactation. This can result in the unnecessary cessation of breastfeeding, the avoidance of pharmacotherapy or the off-label use of medicines. The UmbrelLACT study aims to collect data on human milk transfer of maternal medicines, child exposure and general health outcomes. Additionally, the predictive performance of lactation and paediatric physiologically based pharmacokinetic (PBPK) models, a promising tool to predict medicine exposure in special populations, will be evaluated. METHODS AND ANALYSIS: Each year, we expect to recruit 5-15 breastfeeding mothers using pharmacotherapy via the University Hospitals Leuven, the BELpREG project (pregnancy registry in Belgium) or external health facilities. Each request and compound will be evaluated on relevance (ie, added value to available scientific evidence) and feasibility (including access to analytical assays). Participants will be requested to complete at least one questionnaire on maternal and child's general health and collect human milk samples over 24 hours. Optionally, two maternal and one child's blood samples can be collected. The maternal medicine concentration in human milk will be determined along with the estimation of the medicine intake (eg, daily infant dose and relative infant dose) and systemic exposure of the breastfed child. The predictive performance of PBPK models will be assessed by comparing the observed concentrations in human milk and plasma to the PBPK predictions. ETHICS AND DISSEMINATION: This study has been approved by the Ethics Committee Research UZ/KU Leuven (internal study number S67204). Results will be published in peer-reviewed journals and presented at (inter)national scientific meetings. TRIAL REGISTRATION NUMBER: NCT06042803.

Physiologically Based Pharmacokinetic Modeling in Pregnancy, during Lactation and in Neonates: Achievements, Challenges and Future Directions.

Obstetric subjects represent a special population in pharmacology [...].

When will the Glomerular Filtration Rate in Former Preterm Neonates Catch up with Their Term Peers?

AIMS: Whether and when glomerular filtration rate (GFR) in preterms catches up with term peers is unknown. This study aims to develop a GFR maturation model for (pre)term-born individuals from birth to 18 years of age. Secondarily, the function is applied to data of different renally excreted drugs. METHODS: We combined published inulin clearance values and serum creatinine (Scr) concentrations in (pre)term born individuals throughout childhood. Inulin clearance was assumed to be equal to GFR, and Scr to reflect creatinine synthesis rate/GFR. We developed a GFR function consisting of GFRbirth (GFR at birth), and an Emax model dependent on PNA (with GFRmax, PNA50 (PNA at which half of GFR max is reached) and Hill coefficient). The final GFR model was applied to predict gentamicin, tobramycin and vancomycin concentrations. RESULT: In the GFR model, GFRbirth varied with birthweight linearly while in the PNA-based Emax equation, GA was the best covariate for PNA50, and current weight for GFRmax. The final model showed that for a child born at 26 weeks GA, absolute GFR is 18%, 63%, 80%, 92% and 96% of the GFR of a child born at 40 weeks GA at 1 month, 6 months, 1 year, 3 years and 12 years, respectively. PopPK models with the GFR maturation equations predicted concentrations of renally cleared antibiotics across (pre)term-born neonates until 18 years well. CONCLUSIONS: GFR of preterm individuals catches up with term peers at around three years of age, implying reduced dosages of renally cleared drugs should be considered below this age.

Publication Recommendations to Report Laboratory Data of Neonates - a Modified Delphi Approach.

BACKGROUND: Clinical and analytical information on laboratory data of neonates in scientific publications is sparse and incomplete. Furthermore, interpreting neonatal laboratory data can be complex due to their time-dependent and developmental physiology, and paucity of well-established age-appropriate reference ranges for neonates. This study aims to develop publication recommendations to report laboratory data of neonates to enhance the quality of these data in research and clinical care. METHODS: A modified Delphi approach was used to develop recommendations in cooperation with the International Neonatal Consortium. A Core Group, including different stakeholders, was responsible for developing the recommendations, in collaboration with a Reflection Group, responsible for providing additional input. RESULTS: The recommendations were classified into three categories: 'Clinical Characteristics', 'Bio-analytical Information' and 'Data-analytical Information'. These were each divided into 'Core Data' (always to be reported) and 'Supplemental Considerations' (to be reported when considered relevant to the study). CONCLUSION: Our recommendations provide guidance on standardization of neonatal laboratory data in publications. This will enhance the comparison, replication, and application of study results in research initiatives and clinical practice. Furthermore, these recommendations also serve as foundational work to develop reference ranges for neonatal laboratory values by standardizing the quality of information needed for such efforts. IMPACT: Standardized reporting of neonatal laboratory data in scientific publications will enhance the comparison, replication, and application of study results in research initiatives and clinical practice, as well as improve reporting to regulatory agencies. To integrate multistakeholder perspectives, a modified Delphi approach was used to develop publication recommendations which strengthens the applicability of the recommendations. Implementation of standardization will likely improve the overall quality of neonatal clinical research and neonatal healthcare. In addition, these recommendations are foundational to develop reference ranges for neonatal laboratory values by standardizing the quality of information needed for such efforts.

Pharmacovigilance of nephrotoxic drugs in neonates: the Pottel method for acute kidney injury detection in ELBW neonates.

BACKGROUND: Extremely low birth weight (ELBW) neonates (birth weight ≤ 1000 g) are at high risk to develop drug-induced acute kidney injury (AKI). However, we lack a pragmatic detection tool to capture their time-dependent (patho)physiologic serum creatinine (Scr) patterns. Pottel et al. suggested rescaling Scr by dividing Scr with the mean Scr value of the age- and sex-specific reference population. We explored if this Pottel method can detect drug-related nephrotoxicity in ELBW neonates. METHODS: A previously reported dataset on Scr changes in ELBW neonates exposed to ibuprofen, amikacin, or vancomycin was updated to calculate Pottel scores for every available Scr value in the first 28 postnatal days. We hereby used previously published postnatal age-specific 50th centile values in an ELBW population. Linear mixed models were applied, analyzing Pottel scores as response variable and continuous time (day), drug exposure, and interaction thereof in the explanatory model. RESULTS: Serum creatinine (n = 3231) observations in 201 ELBW neonates were collected. A statistically significant rise of Pottel scores was observed with ibuprofen starting from postnatal day 4. In addition, a cumulative effect of treatment with mean Pottel scores on day 0 of 1.020 and on day 3 during treatment of 1.106 (95% CI 1.068-1.145, p < 0.001) was observed, corrected for effect of antibiotics. Antibiotic administrations showed a small but statistically significant difference up to postnatal day 5. CONCLUSIONS: As rescaled Scr biomarker, the Pottel method showed a clear association with ibuprofen-exposed ELBW neonates, suggesting its applicability as a pragmatic bedside alternative tool to assess nephrotoxicity.

Evaluating the relationship between the proportion of X-chromosome deletions and clinical manifestations in children with turner syndrome.

Purpose: Analyze the relationship between changes in the proportion of X-chromosome deletions and clinical manifestations in children with Turner syndrome (TS). Methods: X-chromosome number abnormalities in 8,635 children with growth retardation were identified using fluorescence in situ hybridization (FISH). Meanwhile, the relationship between the proportion of X-chromosome deletions and the clinical manifestations of TS, such as face and body phenotype, cardiovascular, renal, and other comorbidities in children with TS was analyzed. Results: A total of 389 children had X-chromosome number abnormalities, with an average age at diagnosis of 9.2 years. There was a significant increase in diagnoses around the ages of 3 and 7 years and highest number of diagnoses at 10 years of age. 130 with XO (complete loss of an X-chromosome), 205 with XO/XX, 8 with XO/XXX, 23 with XO/XX/XXX, 19 with XO/XY, and 4 with XO/XY/XYY. Body and facial phenotypes increased with higher mosaicism proportions, with a relatively high correlation shown with Pearson correlation analysis (r = 0.26, p = 1.7e-06). The incidence of congenital heart malformations was 25.56%, mainly involving a bicuspid aortic valve, and were more common in patients who had complete loss of an X-chromosome. However, this relationship was not present for renal disease (p = 0.26), central nervous system, thyroid, or liver disease. Conclusion: The mosaicism (XO/XX) is the most common karyotype of TS in screened cases. The phenotypes in children with TS may increase with the proportion of X-chromosome deletions, but the renal disease and comorbidities did not show the same characteristics.

Web Survey of Turkish Pharmacy Students Comparing First and Fifth Years' Antidepressant Awareness and Stigmatizing Attitudes Regarding Depression and Anxiety.

The prevalence of depression and anxiety has increased day by day. Prejudice, self-stigma, and public stigma, on the other hand, continue to prevent patients from seeking adequate treatment, particularly in traditional communities. In this web-based, cross-sectional study, both the presence of depression and anxiety, and the knowledge, attitude, and awareness of first- and fifth (final)-year pharmacy students were examined via an online survey. The aim was to demonstrate the potential impact of public information and five years of pharmacy school on knowledge, attitude, and awareness. Our study population consisted of first- and fifth-year pharmacy students enrolled in one faculty of pharmacy during the spring semester of 2022-2023. The Beck Depression Inventory and Beck Anxiety Scale were utilized to measure the presence of depression and anxiety, while the Depression and Antidepressant Awareness and Knowledge Scale (DAKAS) was applied to assess their knowledge, attitude, and awareness. Fifth-year participants (n = 101) exhibited noticeably fewer stigmatizing attitudes than first-year participants (n = 104) (p < 0.05). There was no statistically significant difference between the mean Beck Depression Inventory and Beck Anxiety scores in first- and fifth-year pharmacy students. Being in the fifth class (OR: 3.690; p = 0.025), being of female gender (OR: 4.653; p < 0.001), and having a relationship with someone who took a psychotropic (OR: 3.060; p = 0.008) were associated with a lower overall stigma score by multiple linear regression analysis. The students' awareness of antidepressants and familiarity with mental health issues at the end of their pharmacy education were higher and stigmatization behavior was lower than in first-year students. The positive attitudes at the end of their training towards depression will reduce the likelihood of future pharmacists' patients from being exposed to stigmatization, prevents the formation of an additional stress factor, and likely will improve pharmacy practices.

Agreement Between a Colorimetric Assay and Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry for Quantifying Paracetamol Plasma Concentrations.

Special populations, like geriatric patients, experience altered paracetamol pharmacokinetics (PK), complicating pain management. More PK research is essential to optimize paracetamol (acetaminophen) dosing. Yet, the reference method ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) is not readily available. Therefore, we aimed to evaluate the agreement between UPLC-MS/MS and the more accessible colorimetric Roche acetaminophen (ACETA) assay in quantifying paracetamol plasma concentrations, to facilitate PK studies and therapeutic drug monitoring for pain management. Patient data and plasma samples were obtained from a prospective study including geriatric patients admitted to the geriatric wards. ACETA and UPLC-MS/MS assays were performed in two separate laboratories. Bland-Altman plot and Passing-Bablok regression were used to assess agreement. Accuracy was evaluated using the McNemar test for a threshold value of 10 mg/L. Population PK modeling was employed to bridge PK data obtained from both methods (NONMEM 7.5). A total of 242 plasma sample pairs were available from 40 geriatric patients (age range, 80-95 years). Paracetamol plasma concentrations from ACETA (median 9.8 [interquartile range 6.1-14.4] mg/L) and UPLC-MS/MS (9.5 [6.2-14.8] mg/L) did not differ significantly (P > 0.05). No significant proportional nor additive bias was observed between both assay methods. The classification accuracy (at threshold 10 mg/L) was 85% (P = 0.414). The conversion factor between ACETA and UPLC-MS/MS was estimated at 1.06 (relative standard error 5%), yet with a 13.4% (relative standard error 23%) interindividual variability. ACETA assay showed no systematic bias in comparison with the UPLC-MS/MS assay in determining paracetamol exposure in geriatric blood samples despite the imprecision.

Applied pharmacokinetics to improve pharmacotherapy in neonatal and paediatric intensive care units: focus on correct dose selection.

Drug dosing and exposure throughout childhood are constantly affected by maturational changes like weight, age or body surface area. In neonatal and paediatric intensive care units (NICU and PICU, respectively), drug dosing and exposure are further impacted by non-maturational changes. These changes are related to factors such as sepsis, cardiac failure, acute kidney injury, extracorporeal circuits or drug-drug interactions (DDIs) resulting from polypharmacy.This potentially complex situation may alter drug pharmacokinetics to result in greater-than-usual intrapatient and interpatient drug exposure variability. These effects may call for individual dosage adjustments. Dosage adjustments may apply to both loading doses or maintenance doses, which should be used as appropriate, depending on the specific characteristics of a given drug. Phenobarbital and vancomycin dosing are hereby used as illustrations.To optimise dose selection in NICU/PICU settings, we suggest to consider therapeutic drug monitoring integrated in model-informed precision dosing, and to familiarise oneself with existing paediatric drug formularies as well as DDI databases/search engines. Paediatric clinical pharmacologists and pharmacists can hereby guide clinicians with no prior experience on how to properly apply these data sources to day-to-day practice in individual patients or specific subpopulations of NICU or PICU patients.

Global cross-sectional survey on neonatal pharmacologic sedation and analgesia practices and pain assessment tools: impact of the sociodemographic index (SDI).

BACKGROUND: There is variability in the use of sedatives and analgesics in neonatal intensive care units (NICUs). We aimed to investigate the use of analgesics and sedatives and the management of neonatal pain and distress. METHODS: This was a global, prospective, cross-sectional study. A survey was distributed May-November 2022. The primary outcome of this research was to compare results between countries depending on their socio-sanitary level using the sociodemographic index (SDI). We organized results based on geographical location. RESULTS: The survey collected 1304 responses, but we analyzed 924 responses after database cleaning. Responses from 98 different countries were analyzed. More than 60% of NICUs reported having an analgosedation guideline, and one-third of respondents used neonatal pain scales in more than 80% of neonates. We found differences in the management of sedation and analgesia between NICUs on different continents, but especially between countries with different SDIs. Countries with a higher SDI had greater availability of and adherence to analgosedation guidelines, as well as higher rates of analgosedation for painful or distressing procedures. Countries with different SDIs reported differences in analgosedation for neonatal intubation, invasive ventilation, and therapeutic hypothermia, among others. CONCLUSIONS: Socio-economic status of countries impacts on neonatal analgosedation management. IMPACT: There is significant variability in the pain management practices in neonates. There is a lack of knowledge related to how neonatal pain management practices differ between regions. Sociodemographic index is a key factor associated with differences in neonatal pain management practices across global regions.

OSTEO18, a novel urinary proteomic signature, associated with osteoporosis in heart transplant recipients.

Background: Immunosuppressive treatment in heart transplant (HTx) recipient causes osteoporosis. The urinary proteomic profile (UPP) includes peptide fragments derived from the bone extracellular matrix. Study aims were to develop and validate a multidimensional UPP biomarker for osteoporosis in HTx patients from single sequenced urinary peptides identifying the parent proteins. Methods: A single-center HTx cohort was analyzed. Urine samples were measured by capillary electrophoresis coupled with mass spectrometry. Cases with osteoporosis and matching controls were randomly selected from all available 389 patients. In derivation case-control dataset, 1576 sequenced peptides detectable in ≥30 % of patients. Applying statistical analysis on these, an 18-peptide multidimensional osteoporosis UPP biomarker (OSTEO18) was generated by support vector modeling. The 2 replication datasets included 118 and 94 patients. For further validation, the whole cohort was analyzed. Statistical methods included logistic regression and receiver operating characteristic curve (ROC) analysis. Results: In derivation dataset, the AUC, sensitivity and specificity of OSTEO18 were 0.83 (95 % CI: 0.76-0.90), 74.3 % and 87.1 %, respectively. In replication datasets, results were confirmatory. In the whole cohort (154 osteoporotic patients [39.6 %]), the ORs for osteoporosis increased (p < 0.0001) across OSTEO18 quartiles from 0.39 (95 % CI: 0.25-0.61) to 3.14 (2.08-4.75). With full adjustment for known osteoporosis risk factors, OSTEO18 improved AUC from 0.708 to 0.786 (p = 0.0003) for OSTEO18 categorized (optimized threshold: 0.095) and to 0.784 (p = 0.0004) for OSTEO18 as continuously distributed classifier. Conclusion: OSTEO18 is a clinically meaningful novel biomarker indicative of osteoporosis in HTx recipients and is being certified as in-vitro diagnostic.

Interdisciplinary Collaboration on Real World Data to Close the Knowledge Gap: A Reflection on "De Sutter et al. Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling".

This commentary further reflects on the paper of De Sutter et al. on predicting volume of distribution in neonates, and the performance of physiologically based pharmacokinetic models We hereby stressed the add on value to collaborate on real world data to further close this knowledge gap. We illustrated this by weight distribution characteristics in breastfed (physiology) and in asphyxiated (pathophysiology), with additional reflection on their kidney and liver function.

Detailed statistical analysis plan for ALBINO: effect of Allopurinol in addition to hypothermia for hypoxic-ischemic Brain Injury on Neurocognitive Outcome - a blinded randomized placebo-controlled parallel group multicenter trial for superiority (phase III).

BACKGROUND: Despite therapeutic hypothermia (TH) and neonatal intensive care, 45-50% of children affected by moderate-to-severe neonatal hypoxic-ischemic encephalopathy (HIE) die or suffer from long-term neurodevelopmental impairment. Additional neuroprotective therapies are sought, besides TH, to further improve the outcome of affected infants. Allopurinol - a xanthine oxidase inhibitor - reduced the production of oxygen radicals and subsequent brain damage in pre-clinical and preliminary human studies of cerebral ischemia and reperfusion, if administered before or early after the insult. This ALBINO trial aims to evaluate the efficacy and safety of allopurinol administered immediately after birth to (near-)term infants with early signs of HIE. METHODS/DESIGN: The ALBINO trial is an investigator-initiated, randomized, placebo-controlled, double-blinded, multi-national parallel group comparison for superiority investigating the effect of allopurinol in (near-)term infants with neonatal HIE. Primary endpoint is long-term outcome determined as survival with neurodevelopmental impairment versus death versus non-impaired survival at 2 years. RESULTS: The primary analysis with three mutually exclusive responses (healthy, death, composite outcome for impairment) will be on the intention-to-treat (ITT) population by a generalized logits model according to Bishop, Fienberg, Holland (Bishop YF, Discrete Multivariate Analysis: Therory and Practice, 1975) and ."will be stratified for the two treatment groups. DISCUSSION: The statistical analysis for the ALBINO study was defined in detail in the study protocol and implemented in this statistical analysis plan published prior to any data analysis. This is in accordance with the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice guidelines. TRIAL REGISTRATION: ClinicalTrials.gov NCT03162653. Registered on 22 May 2017.