New model of glucose-insulin regulation characterizes effects of physical activity and facilitates personalized treatment evaluation in children and adults with type 1 diabetes.

Accurate treatment adjustment to physical activity (PA) remains a challenging problem in type 1 diabetes (T1D) management. Exercise-driven effects on glucose metabolism depend strongly on duration and intensity of the activity, and are highly variable between patients. In-silico evaluation can support the development of improved treatment strategies, and can facilitate personalized treatment optimization. This requires models of the glucose-insulin system that capture relevant exercise-related processes. We developed a model of glucose-insulin regulation that describes changes in glucose metabolism for aerobic moderate- to high-intensity PA of short and prolonged duration. In particular, we incorporated the insulin-independent increase in glucose uptake and production, including glycogen depletion, and the prolonged rise in insulin sensitivity. The model further includes meal absorption and insulin kinetics, allowing simulation of everyday scenarios. The model accurately predicts glucose dynamics for varying PA scenarios in a range of independent validation data sets, and full-day simulations with PA of different timing, duration and intensity agree with clinical observations. We personalized the model on data from a multi-day free-living study of children with T1D by adjusting a small number of model parameters to each child. To assess the use of the personalized models for individual treatment evaluation, we compared subject-specific treatment options for PA management in replay simulations of the recorded data with altered meal, insulin and PA inputs.

Pharmacokinetics of oral spironolactone in infants up to 2 years of age.

PURPOSE: Spironolactone is a potassium sparing diuretic used for decades. Until now, pharmacokinetic (PK) studies of spironolactone have not been conducted in infants and therefore pediatric dosing is based on expert opinion. We aimed to describe the PK profiles of spironolactone and its main metabolites (7alpha-thiomethylspironolactone (TMS) and canrenone (CAN)) in infants up to two years of age. METHODS: The PK of spironolactone and its main metabolites were evaluated following an oral administration of spironolactone (1 mg/kg/dose) to pediatric patients with chronic heart failure, ascites, and/or oedema. The plasma concentration of spironolactone and metabolites (TMS and CAN) was determined using an ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Based on rich sampling PK data, the estimation of population PK parameters was performed using nonlinear mixed-effects modelling software Monolix 2018R2. RESULTS: A total of 150 spironolactone, 158 TMS, and 158 CAN concentrations from 23 patients (ages: 3 days-21 months; median weight 4.3 kg (2.2-12.6)) were available for PK analysis. A one-compartment model for spironolactone, TMS, and CAN best fitted the data. The median (range) of individual estimated apparent clearance values were 47.7 (11.9-138.1) L/h for spironolactone, 9.7 (1.5-66.9) L/h for TMS, and 1.0 (0.2-5.9) L/h for CAN. The disposition of spironolactone and metabolites was mainly affected by size of the patient: body weight explained 22% of inter-individual variability of spironolactone clearance. None of the undesirable effects of spironolactone was documented during the study period. CONCLUSION: The pharmacokinetics of spironolactone and its metabolites was highly variable between patients below 2 years of age. Body weight explained a significant part of this variability; this highlights the need to take it into account for dosing prescription in this population. (Clinical trial Registration Number 2013-001189-40).

Low-dimensional neural ODEs and their application in pharmacokinetics.

Machine Learning (ML) is a fast-evolving field, integrated in many of today's scientific disciplines. With the recent development of neural ordinary differential equations (NODEs), ML provides a new tool to model dynamical systems in the field of pharmacology and pharmacometrics, such as pharmacokinetics (PK) or pharmacodynamics. The novel and conceptionally different approach of NODEs compared to classical PK modeling creates challenges but also provides opportunities for its application. In this manuscript, we introduce the functionality of NODEs and develop specific low-dimensional NODE structures based on PK principles. We discuss two challenges of NODEs, overfitting and extrapolation to unseen data, and provide practical solutions to these problems. We illustrate concept and application of our proposed low-dimensional NODE approach with several PK modeling examples, including multi-compartmental, target-mediated drug disposition, and delayed absorption behavior. In all investigated scenarios, the NODEs were able to describe the data well and simulate data for new subjects within the observed dosing range. Finally, we briefly demonstrate how NODEs can be combined with mechanistic models. This research work enhances understanding of how NODEs can be applied in PK analyses and illustrates the potential for NODEs in the field of pharmacology and pharmacometrics.

Computing optimal drug dosing with OptiDose: implementation in NONMEM.

Determining a drug dosing recommendation with a PKPD model can be a laborious and complex task. Recently, an optimal dosing algorithm (OptiDose) was developed to compute the optimal doses for any pharmacometrics/PKPD model for a given dosing scenario. In the present work, we reformulate the underlying optimal control problem and elaborate how to solve it with standard commands in the software NONMEM. To demonstrate the potential of the OptiDose implementation in NONMEM, four relevant but substantially different optimal dosing tasks are solved. In addition, the impact of different dosing scenarios as well as the choice of the therapeutic goal on the computed optimal doses are discussed.

Therapeutic Drug Monitoring of Orally Administered Letermovir Prophylaxis in Allogeneic Hematopoietic Stem Cell Transplant Recipients.

With balanced safety-efficacy profile, letermovir anti-cytomegalovirus (CMV) prophylaxis is used in hematopoietic stem cell transplant recipients (HSCTR). We assessed feasibility and usefulness of letermovir therapeutic drug monitoring (TDM) in HSCTR. We performed a prospective observational study on letermovir-TDM including 40 consecutive adult CMV-seropositive allogeneic-HSCTR who received orally (PO) administered letermovir. Minimal blood concentrations of letermovir (Ctrough) were measured on days 3 and 7 postletermovir initiation and weekly thereafter. Letermovir-Ctrough remained stable during the first 70 days post-HSCT at a median of 286 µg/L (interquartile range, 131 to 591 µg/L), with large interpatient/intrapatient variability. No associations between breakthrough clinically significant CMV infection or detectable CMV DNAemia and letermovir-Ctrough were observed. Patients with letermovir-associated adverse events had higher letermovir-Ctrough than patients without (400 versus 266 µg/L, P = 0.02). Letermovir-Ctrough was similar in patients with or without gastrointestinal symptoms (280 versus 300 µg/L, P = 0.49). Acute grade ≥2 GvHD was associated with higher letermovir-Ctrough (479 versus 248 µg/L, P = 0.001), including gastrointestinal GvHD (499 versus 263 µg/L, P = 0.004). Concomitantly administered posaconazole and cyclosporine were associated with higher letermovir-Ctrough (707 versus 259 µg/L, P < 0.001 and 437 versus 248 µg/L, P = 0.01, respectively). In multivariable analysis, both posaconazole (odds ratio [OR], 4.9; 95% confidence interval [CI], 2.4 to 9.7; P < 0.0001) and cyclosporine-adjusted letermovir dose at 240 mg daily (OR, 3.5; 95% CI, 1.4 to 9.0; P = 0.01) were independently associated with higher letermovir-Ctrough. In conclusion, administration of PO letermovir led to measurable and relatively stable letermovir-Ctrough, without noticeable associations with clinical efficacy. Letermovir exposure was not affected by gastrointestinal symptoms, but with posaconazole and cyclosporine administration. Associations between letermovir and concomitantly administered agents and adverse events warrant additional clinical studies.

Pharmacokinetic modelling and simulation to optimize albendazole dosing in hookworm- or Trichuris trichiura-infected infants to adults.

BACKGROUND: Albendazole is the most commonly used drug in preventive chemotherapy programmes against soil-transmitted helminth (STH) infections, with the standard dose of 400 mg resulting in suboptimal clinical outcomes. Population pharmacokinetic (PK) models that could inform dosing strategies are not yet available. METHODS: A population pharmacokinetic model was developed based on micro-blood samples collected from 252 patients aged 2 to 65 years, infected with either hookworm or Trichuris trichiura and treated with albendazole doses ranging from of 200 to 800 mg. An exposure-response analysis was performed relating albendazole and its two metabolites to cure rates and egg reduction rates (ERR). Finally, model-based simulations were conducted to determine equivalent exposure coverage in infants to adults. RESULTS: A population PK model, with one distribution compartment for each compound and one peripheral compartment, following oral administration with a lag time, assuming first-order absorption and linear elimination, best described the concentration-time profiles. Clearance and volume parameters were scaled to body size (weight for albendazole and height for albendazole sulfoxide and sulfone). Dose proportionality was observed for the active metabolite, albendazole sulfoxide, but only in hookworm-infected individuals, with increasing exposure resulting in increased ERR. Exposure of sulfoxide was lowest in the tallest individuals. CONCLUSIONS: Pharmacometric simulations indicate that doses up to 800 mg could further increase albendazole efficacy in hookworm-infected adults, whereas the standard dose of 400 mg is sufficient in the youngest age cohorts. In the absence of evidence-based arguments for adjusting albendazole doses in T. trichiura-infected individuals, the search for new treatment options is further emphasized.

Dosing strategies of imipenem in neonates based on pharmacometric modelling and simulation.

OBJECTIVES: Imipenem is a broad-spectrum antibacterial agent used in critically ill neonates after failure of first-line treatments. Few studies have described imipenem disposition in this population. The objectives of our study were: (i) to characterize imipenem population pharmacokinetics (PK) in a cohort of neonates; and (ii) to conduct model-based simulations to evaluate the performance of six different dosing regimens aiming at optimizing PK target attainment. METHODS: A total of 173 plasma samples from 82 neonates were collected over 15 years at the Lausanne University Hospital, Switzerland. The majority of study subjects were preterm neonates with a median gestational age (GA) of 27 weeks (range: 24-41), a postnatal age (PNA) of 21 days (2-153) and a body weight (BW) of 1.16 kg (0.5-4.1). PK data were analysed using non-linear mixed-effect modelling (NONMEM). RESULTS: A one-compartment model best characterized imipenem disposition. Population PK parameters estimates of CL and volume of distribution were 0.21 L/h and 0.73 L, with an interpatient variability (CV%) of 20.1% on CL in a representative neonate (GA 27 weeks, PNA 21 days, BW 1.16 kg, serum creatinine, SCr 46.6 µmol/L). GA and PNA exhibited the greatest impact on PK parameters, followed by SCr. These covariates explained 36% and 15% of interindividual variability in CL, respectively.Simulated regimens using a dose of 20-25 mg/kg every 6-12 h according to postnatal age led to the highest PTA (T>MIC over 100% of time). CONCLUSIONS: Dosing adjustment according to BW, GA and PNA optimizes imipenem exposure in neonates.

Pharmacometric Analysis of Tribendimidine Monotherapy and Combination Therapies To Achieve High Cure Rates in Patients with Hookworm Infections.

In the treatment of hookworm infections, pharmacotherapy has been only moderately successful and drug resistance is a threat. Therefore, novel treatment options including combination therapies should be considered, in which tribendimidine could play a role. Our aims were to (i) characterize the pharmacokinetics of tribendimidine's metabolites in adolescents receiving tribendimidine monotherapy or in combination with ivermectin or oxantel pamoate, (ii) evaluate possible drug-drug interactions (DDI), (iii) link exposure to response, and (iv) identify a treatment strategy associated with high efficacy, i.e., >90% cure rates (CRs), utilizing model-based simulations. A population pharmacokinetic model was developed for tribendimidine's primary and secondary metabolites, dADT and adADT, in 54 hookworm-positive adolescents, with combination therapy evaluated as a possible covariate. Subsequently, an exposure-response analysis was performed utilizing CRs as response markers. Simulations were performed to identify a treatment strategy to achieve >90% CRs. A two-compartmental model best described metabolite disposition. No pharmacokinetic DDI was identified with ivermectin or oxantel pamoate. All participants receiving tribendimidine plus ivermectin were cured. For the monotherapy arm and the arm including the combination with oxantel pamoate, Emax models adequately described the correlation between dADT exposure and probability of being cured, with required exposures to achieve 50% of maximum effect of 39.6 and 15.6 nmol/ml·h, respectively. Based on our simulations, an unrealistically high monotherapy tribendimidine dose would be necessary to achieve CRs of >90%, while combination therapy with ivermectin would meet this desired target product profile. Further clinical studies should be launched to develop this combination for the treatment of hookworm and other helminth infections.

Population Pharmacokinetics and Exposure-Response Analysis of Tribendimidine To Improve Treatment for Children with Hookworm Infection.

Tribendimidine has been successful in treating hookworm infections and may serve as an alternative to albendazole should resistance arise. Our aims were to (i) characterize the pharmacokinetics (PK) of tribendimidine's primary metabolite, deacetylated amidantel (dADT), and secondary metabolite, acetylated derivative of amidantel (adADT), in school-aged children and adolescents, (ii) link exposure to efficacy against hookworm, and (iii) evaluate whether tribendimidine pharmacotherapy in children could be further improved. First, a population PK model was developed based on dried-blood-spot samples collected from 155 school-aged children and adolescents with hookworm infections, following tribendimidine doses ranging from 100 to 400 mg. Second, an exposure-response analysis was conducted to link the active metabolite dADT to cure rates (CRs) and egg reduction rates (ERRs). Third, simulations were performed to identify a treatment strategy associated with >90% CRs. A two-compartmental model with transit compartments describing observed delay in absorption adequately described PK data of dADT and adADT. Allometric scaling was included to account for growth and development. The absorption rate was 56% lower with 200-mg tablets than with 50-mg tablets, while the extent of absorption remained unaffected. The identified Emax models linking dADT exposure to ERRs and CRs showed shallow curves, as increasing exposure led to marginal efficacy increase. Combination therapy should be considered, as a 12-fold-higher dose would be needed to achieve 95% ERRs and CRs >90% with tribendimidine alone. Further studies are warranted to evaluate safety of higher tribendimidine doses and combination therapies with other anthelmintic agents to improve treatment strategy for children with hookworm infection.

Identifying key predictors of mortality in young patients on chronic haemodialysis-a machine learning approach.

BACKGROUND: The mortality risk remains significant in paediatric and adult patients on chronic haemodialysis (HD) treatment. We aimed to identify factors associated with mortality in patients who started HD as children and continued HD as adults. METHODS: The data originated from a cohort of patients <30 years of age who started HD in childhood (≤19 years) on thrice-weekly HD in outpatient DaVita dialysis centres between 2004 and 2016. Patients with at least 5 years of follow-up since the initiation of HD or death within 5 years were included; 105 variables relating to demographics, HD treatment and laboratory measurements were evaluated as predictors of 5-year mortality utilizing a machine learning approach (random forest). RESULTS: A total of 363 patients were included in the analysis, with 84 patients having started HD at <12 years of age. Low albumin and elevated lactate dehydrogenase (LDH) were the two most important predictors of 5-year mortality. Other predictors included elevated red blood cell distribution width or blood pressure and decreased red blood cell count, haemoglobin, albumin:globulin ratio, ultrafiltration rate, z-score weight for age or single-pool Kt/V (below target). Mortality was predicted with an accuracy of 81%. CONCLUSIONS: Mortality in paediatric and young adult patients on chronic HD is associated with multifactorial markers of nutrition, inflammation, anaemia and dialysis dose. This highlights the importance of multimodal intervention strategies besides adequate HD treatment as determined by Kt/V alone. The association with elevated LDH was not previously reported and may indicate the relevance of blood-membrane interactions, organ malperfusion or haematologic and metabolic changes during maintenance HD in this population.

Pharmacometric analyses to characterize the effect of CSL112 on apolipoprotein A-I and cholesterol efflux capacity in acute myocardial infarction patients.

AIMS: To characterize relationships between apolipoprotein A-I (apoA-I) exposure and cholesterol efflux capacity (CEC) and covariate effects following CSL112 (apoA-I [human]) administration in an integrated population including acute myocardial infarction (AMI) patients. METHODS: A pharmacometric analysis utilized data from seven clinical trials, including patients with AMI, subjects with renal impairment and healthy subjects. A population pharmacokinetic (PK) analysis was performed to relate CSL112 doses to changes in apoA-I plasma concentrations. Covariate analysis was conducted to identify sources of variability in apoA-I exposure. Exposure-response modeling was conducted to describe the relationship between apoA-I exposure and total or ATP binding cassette transporter A1-(ABCA1)-dependent CEC and to identify clinical predictors of CEC. RESULTS: A two-compartment model described apoA-I PK. ApoA-I clearance was slightly lower in subjects with AMI, whereas baseline apoA-I was marginally higher in female and Japanese subjects. Covariate effects on apoA-I exposure were in the order of 10% and thus not clinically relevant. The relationships between apoA-I exposure and CECs were described by nonlinear models. Simulations showed CEC elevation resulting from apoA-I exposure increment was comparable in AMI and non-AMI subjects; no covariate had clinically meaningful effects on CEC. Simulations also demonstrated that CEC in patients with AMI post 6 g CSL112 dosing was substantially elevated compared to placebo and lower dose levels. CONCLUSIONS: The model-based exposure-response analysis demonstrated, irrespective of body weight, sex and race, that fixed 6 g CSL112 dosing causes a desired CEC elevation, which may benefit AMI patients by potentially reducing early recurrent cardiovascular event risk.

Hemodialysis (HD) dose and ultrafiltration rate are associated with survival in pediatric and adolescent patients on chronic HD-a large observational study with follow-up to young adult age.

BACKGROUND: Hemodialysis (HD) dose targets and ultrafiltration rate (UFR) limits for pediatric patients on chronic HD are not known and are derived from adults (spKt/V>1.4 and <13 ml/kg/h). We aimed to characterize how delivered HD dose and UFR are associated with survival in a large cohort of patients who started HD in childhood. METHODS: Retrospective analysis on a cohort of patients <30 years, on chronic HD since childhood (<19 years), having received thrice-weekly HD 2004-2016 in outpatient DaVita centers. OUTCOME: Survival while remaining on HD. PREDICTORS: (I) primary analysis: mean delivered dialysis dose stratified as spKt/V ≤1.4/1.4-1.6/>1.6 (Kaplan-Meier analysis), (II) secondary analyses: UFR and alternative dialysis adequacy measures [eKt/V, body-surface normalized Kt/BSA] on continuous scale (Weibull regression model). RESULTS: A total of 1780 patients were included (age at the start of HD: 0-12y: n=321, >12-18y: n=1459; median spKt/V=1.55, eKt/V=1.31, Kt/BSA=31.2 L/m2, UFR=10.6 mL/kg/h). (I) spKt/V<1.4 was associated with lower survival compared to spKt/V>1.4-1.6 (P<0.001, log-rank test), and spKt/V>1.6 (P<0.001), with 10-year survival of 69.3% (59.4-80.9%) versus 83.0% (76.8-89.8%) and 84.0% (79.6-88.5%), respectively. (II) Kt/BSA was a better predictor of survival than spKt/V or eKt/V. UFR was additionally associated with survival (P<0.001), with increased mortality <10/>18 mL/kg/h. Associations did not alter significantly following adjustment for demographic characteristics (age, etiology of kidney disease, and ethnicity). CONCLUSIONS: Our results suggest usefulness of targeting Kt/BSA>30 L/m2 for best long-term outcomes, corresponding to spKt/V>1.4 (>12 years) and >1.6 (<12 years). In contrast to adults, higher UFR of 10-18 ml/kg/h was not associated with greater mortality in this population.

Characterizing dynamics of serum creatinine and creatinine clearance in extremely low birth weight neonates during the first 6 weeks of life.

BACKGROUND: Characterizing the dynamics of serum creatinine concentrations (Scr) and associated creatinine clearance (CLcr) as a measure of kidney function in extremely low birth weight (≤ 1000 g; ELBW) neonates remains challenging. METHODS: We performed a retrospective study that included longitudinal Scr (enzymatic assay) data from 148 ELBW neonates up to 6 weeks after birth. Change of Scr and inter-individual variability was characterized with nonlinear mixed-effect modeling. Key covariates such as gestational age (GA), mode of delivery (MOD), and treatment with ibuprofen or inotropic agents were investigated. RESULTS: A total of 2814 Scr concentrations were analyzed. GA was associated with Scr at birth (higher with advancing GA), and GA and MOD showed an association with postnatal maturation of CLcr (faster clearance increase with advancing GA and after C-section). Small CLcr decrease (≤ 5%) was quantified during ibuprofen treatment. For a GA of 27 weeks, mean Scr (estimated CLcr) at birth was 0.61 mg/dl (0.23 ml/min), increasing to 0.87 mg/dl (0.27 ml/min) at day three, and decreasing to 0.36 mg/dl (0.67 ml/min) at day 42 after birth. CONCLUSIONS: We report the first mathematical model able to characterize Scr and CLcr in ELBW neonates during the first 6 weeks of life in a quantitative manner as a function of GA, MOD, and ibuprofen treatment. This model allows the derivation of GA-adjusted reference ranges for ELBW neonates and provides a rationale for normative Scr concentrations, and as such will help clinicians to further optimize monitoring and treatment decisions in this vulnerable patient population.

The rhythm of a preterm neonate's life: ultradian oscillations of heart rate, body temperature and sleep cycles.

The objectives are to characterize oscillations of physiological functions such as heart rate and body temperature, as well as the sleep cycle from behavioral states in generally stable preterm neonates during the first 5 days of life. Heart rate, body temperature as well as behavioral states were collected during a daily 3-h observation interval in 65 preterm neonates within the first 5 days of life. Participants were born before 32 weeks of gestational age or had a birth weight below 1500 g; neonates with asphyxia, proven sepsis or malformation were excluded. In total 263 observation intervals were available. Heart rate and body temperature were analyzed with mathematical models in the context of non-linear mixed effects modeling, and the sleep cycles were characterized with signal processing methods. The average period length of an oscillation in this preterm neonate population was 159 min for heart rate, 290 min for body temperature, and the average sleep cycle duration was 19 min. Oscillation of physiological functions as well as sleep cycles can be characterized in very preterm neonates within the first few days of life. The observed parameters heart rate, body temperature and sleep are running in a seemingly uncorrelated pace at that stage of development. Knowledge about such oscillations may help to guide nursing and medical care in these neonates as they do not yet follow a circadian rhythm.

Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study.

Modeling of retrospectively collected multi-center data of a rare disease in pediatrics is challenging because laboratory data can stem from several decades measured with different assays. Here we present a retrospective pharmacometrics (PMX) based data analysis of the rare disease congenital hypothyroidism (CH) in newborns and infants. Our overall aim is to develop a model that can be applied to optimize dosing in this pediatric patient population since suboptimal treatment of CH during the first 2 years of life is associated with a reduced intelligence quotient between 10 and 14 years. The first goal is to describe a retrospectively collected dataset consisting of 61 newborns and infants with CH up to 2 years of age. Overall, 505 measurements of free thyroxine (FT4) and 510 measurements of thyrotropin or thyroid-stimulating hormone were available from patients receiving substitution treatment with levothyroxine (LT4). The second goal is to introduce a scale/location-scale normalization method to merge available FT4 measurements since 34 different postnatal age- and assay-specific laboratory reference ranges were applied. This method takes into account the change of the distribution of FT4 values over time, i.e. a transformation from right-skewed towards normality during LT4 treatment. The third goal is to develop a practical and useful PMX model for LT4 treatment to characterize FT4 measurements, which is applicable within a clinical setting. In summary, a time-dependent normalization method and a practical PMX model are presented. Since there is no on-going or planned development of new pharmacological approaches for CH, PMX based modeling and simulation can be leveraged to personalize dosing with the goal to enhance longer-term neurological outcome in children with the rare disease CH.

Optimisation of vancomycin exposure in neonates based on the best level of evidence.

There is no consensus regarding optimal dosing of vancomycin in term or preterm neonates. Various available dosing recommendations are based on age, kidney function and/or body weight to define a starting dose. Our objectives were (i) to develop a comprehensive population PK model of vancomycin in a large cohort of neonates and (ii) to evaluate and compare the performances of current dosing approaches with respect to target attainment, using simulations based on our model. This will serve the purpose to recommend the best dosing approaches among existing regimens in the early and later phases after treatment initiation as a complementary approach to therapeutic drug monitoring (TDM). A total 405 neonates provided 1831 vancomycin concentrations measured during routine TDM. A one-compartment model with linear elimination incorporating covariates such as age, kidney function and body weight was developed (NONMEM®). The final model was applied to simulate in our population vancomycin exposure resulting from 20 dosing guidelines identified in the literature. Proportions of patients within and above target exposure were used as a performance measure. Target attainment meant area under the curve/minimal inhibitory concentration (AUC24/MIC) ratio of 400-700 h and trough concentration of 10-20 mg/L, both on days 1 and 7. Most current vancomycin dosing regimens fail to ensure target attainment in a majority of neonates. Insufficiently dosed regimens should be avoided, especially in centers with widespread coagulase negative Staphylococci. Adding a loading dose to simple regimens is best recommended to increase the proportion of early target attainment. Complex regimens seem to marginally improve exposure. Optimisation of efficacy while minimizing toxicity of vancomycin in neonates is needed. The application of a simple dosing regimens like NNF7 or the Neofax Hi-Dose regimens, with a 25 mg/kg loading dose for severe infections, or the SmPC regimen should be recommended to ensure the highest proportion of target attainment after 24 h. TDM should then be carried out, to account for residual unexplained variability in vancomycin elimination.

Age appropriate reference intervals for eight kidney function and injury markers in infants, children and adolescents.

Objectives: The use of kidney function and injury markers for early detection of drug-related glomerular or tubular kidney injury in infants, children and adolescents requires age-specific data on reference intervals in a pediatric healthy population. This study characterizes serum values for eight kidney function and injury markers in healthy infants, children and adolescents. Methods: A single center prospective observational study was conducted between December 2018 and June 2019. Serum samples from 142 healthy infants, children and adolescents aged between 0 and ≤15 years were collected. Statistical analyses for eight markers (albumin (ALB), ß2-microglobulin (B2M), ß-trace protein (BTP), creatinine (SCR), cystatin C (CYSC), kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), uromodulin (URO)) were performed to obtain reference intervals and associations with age, sex and weight were investigated (Pearson correlation, linear and piecewise regression). Results: ALB and SCR increased with age (p<0.01), whereas B2M, BTP and KIM-1 values decreased with advancing age (p<0.05) in this healthy pediatric study population. CYSC showed dependency on sex (lower concentration in females) and decreased with age until reaching approximately 1.8 years; thereafter an increase with age was seen. NGAL and URO did not show any age-dependency. Conclusions: This study provides age appropriate reference intervals for key serum kidney function and injury markers determined in healthy infants, children and adolescents. Such reference intervals facilitate the interpretation of changes in kidney function and injury markers in daily practice, and allow early detection of glomerular and tubular injury in infancy, childhood and adolescence.

Understanding the Effects of Kidney Disease and Dialysis Treatment on Pharmacotherapy in Children.

Chronic kidney disease (CKD) and acute kidney injury (AKI) requiring renal replacement therapy (RRT) by dialysis are rare conditions in pediatric patients. In pediatric patients with CKD, dialysis is mainly performed using peritoneal dialysis (PD) or intermittent hemodialysis (HD). In patients with AKI, continuous renal replacement therapy (CRRT) using hemofiltration, hemodialysis, or both techniques can be used. This chapter reviews (1) physiology and epidemiology of kidney disease and dialysis in children and (2) pharmacokinetic principles to be considered for developing pediatric dose recommendations under different dialysis modalities. Methods for both calculating and predicting dialysis drug clearance are reviewed; scaling approaches for predicting dialysis clearance in pediatric patients from data obtained in adults are discussed.

Clinical Pharmacology and Pharmacometrics to Better Understand Physiological Changes During Pregnancy and Neonatal Life.

Pregnant women, fetuses, and newborns are particularly vulnerable patient populations. During pregnancy, the body is subject to physiological changes that influence the pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in pregnant women can result in sub-therapeutic or toxic effects, putting not only the pregnant woman but also her fetus at risk. During neonatal life, maturation processes also affect pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in newborns leads not only to short-term complications but can also have a negative impact on the long-term development of infants and children. For these reasons, it is crucial to characterize physiological changes in pregnant women, describe placental transfer kinetics of drugs, and describe physiological changes related to the transition from intrauterine to extrauterine life and maturation processes in preterm and term neonates. Quantitative pharmacological approaches such as pharmacometric and physiologically-based modeling and model-based simulations can be useful to better understand and predict such physiological changes and their effects on drug exposure and response. This review article (1) gives an overview of physiological changes in pregnant women, their fetuses, and (pre)term neonates, (2) presents case studies to illustrate applications of new modeling and simulation approaches, and (3) discusses challenges and opportunities in optimizing and personalizing treatments during pregnancy and neonatal life.

Enhanced early prediction of clinically relevant neonatal hyperbilirubinemia with machine learning.

BACKGROUND: Machine learning models may enhance the early detection of clinically relevant hyperbilirubinemia based on patient information available in every hospital. METHODS: We conducted a longitudinal study on preterm and term born neonates with serial measurements of total serum bilirubin in the first two weeks of life. An ensemble, that combines a logistic regression with a random forest classifier, was trained to discriminate between the two classes phototherapy treatment vs. no treatment. RESULTS: Of 362 neonates included in this study, 98 had a phototherapy treatment, which our model was able to predict up to 48 h in advance with an area under the ROC-curve of 95.20%. From a set of 44 variables, including potential laboratory and clinical confounders, a subset of just four (bilirubin, weight, gestational age, hours since birth) suffices for a strong predictive performance. The resulting early phototherapy prediction tool (EPPT) is provided as an open web application. CONCLUSION: Early detection of clinically relevant hyperbilirubinemia can be enhanced by the application of machine learning. Existing guidelines can be further improved to optimize timing of bilirubin measurements to avoid toxic hyperbilirubinemia in high-risk patients while minimizing unneeded measurements in neonates who are at low risk.