A physiological approach to renal clearance: From premature neonates to adults.

AIMS: We propose using glomerular filtration rate (GFR) as the physiological basis for distinguishing components of renal clearance. METHODS: Gentamicin, amikacin and vancomycin are thought to be predominantly excreted by the kidneys. A mixed-effects joint model of the pharmacokinetics of these drugs was developed, with a wide dispersion of weight, age and serum creatinine. A dataset created from 18 sources resulted in 27,338 drug concentrations from 9,901 patients. Body size and composition, maturation and renal function were used to describe differences in drug clearance and volume of distribution. RESULTS: This study demonstrates that GFR is a predictor of two distinct components of renal elimination clearance: (1) GFR clearance associated with normal GFR and (2) non-GFR clearance not associated with normal GFR. All three drugs had GFR clearance estimated as a drug-specific percentage of normal GFR (gentamicin 39%, amikacin 90% and vancomycin 57%). The total clearance (sum of GFR and non-GFR clearance), standardized to 70 kg total body mass, 176 cm, male, renal function 1, was 5.58 L/h (95% confidence interval [CI] 5.50-5.69) (gentamicin), 7.77 L/h (95% CI 7.26-8.19) (amikacin) and 4.70 L/h (95% CI 4.61-4.80) (vancomycin). CONCLUSIONS: GFR provides a physiological basis for renal drug elimination. It has been used to distinguish two elimination components. This physiological approach has been applied to describe clearance and volume of distribution from premature neonates to elderly adults with a wide dispersion of size, body composition and renal function. Dose individualization has been implemented using target concentration intervention.

Key factors associated with 6-thioguanine and 6-methylmercaptopurine nucleotide concentrations in children treated by thiopurine for acute leukaemia and inflammatory bowel disease.

AIMS: Azathioprine (AZA) and 6-mercaptopurine are prescribed in acute lymphoblastic leukaemia (ALL) and inflammatory bowel diseases (IBD). Metabolism to active 6-thioguanine (6TGN) and 6-methylmercaptopurine nucleotides (6MMPN) is variable but therapeutic drug monitoring (TDM) remains debatable. This study reports on factors impacting on red blood cell (RBC) metabolites concentrations in children to facilitate TDM interpretation. METHODS: The first paediatric TDM samples received during year 2021 were analysed, whatever indication and thiopurine drug. Target concentration ranges were 200-500, <6000 pmol/8 × 108 RBC for 6TGN and 6MMPN. RESULTS: Children (n = 492) had IBD (64.8%), ALL (22.6%) or another autoimmune disease (12.6%): mean ages at TDM were 7.5 in ALL and 13.7 years in IBD (P < .0001). ALL received 6-mercaptopurine (mean dose 1.7 mg/kg/d with methotrexate), IBD received AZA (1.9 mg/kg/d with anti-inflammatory drugs and/or monoclonal antibodies). Median 6TGN and 6MMPN concentrations were 213.7 [interquartile range: 142.5; 309.6] and 1144.6 [419.4; 3574.3] pmol/8 × 108 RBC, 38.8% of patients were in the recommended therapeutic range for both compounds. Aminotransferases and blood tests were abnormal in 57/260 patients: 8.1% patients had high alanine aminotransaminase, 3.4% of patients had abnormal blood count. Factors associated with increased 6TGN were age at TDM and thiopurine methyltransferase genotype in ALL and AZA dose in IBD. The impact of associated treatment in IBD patients was also significant. CONCLUSION: TDM allowed identification of children who do not reach target levels or remain over treated. Including TDM in follow-up may help physicians to adjust dosage with the aim of reducing adverse effects and improve treatment outcome.

Limited sampling strategy and population pharmacokinetic model of mycophenolic acid in pediatric patients with systemic lupus erythematosus: application of a double gamma absorption model with SAEM algorithm.

INTRODUCTION: Mycophenolic acid (MPA), the active metabolite of mycophenolate mofetil (MMF), is widely used in the treatment of systemic lupus erythematosus (SLE). It has been shown that its therapeutic drug monitoring based on the area under the curve (AUC) improves treatment efficacy. MPA exhibits a complex bimodal absorption, and a double gamma distribution model has been already proposed in the past to accurately describe this phenomenon. These previous population pharmacokinetics models (POPPK) have been developed using iterative two stage Bayesian (IT2B) or non-parametric adaptive grid (NPAG) methods. However, non-linear mixed effect (NLME) approaches based on stochastic approximation expectation-maximization (SAEM) algorithms have never been published so far for this particular model. The objectives of this study were (i) to implement the double absorption gamma model in Monolix, (ii) to compare different absorption models to describe the pharmacokinetics of MMF, and (iii) to develop a limited sampling strategy (LSS) to estimate AUC in pediatric SLE patients. MATERIAL AND METHODS: A data splitting of full pharmacokinetic profiles sampled in 67 children extracted either from the expert system ISBA (n = 34) or the hospital Saint Louis (n = 33) was performed into train (75%) and test (25%) sets. A POPPK was developed for MPA in the train set using a NLME and the SAEM algorithm and different absorption models were implemented and compared (first order, transit, or simple and double gamma). The best limited sampling strategy was then determined in the test set using a maximum-a-posteriori Bayesian method to estimate individual PK parameters and AUC based on three blood samples compared to the reference AUC calculated using the trapezoidal rule applied on all samples and performances were assessed in the test set. RESULTS: Mean patient age and dose was 13 years old (5-18) and 18.1 mg/kg (7.9-47.6), respectively. MPA concentrations (764) from 107 occasions were included in the analysis. A double gamma absorption with a first-order elimination from the central compartment best fitted the data. The optimal LSS with samples at 30 min, 2 h, and 3 h post-dose exhibited good performances in the test set (mean bias - 0.32% and RMSE 21.0%). CONCLUSION: The POPPK developed in this study adequately estimated the MPA AUC in pediatric patients with SLE based on three samples. The double absorption gamma model developed with the SAEM algorithm showed very accurate fit and reduced computation time.

Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates.

BACKGROUND AND OBJECTIVE: High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0) and steady-state area-under-curve (AUC0-24) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions. METHODS: C0 were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC0-24 were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C0 and AUC0-24. An external dataset was used for predictive performance evaluation. RESULTS: Before starting treatment, C0 can be predicted a priori using the Catboost-based C0-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C0 in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C0) in patients have been obtained, AUC0-24 can be further predicted using the Catboost-based AUC-ML model combined with C0 and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%. CONCLUSION: C0-based and AUC0-24-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.

Improved HPLC Quantification of 6-Mercaptopurine Metabolites in Red Blood Cells: Monitoring Data and Literature Analysis.

Thiopurine drugs azathioprine (AZA) and 6-mercaptopurine (6-MP) are used extensively in pediatric and adult patients with inflammatory and neoplastic diseases. They are metabolized to 6-thioguanine nucleotides (6-TGN) or to 6-methyl-mercaptopurine nucleotides (6-MMPN). The balance between 6-TGN and 6-MMPN is highly variable and monitoring is recommended, but its benefit in outcome gives rise to conflicting results, potentially increased by differences in quantifying 6-MP metabolism. Our aim was to report (1) the HPLC-UV procedure used in our laboratory to quantify red blood cells (RBCs) with 6-TGN and 6-MMPN (as its derivate: 6-MMP(d)) in patients treated with thiopurines and (2) additional tests, sometimes confirmatory, to improve method standardization. The comparison of two methods to count RBCs shows that metabolite concentrations were slightly lower in the washed and resuspended RBCs than in whole blood. Perchloric acid (0.7 M), dithiothreitol (DTT, final 0.013 M sample concentration) and 60 min hydrolysis were selected for acid hydrolysis. (3) Monitoring data from 83 patients receiving AZA or 6-MP showed that at steady state, only 53/183 (29%) had 6-TGN and 6-MMPN in the recommended therapeutic range. Our method is discussed in light of the technical conditions and sample stability data from 17 publications identified since the first analytical report in 1987. Monitoring data demonstrate, if required, that inter-patient variability in 6-TGN and 6-MMPN concentrations is high in samples from treated patients.

Optimization of Vancomycin Initial Dose in Term and Preterm Neonates by Machine Learning.

INTRODUCTION: Vancomycin is one of the antibiotics most used in neonates. Continuous infusion has many advantages over intermittent infusions, but no consensus has been achieved regarding the optimal initial dose. The objectives of this study were: to develop a Machine learning (ML) algorithm based on pharmacokinetic profiles obtained by Monte Carlo simulations using a population pharmacokinetic model (POPPK) from the literature, in order to derive the best vancomycin initial dose in preterm and term neonates, and to compare ML performances with those of an literature equation (LE) derived from a POPPK previously published. MATERIALS AND METHODS: The parameters of a previously published POPPK model of vancomycin in children and neonates were used in the mrgsolve R package to simulate 1900 PK profiles. ML algorithms were developed from these simulations using Xgboost, GLMNET and MARS in parallel, benchmarked and used to calculate the ML first dose. Performances were evaluated in a second simulation set and in an external set of 82 real patients and compared to those of a LE. RESULTS: The Xgboost algorithm yielded numerically best performances and target attainment rates: 46.9% in the second simulation set of 400-600 AUC/MIC ratio vs. 41.4% for the LE model (p = 0.0018); and 35.3% vs. 28% in real patients (p = 0.401), respectively). The Xgboost model resulted in less AUC/MIC > 600, thus decreasing the risk of nephrotoxicity. CONCLUSION: The Xgboost algorithm developed to estimate the initial dose of vancomycin in term or preterm infants has better performances than a previous validated LE and should be evaluated prospectively.

[Practical management during maintenance therapy of pediatric acute lymphoblastic leukemia: Recommendations of the French Society for Childhood and Adolescent Cancer and Leukemia (SFCE)]. / Modalités pratiques de prise en charge en cours de traitement d'entretien des leucémies aiguës lymphoblastiques pédiatriques : recommandations du Comité leucémies de la Société française de lutte contre les cancers et les leucémies de l'enfant et de l'adolescent (SFCE).

Maintenance therapy is the last phase of treatment for acute lymphoblastic leukemia in children and adolescents. Although maintenance therapy is associated with toxicities and specific management issues, it is an essential phase of treatment that reduces the risk of relapse. The objective of this work is to propose a guide for the initiation, administration, and monitoring of maintenance therapy, and for the management of food, schooling, leisure, community life, risk of infection and links with family medicine.

Analysis of Paediatric Clinical Trial Characteristics and Activity Over 23 Years-Impact of the European Paediatric Regulation on a Single French Clinical Research Center.

As unlicensed or off-label drugs are frequently prescribed in children, the European Pediatric Regulation came into force in 2007 to improve the safe use of medicinal products in the pediatric population. This present report analyzes the pediatric research trials over 23 years in a clinical research center dedicated to children and the impact of regulation. The database of trial characteristics from 1998 to 2020 was analyzed. We also searched for differences between two periods (1998-2006 and 2007-2020) and between institutional and industrial sponsors during the whole period (1998-2020). A total of 379 pediatric trials were initiated at our center, corresponding to inclusion of 7955 subjects and 19448 on-site patient visits. The trials were predominantly drug evaluation trials (n = 278, 73%), sponsored by industries (n = 216, 57%) or government/non-profit institutions (n = 163, 43%). All age groups and most subspecialties were concerned. We noted an important and regular increase in the number of trials conducted over the years, with an increased number of multinational, industrially sponsored trials. Based on the data presented, areas of improvement are discussed: (1) following ethical and regulatory approval depending on the sponsor, the mean time needed for administrative and financial agreement, validation of trial procedures allowing trial initiation at the level of the center was 6.3 and 6.5 months (periods 1 and 2, respectively) and should be reduced, (2) availability of expert research teams remain insufficient, time dedicated to research attributed to physicians should be organized and recognition of research nurses is required. The positive impact of the European Pediatric Regulation highlights the need to increase the availability of trained research teams, organized within identified multicenter international pediatric research networks.

Predictive Performance of Pharmacokinetic Model-Based Virtual Trials of Vancomycin in Neonates: Mathematics Matches Clinical Observation.

BACKGROUND AND OBJECTIVE: Vancomycin is frequently used to treat Gram-positive bacterial infections in neonates. However, there is still no consensus on the optimal initial dosing regimen. This study aimed to assess the performance of pharmacokinetic model-based virtual trials to predict the dose-exposure relationship of vancomycin in neonates. METHODS: The PubMed database was searched for clinical trials of vancomycin in neonates that reported the percentage of target attainment. Monte Carlo simulations were performed using nonlinear mixed-effect modeling to predict the dose-exposure relationship, and the differences in outcomes between virtual trials and real-world data in clinical studies were calculated. RESULTS: A total of 11 studies with 14 dosing groups were identified from the literature to evaluate dose-exposure relationships. For the ten dosing groups where the surrogate marker for exposure was the trough concentration, the mean ± standard deviation (SD) for the target attainment between original studies and virtual trials was 3.0 ± 7.3%. Deviations between - 10 and 10% accounted for 80% of the included dosing groups. For the other four dosing groups where the surrogate marker for exposure was concentration during continuous infusion, all deviations were between - 10 and 10%, and the mean ± SD value was 2.9 ± 4.5%. CONCLUSION: The pharmacokinetic model-based virtual trials of vancomycin exhibited good predictive performance for dose-exposure relationships in neonates. These results might be used to assist the optimization of dosing regimens in neonatal practice, avoiding the need for trial and error.

A loss-of-function IFNAR1 allele in Polynesia underlies severe viral diseases in homozygotes.

Globally, autosomal recessive IFNAR1 deficiency is a rare inborn error of immunity underlying susceptibility to live attenuated vaccine and wild-type viruses. We report seven children from five unrelated kindreds of western Polynesian ancestry who suffered from severe viral diseases. All the patients are homozygous for the same nonsense IFNAR1 variant (p.Glu386*). This allele encodes a truncated protein that is absent from the cell surface and is loss-of-function. The fibroblasts of the patients do not respond to type I IFNs (IFN-α2, IFN-ω, or IFN-ß). Remarkably, this IFNAR1 variant has a minor allele frequency >1% in Samoa and is also observed in the Cook, Society, Marquesas, and Austral islands, as well as Fiji, whereas it is extremely rare or absent in the other populations tested, including those of the Pacific region. Inherited IFNAR1 deficiency should be considered in individuals of Polynesian ancestry with severe viral illnesses.

Pharmacokinetics of mycophenolic acid and external evaluation of two limited sampling strategies of drug exposure in patients with juvenile systematic lupus erythematosus.

INTRODUCTION: Mycophenolate mofetil (MMF), a pro-drug of mycophenolic acid (MPA), has become a major therapeutic option in juvenile systemic lupus erythematosus (jSLE). Monitoring MPA exposure using area under curve (AUC) has proved its value to increase efficacy and safety in solid organ transplantation both in children and adults, but additional data are required in patients with autoimmune diseases. In order to facilitate MMF therapeutic drug monitoring (TDM) in children, Bayesian estimators (BE) of MPA AUC0-12 h using limited sampling strategies (LSS) have been developed. Our aim was to conduct an external validation of these LSS using rich pharmacokinetics and compare their predictive performance. METHODS: Pharmacokinetic blood samples were collected from jSLE treated by MMF and MPA plasma concentrations were determined using high-performance liquid chromatography system with ultraviolet detection (HPLC-UV). Individual AUC0-12 h at steady state was calculated using the trapezoid rule and compared with two LSS: (1) ISBA, a two-stage Bayesian approach developed for jSLE and (2) ADAPT, a non-linear mixed effects model with a parametric maximum likelihood approach developed with data from renal transplanted adults. RESULTS: We received 41 rich pediatric PK at steady state from jSLE and calculated individual AUC0-12 h. The external validation MPA AUC0-12 h was conducted by selecting the concentration-time points adapted to ISBA and ADAPT: (1) ISBA showed good accuracy (bias: - 0.8 mg h/L), (2) ADAPT resulted in a bias of 6.7 mg L/h. The corresponding relative root mean square prediction error (RSME) was 23% and 43% respectively. CONCLUSION: According to our external validation of two LSS of drug exposure, the ISBA model is recommended for Bayesian estimation of MPA AUC0-12 h in jSLE. In the literature focusing on MMF TDM, an efficacy cut-off for MPA AUC0-12 h between 30 and 45 mg h/L is proposed in jSLE but this requires additional validation.

How paediatric drug development and use could benefit from OMICs: A c4c expert group white paper.

The safety and efficacy of pharmacotherapy in children, particularly preterms, neonates and infants, is limited by a paucity of good-quality data from prospective clinical drug trials. A specific challenge is the establishment of valid biomarkers. OMICs technologies may support these efforts by complementary information about targeted and nontargeted molecules through systematic characterization and quantitation of biological samples. OMICs technologies comprise at least genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics in addition to the patient's phenotype. OMICs technologies are in part hypothesis-generating, allowing an in depth understanding of disease pathophysiology and pharmacological mechanisms. Application of OMICs technologies in paediatrics faces major challenges before routine adoption. First, developmental processes need to be considered, including a subdivision into specific age groups as developmental changes clearly impact OMICs data. Second, compared to the adult population, the number of patients is limited as are the type and amount of necessary biomaterial, especially in neonates and preterms. Thus, advanced trial designs and biostatistical methods, noninvasive biomarkers, innovative biobanking concepts including data and samples from healthy children, as well as analytical approaches (eg liquid biopsies) should be addressed to overcome these obstacles. The ultimate goal is to link OMICs technologies with innovative analysis tools, such as artificial intelligence at an early stage. The use of OMICs data based on a feasible approach will contribute to the identification complex phenotypes and subpopulations of patients to improve the development of medicines for children with potential economic advantages.

Agreement between a regional pharmacovigilance centre and an adjudication committee regarding adverse drug reactions on a cohort of hospitalised children.

BACKGROUND AND PURPOSE: The EREMI project was set up to collect data on adverse drug reactions (ADRs) occurring due to off-label and/or unlicensed drugs prescribed to hospitalised children in France. These events were evaluated by a regional pharmacovigilance centre (RPC) and an adjudication committee (AC). The aim of this study was to assess the agreement between these two different entities on their evaluation of ADRs. EXPERIMENTAL APPROACH: The RPC first validated the ADRs and assessed their causality using the Naranjo scale. The AC assessed then ADRs using all available information, including the RPC evaluation. The agreement on severity and nature of ADRs, role of treatment (suspect or concomitant) and drug causality was calculated using Cohen's nonparametric kappa coefficient (k). KEY RESULTS: Three hundred and eighty-six events were reported in 219 children. The RPC excluded 65 events and validated 321 ADRs. Agreement was very good on nature of ADRs (k=0.85) and role of treatment (k=0.81), moderate on severity of ADRs (k=0.60) and very poor on drug causality (k=0.05). CONCLUSION AND IMPLICATIONS: Agreement between the RPC and the AC was not constant throughout this evaluation. They troubled to agree on severe ADRs and on drug causality.

Optimised versus standard dosing of vancomycin in infants with Gram-positive sepsis (NeoVanc): a multicentre, randomised, open-label, phase 2b, non-inferiority trial.

BACKGROUND: Vancomycin is the most widely used antibiotic for neonatal Gram-positive sepsis, but clinical outcome data of dosing strategies are scarce. The NeoVanc programme comprised extensive preclinical studies to inform a randomised controlled trial to assess optimised vancomycin dosing. We compared the efficacy of an optimised regimen to a standard regimen in infants with late onset sepsis that was known or suspected to be caused by Gram-positive microorganisms. METHODS: NeoVanc was an open-label, multicentre, phase 2b, parallel-group, randomised, non-inferiority trial comparing the efficacy and toxicity of an optimised regimen of vancomycin to a standard regimen in infants aged 90 days or younger. Infants with at least three clinical or laboratory sepsis criteria or confirmed Gram-positive sepsis with at least one clinical or laboratory criterion were enrolled from 22 neonatal intensive care units in Greece, Italy, Estonia, Spain, and the UK. Infants were randomly assigned (1:1) to either the optimised regimen (25 mg/kg loading dose, followed by 15 mg/kg every 12 h or 8 h dependent on postmenstrual age, for 5 ± 1 days) or the standard regimen (no loading dose; 15 mg/kg every 24 h, 12 h, or 8 h dependent on postmenstrual age for 10 ± 2 days). Vancomycin was administered intravenously via 60 min infusion. Group allocation was not masked to local investigators or parents. The primary endpoint was success at the test of cure visit (10 ± 1 days after the end of actual vancomycin therapy) in the per-protocol population, where success was defined as the participant being alive at the test of cure visit, having a successful outcome at the end of actual vancomycin therapy, and not having a clinically or microbiologically significant relapse or new infection requiring antistaphylococcal antibiotics for more than 24 h within 10 days of the end of actual vancomycin therapy. The non-inferiority margin was -10%. Safety was assessed in the intention-to-treat population. This trial is registered at ClinicalTrials.gov (NCT02790996). FINDINGS: Between March 3, 2017, and July 29, 2019, 242 infants were randomly assigned to the standard regimen group (n=122) or the optimised regimen group (n=120). Primary outcome data in the per-protocol population were available for 90 infants in the optimised group and 92 in the standard group. 64 (71%) of 90 infants in the optimised group and 73 (79%) of 92 in the standard group had success at test of cure visit; non-inferiority was not confirmed (adjusted risk difference -7% [95% CI -15 to 2]). Incomplete resolution of clinical or laboratory signs after 5 ± 1 days of vancomycin therapy was the main factor contributing to clinical failure in the optimised group. Abnormal hearing test results were recorded in 25 (30%) of 84 infants in the optimised group and 12 (15%) of 79 in the standard group (adjusted risk ratio 1·96 [95% CI 1·07 to 3·59], p=0·030). There were six vancomycin-related adverse events in the optimised group (one serious adverse event) and four in the standard group (two serious adverse events). 11 infants in the intention-to-treat population died (six [6%] of 102 infants in the optimised group and five [5%] of 98 in the standard group). INTERPRETATION: In the largest neonatal vancomycin efficacy trial yet conducted, no clear clinical impact of a shorter duration of treatment with a loading dose was demonstrated. The use of the optimised regimen cannot be recommended because a potential hearing safety signal was identified; long-term follow-up is being done. These results emphasise the importance of robust clinical safety assessments of novel antibiotic dosing regimens in infants. FUNDING: EU Seventh Framework Programme for research, technological development and demonstration.

Drug Safety in Translational Paediatric Research: Practical Points to Consider for Paediatric Safety Profiling and Protocol Development: A Scoping Review.

Translational paediatric drug development includes the exchange between basic, clinical and population-based research to improve the health of children. This includes the assessment of treatment related risks and their management. The objectives of this scoping review were to search and summarise the literature for practical guidance on how to establish a paediatric safety specification and its integration into a paediatric protocol. PubMed, Embase, Web of Science, and websites of regulatory authorities and learned societies were searched (up to 31 December 2020). Retrieved citations were screened and full texts reviewed where applicable. A total of 3480 publications were retrieved. No article was identified providing practical guidance. An introduction to the practical aspects of paediatric safety profiling and protocol development is provided by combining health authority and learned society guidelines with the specifics of paediatric research. The paediatric safety specification informs paediatric protocol development by, for example, highlighting the need for a pharmacokinetic study prior to a paediatric trial. It also informs safety related protocol sections such as exclusion criteria, safety monitoring and risk management. In conclusion, safety related protocol sections require an understanding of the paediatric safety specification. Safety data from carefully planned paediatric research provide valuable information for children, parents and healthcare providers.

Drug Clearance in Neonates: A Combination of Population Pharmacokinetic Modelling and Machine Learning Approaches to Improve Individual Prediction.

BACKGROUND: Population pharmacokinetic evaluations have been widely used in neonatal pharmacokinetic studies, while machine learning has become a popular approach to solving complex problems in the current era of big data. OBJECTIVE: The aim of this proof-of-concept study was to evaluate whether combining population pharmacokinetic and machine learning approaches could provide a more accurate prediction of the clearance of renally eliminated drugs in individual neonates. METHODS: Six drugs that are primarily eliminated by the kidneys were selected (vancomycin, latamoxef, cefepime, azlocillin, ceftazidime, and amoxicillin) as 'proof of concept' compounds. Individual estimates of clearance obtained from population pharmacokinetic models were used as reference clearances, and diverse machine learning methods and nested cross-validation were adopted and evaluated against these reference clearances. The predictive performance of these combined methods was compared with the performance of two other predictive methods: a covariate-based maturation model and a postmenstrual age and body weight scaling model. Relative error was used to evaluate the different methods. RESULTS: The extra tree regressor was selected as the best-fit machine learning method. Using the combined method, more than 95% of predictions for all six drugs had a relative error of < 50% and the mean relative error was reduced by an average of 44.3% and 71.3% compared with the other two predictive methods. CONCLUSION: A combined population pharmacokinetic and machine learning approach provided improved predictions of individual clearances of renally cleared drugs in neonates. For a new patient treated in clinical practice, individual clearance can be predicted a priori using our model code combined with demographic data.

Serum Creatinine and Serum Cystatin C are Both Relevant Renal Markers to Estimate Vancomycin Clearance in Critically Ill Neonates.

Purpose: Serum creatinine (SCr) is used as a marker of kidney function to guide dosing of renally eliminated drugs. Serum Cystatin C (S-CysC) has been suggested as a more reliable kidney marker than SCr in adults and children. Purpose of this study was to investigate S-CysC as alternative renal marker to SCr for estimating vancomycin clearance in neonates undergoing intensive care. Methods: Vancomycin pharmacokinetics (PK), SCr and S-CysC data were collected in patients undergoing vancomycin treatment in the neonatal intensive care unit of Robert Debré Hospital - Paris. A population PK analysis was performed utilizing routine therapeutic drug monitoring samples. S-CysC and SCr were compared as covariates on vancomycin clearance using stepwise covariate modeling (forward inclusion [p < 0.05] and backward elimination [p < 0.01]). Model performance was evaluated by graphical and statistical criteria. Results: A total of 108 vancomycin concentrations from 66 patients (postmenstrual age [PMA] of 26-46 weeks) were modeled with an allometric one-compartment model. The median (range) values for SCr and S-CysC were 41 (12-153) µmol/l and 1.43 (0.95-2.83) mg/l, respectively. Following stepwise covariate model building, SCr was retained as single marker of kidney function (after accounting for weight and PMA) in the final model. Compared to the final model based on SCr, the alternative model based on S-CysC showed very similar performance (e.g. BIC of 578.3 vs. 576.4) but included one additional covariate: impact of mechanical ventilation on vancomycin clearance, in addition to the effects of size and maturation. Conclusion: ill neonates. However, if using S-CysC for this purpose mechanical ventilation needs to be taken into account.

Contribution of Population Pharmacokinetics of Glycopeptides and Antifungals to Dosage Adaptation in Paediatric Onco-hematological Malignancies: A Review.

The response to medications in children differs not only in comparison to adults but also between children of the different age groups and according to the disease. This is true for anti-infectives that are widely prescribed in children with malignancy. In the absence of pharmacokinetic/pharmacodynamic paediatric studies, dosage is frequently based on protocols adapted to adults. After a short presentation of the drugs, we reviewed the population pharmacokinetic studies available for glycopeptides (vancomycin and teicoplanin, n = 5) and antifungals (voriconazole, posaconazole, and amphotericin B, n = 9) currently administered in children with onco-hematological malignancies. For each of them, we reported the main study characteristics including identified covariates affecting pharmacokinetics and proposed paediatric dosage recommendations. This review highlighted the very limited amount of data available, the lack of consensus regarding PK/PD targets used for dosing optimization and regarding dosage recommendations when available. Additional PK studies are urgently needed in this specific patient population. In addition to pharmacokinetics, efficacy may be altered in immunocompromised patients and prospective clinical evaluation of new dosage regimen should be provided as they are missing in most cases.