Intergenerational transmission of sucralose and acesulfame-potassium from mothers to their infants via human milk: a pharmacokinetic study.

BACKGROUND: Low-calorie sweetener (LCS) consumption is prevalent among lactating women, yet infants' exposure to LCS in human milk is not well-characterized. OBJECTIVE: Conduct a pharmacokinetic study of sucralose and ace-K in mothers' milk and plasma over 72 hours, and in infants' plasma. METHODS: Following baseline blood and milk collection, mothers (n=40) consumed 20-ounces of diet cranberry juice, containing sucralose and ace-K. Blood samples were collected from the mother 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 24, 48, and 72 hours after beverage ingestion, and milk was expressed at 1, 2, 3, 4, 6, 8, 12, and 24 hours post-ingestion. One blood sample was collected from each infant, the timing of which was determined using pharmacokinetics model-based simulation. Concentration-time profiles of LCS from mother's plasma and milk were analyzed using non-compartmental methods. RESULTS: Ace-K rapidly entered human milk with the largest observed concentration of 373.0 (CV 69%) ng/ml first detected 4 hours following diet beverage ingestion. Sucralose appeared in human milk 1-2 hours after diet beverage ingestion with the largest observed concentration of 7.2 (CV 63%) ng/ml first detected 7 hours post-ingestion. The mean 24-hour milk to plasma ratio (MPR) of ace-K was 1.75 (SD 1.37) with a mean relative infant dose (RID) of 1.59% (SD 1.72%). ace-K was detected in all infants' plasma with an average concentration of 9.2 (SD% 14.8) ng/ml approximately 6 hours after maternal beverage ingestion. The mean 24-hour MPR of sucralose was 0.15 (SD 0.06) with a mean RID of 0.04% (SD 0.02%). Sucralose was detected in only fifteen infants' plasma, and the average concentration was 5.0 (SD% 7.1) ng/ml, approximately 5 hours after diet beverage ingestion. CONCLUSIONS: Ace-K rapidly transfers from human milk into infants' circulation whereas sucralose was detected at much lower concentrations and in some but not all infants. Future research should investigate effects of early life sucralose and ace-K exposure via human milk on infants' health. TRIAL REGISTRATION: NCT05379270, https://classic. CLINICALTRIALS: gov/ct2/show/NCT05379270.

Drug related adverse event assessment in neonates in clinical trials and clinical care.

INTRODUCTION: Assessment of drug-related adverse events is essential to fully understand the benefit-risk balance of any drug exposure, weighing efficacy versus safety. This is needed for both drug labeling and clinical decision-making. Assessment is based on seriousness, severity and causality, be it more difficult to apply in neonates. Adverse event detection or prevention in the neonatal clinical setting is also more complicated because of polypharmacy, and off-label or unlicensed pharmacotherapy. AREAS COVERED: Tools became available to assess severity and causality of adverse events in neonates recruited in clinical trials. The first version of the Neonatal Adverse Event severity score (NAESS) reduced the inter-observer variability. Causality tools like the Naranjo score were also tailored to neonates. These tools are also instrumental to support proactive pharmacovigilance in clinical care, while multidisciplinary care teams and computerized pharmacovigilance using advanced data analysis, like machine learning are emerging approaches to develop effective decision strategies. EXPERT OPINION: All stakeholders involved in development of medicines or its clinical use should be aware of the limitations of the currently available assessment tools. Extension and optimization of these tools, advanced data analysis approaches, and capturing the variability in time-dependent physiology are warranted to improve pharmacovigilance in neonates.

Optimal dosing regimen of caspofungin in adolescents with allogeneic haematopoietic stem cell transplantation.

OBJECTIVES: The optimal dosing regimen of caspofungin in adolescents undergoing allogeneic haematopoietic stem cell transplantation against Candida spp. is unknown. The study aimed to compare body surface area (BSA)-based and fixed dosing regimens through population pharmacokinetic (PPK) analysis and to optimize dosing regimens likely to achieve therapeutic exposures. METHODS: Opportunistic sampling was used to collect plasma concentrations through a prospective observational pharmacokinetic study. PPK analysis and Monte Carlo simulations (n = 1000) were performed using NONMEM. RESULTS: A total of 86 samples of 30 adolescents (12-17 years old) were best described by a two-compartment pharmacokinetic model. BSA is the only covariate on clearance and central volume of distribution. For Candida glabrata and Candida albicans, a standard dosing regimen could achieve at least a 90% probability of target attainment for the indicator of AUC0-24/MIC90. Dosing regimen simulations identified a BSA cut-off value of 1.3 m2, where a fixed loading dose (LD) is preferred when BSA ≥ 1.3 m2 and a BSA-based LD is preferred when BSA < 1.3 m2. For maintenance dose (MD), however, the BSA-based dose was proposed, regardless of BSA. The current maximum dosing regimen of LD 70 mg/day and MD 70 mg/day could not result in sufficient antifungal exposure for Candida parapsilosis with MIC90 of 1 mg/L. Furthermore, an LD of 70 mg/day and MD of 60 mg/m2/day rendered 90.4% steady-state trough concentration (Ctrough) over 1 mg/L in the virtual population. CONCLUSIONS: Our study proposed optimized dosing regimens of caspofungin based on AUC0-24/MIC90 or Ctrough, which may support further individualized treatment.

Labetalol Dosing in Pregnancy: PBPK/PD and CYP2C19 Polymorphisms.

As detailed information on the pharmacokinetics (PK) of labetalol in pregnant people are lacking, the aims of this study were: (1) to build a physiologically based PK (PBPK) model of labetalol in non-pregnant individuals that incorporates different CYP2C19 genotypes (specifically, *1/*1, *1/*2 or *3, *2/*2, and *17/*17); (2) to translate this model to the second and third trimester of pregnancy; and (3) to combine the model with a previously published direct pharmacodynamic (PD) model to predict the blood pressure lowering effect of labetalol in the third trimester. Clinical data for model evaluation was obtained from the scientific literature. In non-pregnant populations, the mean ratios of simulated versus observed peak concentration (Cmax), time to reach Cmax (Tmax), and exposure (area under the plasma concentration-time curve, AUC) were 0.94, 0.82, and 1.16, respectively. The pregnancy PBPK model captured the observed PK adequately, but clearance was slightly underestimated with mean ratios of simulated versus observed Cmax, Tmax, and AUC of 1.28, 1.30, and 1.39, respectively. The results suggested that pregnant people with CYP2C19 *2/*2 alleles have similar labetalol exposure and trough levels compared to non-pregnant controls, whereas those with other alleles were found to have increased exposure and trough concentrations. Importantly, the pregnancy PBPK/PD model predicted that, despite increased exposure in some genotypes, the blood pressure lowering effect was broadly comparable across all genotypes. In view of the large inter-individual variability and the potentially increasing blood pressure during pregnancy, patients may need to be closely monitored for achieving optimal therapeutic effects and avoiding adverse events.

Machine Learning Approach in Dosage Individualization of Isoniazid for Tuberculosis.

INTRODUCTION: Isoniazid is a first-line antituberculosis agent with high variability, which would profit from individualized dosing. Concentrations of isoniazid at 2 h (C2h), as an indicator of safety and efficacy, are important for optimizing therapy. OBJECTIVE: The objective of this study was to establish machine learning (ML) models to predict the C2h, that can be used for establishing an individualized dosing regimen in clinical practice. METHODS: Published population pharmacokinetic (PopPK) models for adults were searched based on PubMed and ultimately four reliable models were selected for simulating individual C2h datasets under different conditions (demographics, genotype, ethnicity, etc.). Machine learning models were trained on simulated C2h obtained from the four PopPK models. Five different algorithms were used for ML model building to predict C2h. Real-world data were used for predictive performance evaluations. Virtual trials were used to compare ML-optimized doses with PopPK model-optimized doses. RESULTS: Categorical boosting (CatBoost) exhibited the highest prediction ability. Target C2h can be predicted using the ML model combined with the dosing regimen and three covariates (N-acetyltransferase 2 [NAT2] genotypes, weight and race [Asians and Africans]). Real-world data validation results showed that the ML model can achieve an overall prediction accuracy of 93.4%. Using the final ML model, the mean absolute prediction error value decreased by 45.7% relative to the average of PopPK models. Using the ML-optimized dosing regimen, the probability of target attainment increased by 43.7% relative to the PopPK model-optimized dosing regimens. CONCLUSION: Machine learning models were developed with great predictive performance, which can be used to determine the individualized initial dose of isoniazid in adult patients.

Piperacillin/tazobactam treatment in children: evidence of subtherapeutic concentrations.

Objective: Piperacillin/tazobactam (PIP/TAZ) is used for the treatment of lower respiratory tract bacterial infections in children. This study was performed to evaluate if the current dosing regimen results in therapeutic drug concentrations. Patients and methods: Patients suspected or proven to have lower respiratory tract bacterial infection and administrated PIP/TAZ intravenously for a duration of no less than 0.5 h, q6h-q12h daily, were enrolled. Blood samples were collected, and PIP concentrations were determined by high-performance liquid chromatography. The individual predicted concentration of PIP was evaluated using the individual empirical Bayesian estimate method. The evaluated PK/PD targets included (1) 70% time when the predicted free drug concentration exceeds the minimum inhibitory concentration (fT > MIC) and (2) 50% fT > 4× MIC. Probability of target attainment (PTA) was assessed by the proportion of patients who reached the PK/PD targets. The PIP concentrations between different groups of patients were compared. Results: A total of 57 samples were collected from 57 patients with a median age of 2.26 years (0.17-12.58). For the PK/PD targets of 70% fT > MIC and 50% fT > 4× MIC for Pseudomonas aeruginosa and Klebsiella pneumoniae, the PTA was all 0. The median Cmin of PIP was significantly higher in infants than in children, and the median Cmin after administration in q8h was significantly higher than that after administration in q12h. Conclusion: The current dose regimen of PIP/TAZ leads to extremely low plasma concentrations in most children with lower respiratory tract bacterial infections. More optimized dosing regimens or better alternative therapies need to be further explored.

Model-informed drug development in pediatric, pregnancy and geriatric drug development: States of the art and future.

The challenges of drug development in pediatric, pregnant and geriatric populations are a worldwide concern shared by regulatory authorities, pharmaceutical companies, and healthcare professionals. Model-informed drug development (MIDD) can integrate and quantify real-world data of physiology, pharmacology, and disease processes by using modeling and simulation techniques to facilitate decision-making in drug development. In this article, we reviewed current MIDD policy updates, reflected on the integrity of physiological data used for MIDD and the effects of physiological changes on the drug PK, as well as summarized current MIDD strategies and applications, so as to present the state of the art of MIDD in pediatric, pregnant and geriatric populations. Some considerations are put forth for the future improvements of MIDD including refining regulatory considerations, improving the integrity of physiological data, applying the emerging technologies, and exploring the application of MIDD in new therapies like gene therapies for special populations.

Machine Learning: A Potential Therapeutic Tool to Facilitate Neonatal Therapeutic Decision Making.

Bacterial infection is one of the major causes of neonatal morbidity and mortality worldwide. Finding rapid and reliable methods for early recognition and diagnosis of bacterial infections and early individualization of antibacterial drug administration are essential to eradicate these infections and prevent serious complications. However, this is often difficult to perform due to non-specific clinical presentations, low accuracy of current diagnostic methods, and limited knowledge of neonatal pharmacokinetics. Although neonatal medicine has been relatively late to embrace the benefits of machine learning (ML), there have been some initial applications of ML for the early prediction of neonatal sepsis and individualization of antibiotics. This article provides a brief introduction to ML and discusses the current state of the art in diagnosing and treating neonatal bacterial infections, gaps, potential uses of ML, and future directions to address the limitations of current studies. Neonatal bacterial infections involve a combination of physiologic development, disease expression, and treatment response outcomes. To address this complex relationship, future models could consider appropriate ML algorithms to capture time series features while integrating influences from the host, microbes, and drugs to optimize antimicrobial drug use in neonates. All models require prospective clinical trials to validate their clinical utility before clinical use.

Optimal use of ß-lactams in neonates: machine learning-based clinical decision support system.

BACKGROUND: Accurate prediction of the optimal dose for ß-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliable clinical decision support system (CDSS) based on machine learning (ML) can assist clinicians in making optimal dose selections. METHODS: Five ß-lactam antibiotics (amoxicillin, ceftazidime, cefotaxime, meropenem and latamoxef), commonly used to treat neonatal sepsis, were selected. The CDSS was constructed by incorporating the drug, patient, dosage, pharmacodynamic, and microbiological factors. The CatBoost ML algorithm was used to build the CDSS. Real-world studies were used to evaluate the CDSS performance. Virtual trials were used to compare the CDSS-optimized doses with guideline-recommended doses. FINDINGS: For a specific drug, by entering the patient characteristics and pharmacodynamic (PD) target (50%/70%/100% fraction of time that the free drug concentration is above the minimal inhibitory concentration [fT > MIC]), the CDSS can determine whether the planned dosing regimen will achieve the PD target and suggest an optimal dose. The prediction accuracy of all five drugs was >80.0% in the real-world validation. Compared with the PopPK model, the overall accuracy, precision, recall, and F1-Score improved by 10.7%, 22.1%, 64.2%, and 43.1%, respectively. Using the CDSS-optimized doses, the average probability of target concentration attainment increased by 58.2% compared to the guideline-recommended doses. INTERPRETATION: An ML-based CDSS was successfully constructed to assist clinicians in selecting optimal ß-lactam antibiotic doses. FUNDING: This work was supported by the National Natural Science Foundation of China; Distinguished Young and Middle-aged Scholar of Shandong University; National Key Research and Development Program of China.

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.

Assessing Pharmacogenomic loci Associated with the Pharmacokinetics of Vamorolone in Boys with Duchenne Muscular Dystrophy.

Human genetic variation (polymorphisms) in genes coding proteins involved in the absorption, distribution, metabolism, and elimination (ADME) of drugs can have a strong effect on drug exposure and downstream efficacy and safety outcomes. Vamorolone, a dissociative steroidal anti-inflammatory drug for treating Duchenne muscular dystrophy (DMD), primarily undergoes oxidation by CYP3A4 and CYP3A5 and glucuronidation by UDP-glucuronosyltransferases. This work assesses the pharmacokinetics (PKs) of vamorolone and sources of interindividual variability (IIV) in 81 steroid-naïve boys with DMD aged 4 to <7 years old considering the genetic polymorphisms of CYPS3A4 (CYP3A4*22, CYP3A4*1B), CYP3A5 (CYP3A5*3), and UGT1A1 (UGT1A1*60) utilizing population PK modeling. A one-compartment model with zero-order absorption (Tk0, duration of absorption), linear clearance (CL/F), and volume (V/F) describes the plasma PK data for boys with DMD receiving a wide range of vamorolone doses (0.25-6 mg/kg/day). The typical CL/F and V/F values of vamorolone were 35.8 L/h and 119 L, with modest IIV. The population Tk0 was 3.14 h yielding an average zero-order absorption rate (k0) of 1.16 mg/kg/h with similar absorption kinetics across subjects at the same vamorolone dose (i.e., no IIV on Tk0). The covariate analysis showed that none of the genetic covariates had any significant impact on the PKs of vamorolone in boys with DMD. Thus, the PKs of vamorolone is very consistent in these young boys with DMD.

Pharmacometric in silico studies used to facilitate a national dose standardisation process in neonatology - application to amikacin.

BACKGROUND AND AIMS: Pharmacometric in silico approaches are frequently applied to guide decisions concerning dosage regimes during the development of new medicines. We aimed to demonstrate how such pharmacometric modelling and simulation can provide a scientific rationale for optimising drug doses in the context of the Swiss national dose standardisation project in paediatrics using amikacin as a case study. METHODS: Amikacin neonatal dosage is stratified by post-menstrual age (PMA) and post-natal age (PNA) in Switzerland and many other countries. Clinical concerns have been raised for the subpopulation of neonates with a post-menstrual age of 30-35 weeks and a post-natal age of 0-14 days ("subpopulation of clinical concern"), as potentially oto-/nephrotoxic trough concentrations (Ctrough >5 mg/l) were observed with a once-daily dose of 15 mg/kg. We applied a two-compartmental population pharmacokinetic model (amikacin clearance depending on birth weight and post-natal age) to real-world demographic data from 1563 neonates receiving anti-infectives (median birth weight 2.3 kg, median post-natal age six days) and performed pharmacometric dose-exposure simulations to identify extended dosing intervals that would ensure non-toxic Ctrough (Ctrough <5 mg/l) dosages in most neonates. RESULTS: In the subpopulation of clinical concern, Ctrough <5 mg/l was predicted in 59% versus 79-99% of cases in all other subpopulations following the current recommendations. Elevated Ctrough values were associated with a post-natal age of less than seven days. Simulations showed that extending the dosing interval to ≥36 h in the subpopulation of clinical concern increased the frequency of a desirable Ctrough below 5 mg/l to >80%. CONCLUSION: Pharmacometric in silico studies using high-quality real-world demographic data can provide a scientific rationale for national paediatric dose optimisation. This may increase clinical acceptance of fine-tuned standardised dosing recommendations and support their implementation, including in vulnerable subpopulations.

Efficacy, Safety, and Population Pharmacokinetics of Eltrombopag in Children with Different Severities of Aplastic Anemia.

Eltrombopag was approved as a first-line treatment for patients older than 2 years old with severe aplastic anemia (SAA). However, data on eltrombopag in children with different types of aplastic anemia (AA), especially non-severe AA (NSAA), are limited. We performed a prospective, single-arm, and observational study to investigate eltrombopag's efficacy, safety, and pharmacokinetics in children with NSAA, SAA, and very severe AA (VSAA). The efficacy and safety were assessed every 3 months. The population pharmacokinetic (PPK) model was used to depict the pharmacokinetic profile of eltrombopag. Twenty-three AA children with an average age of 7.9 (range of 3.0-14.0) years were enrolled. The response (complete and partial response) rate was 12.5%, 50.0%, and 100.0% after 3, 6, and 12 months in patients with NSAA. For patients with SAA and VSAA, these response rates were 46.7%, 61.5%, and 87.5%. Hepatotoxicity occurred in one patient. Fifty-three blood samples were used to build the PPK model. Body weight was the only covariate for apparent clearance (CL/F) and volume of distribution. The allele-T carrier of adenosine triphosphate-binding cassette transporter G2 was found to increase eltrombopag's clearance. However, when normalized by weight, the clearance between the wild-type and variant showed no statistical difference. In patients with response, children with NSAA exhibited lower area under the curve from time zero to infinity, higher CL/F, and higher weight-adjusted CL/F than those with SAA or VSAA. However, the differences were not statistically significant. The results may support further individualized treatment of eltrombopag in children with AA.

Pharmacokinetics-Based Pediatric Dose Evaluation and Optimization Using Saliva - A Case Study.

Understanding pharmacokinetics (PK) in children is a prerequisite to determine optimal pediatric dosing. As plasma sampling in children is challenging, alternative PK sampling strategies are needed. In this case study we evaluated the suitability of saliva as alternative PK matrix to simplify studies in infants, investigating metamizole, an analgesic used off-label in infants. Six plasma and 6 saliva PK sample collections were scheduled after a single intravenous dose of 10 mg/kg metamizole. Plasma/saliva pharmacometric (PMX) modeling of the active metabolites 4-methylaminoantipyrine (4-MAA) and 4-aminoantipyrine (4-AA) was performed. Various reduced plasma sampling scenarios were evaluated by PMX simulations. Saliva and plasma samples from 25 children were included (age range, 5-70 months; weight range, 8.7-24.8 kg). Distribution of metamizole metabolites between plasma and saliva was without delay. Estimated mean (individual range) saliva/plasma fractions of 4-MAA and 4-AA were 0.32 (0.05-0.57) and 0.57 (0.25-0.70), respectively. Residual variability of 4-MAA (4-AA) in saliva was 47% (28%) versus 17% (11%) in plasma. A simplified sampling scenario with up to 6 saliva samples combined with 1 plasma sample was associated with similar PK parameter estimates as the full plasma sampling scenario. This case study with metamizole shows increased PK variability in saliva compared to plasma, compromising its suitability as single matrix for PK studies in infants. Nonetheless, rich saliva sampling can reduce the number of plasma samples required for PK characterization, thereby facilitating the conduct of PK studies to optimize dosing in pediatric patients.

No additional risk of congenital anomalies after first-trimester dydrogesterone use: a systematic review and meta-analysis.

STUDY QUESTION: Is exposure to dydrogesterone a risk factor for congenital anomalies when given in the first trimester for recurrent/threatened pregnancy loss or as luteal support in assisted reproductive technology (ART)? SUMMARY ANSWER: Dydrogesterone, when given in the first trimester for recurrent/threatened pregnancy loss or as luteal support in ART, is not a relevant additional risk factor for congenital anomalies. WHAT IS KNOWN ALREADY: Despite large clinical trials and meta-analyses that show no association between dydrogesterone and congenital anomalies, some recently retracted publications have postulated an association with teratogenicity. Dydrogesterone is also often rated as less safe than bioidentical progestins. STUDY DESIGN SIZE DURATION: A systematic review was conducted according to a pre-specified protocol with searches on Medline, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), and Clinicaltrials.gov. The search was limited to human studies, with no restrictions on language, geographical region, or date. The search algorithm used a PICO (Population, Intervention, Comparison, Outcome)-style approach combining both simple search terms and medical subject heading terms. As congenital anomalies are mostly reported as secondary outcomes, the search term 'safety' was added. PARTICIPANTS/MATERIALS SETTING METHODS: Interventional study and observational study (OS) designs were eligible for inclusion. Inclusion criteria were: women >17 years old treated for threatened miscarriage, recurrent pregnancy loss, and/or ART; the use of dydrogesterone in the first trimester compared with placebo, no treatment or other interventions; and reporting of congenital anomalies in newborns or infants ≤12 months old (primary outcome). Two authors (A.K., M.R.N.) independently extracted the following data: general study information, study population details, intervention and comparator(s), and frequencies of congenital anomalies (classification, time of determination, and type). Risk of bias focused on the reporting of congenital malformations and was assessed using the Cochrane Risk of Bias Tool Version 2 or the ROBINS-I tool. The GRADEproGDT platform was used to generate the GRADE summary of findings table. MAIN RESULTS AND THE ROLE OF CHANCE: Of the 897 records retrieved during the literature search, 47 were assessed for eligibility. Nine studies were included in the final analysis: six randomized controlled trials (RCTs) and three OSs. Among the RCTs, three had a low risk and three a high risk of bias. Two of the OSs were considered to have a serious risk of bias and one with critical risk of bias and was excluded for the evidence syntheses. The eight remaining studies included a total of 5070 participants and 2680 live births from 16 countries. In the meta-analysis of RCTs only, the overall risk ratio (RR) was 0.92 [95% CI 0.55; 1.55] with low certainty. When the two OSs were included, the overall RR was 1.11 [95% CI 0.73; 1.68] with low certainty. LIMITATIONS REASONS FOR CAUTION: The studies included in the analysis do not report congenital anomalies as the primary outcome; reporting of congenital anomalies was often not standardized. WIDER IMPLICATIONS OF THE FINDINGS: This systematic literature review and meta-analysis provide clear reassurance to both clinicians and patients that dydrogesterone is not associated with congenital anomalies above the rate that might be expected due to environmental and genetic factors. The results of this work represent the highest current level of evidence for the question of congenital anomalies, which removes the existing uncertainty caused by poor quality and retracted studies. STUDY FUNDING/COMPETING INTERESTS: Editorial support was provided by Highfield Communication Consultancy, Oxford, UK, sponsored by Abbott Products Operations AG, Allschwil, Switzerland. A.K., J.A.G.-V., L.P.S., J.N.v.d.A., and J.F.S. received honoraria from Abbott for preparation and participation in an advisory board. J.A.G.-V. received grants and lecture fees from Merck, Organon, Ferring, Gedeon Richter, and Theramex. M.R.N. has no conflicts of interest. J.N.v.d.A. and J.A.G.-V. have no other conflicts of interest. A.K. received payment from Abbott for a talk at the IVF Worldwide congress on 22 September 2023. J.F.S. has received grants from the National Institutes of Health, royalties/licences from Elsevier and Prescient Medicine (SOLVD Health), consulting fees from Burroughs Wellcome Fund (BWF) and Bayer, honoraria from Magee Women's Research Institute, Wisconsin National Primate Research Centre, University of Kansas and Oakridge National Research Laboratory, Agile, Daiichi Sankyo/American Regent, and Bayer, and travel support to attend meetings for the International Academy of Human Reproduction (IAHR). J.F.S. has patents related to diagnosis and treatment of PCOS and prediction of preterm birth. J.F.S. participates on advisory boards for SOLVD Health, Wisconsin National Primate Research Centre, and FHI360, was the past President board member of the Society for Reproductive Investigation, has a leadership role for the following organizations: Scientific Advisory Board, SOLVD Health, EAB Chair for contraceptive technology initiative, FHI360, EAB member, Wisconsin National Primate Research Centre, Advisory Board for MWRI Summit, Chair of BWF NextGen Pregnancy Research Panel, Medical Executive Committee at the Howard, and Georgeanna Jones Foundation, and is Vice President, IAHR. L.P.S. has received consulting fees from Shield Pharmaceuticals, Scynexis, Organon, Natera, Celula China, AiVF, Agile, Daiichi Sankyo, American Regent, and Medicem, honoraria from Agile, Daiichi Sankyo/American Regent, and Bayer, and travel support from BD Diagnostics. L.P.S. participates on the data safety monitoring board for Astellas and is a Chair of DSMB for fezolinetant. Abbott played no role in the funding of the study or in study design, data collection, data analysis, data interpretation, or writing of the report. TRIAL REGISTRATION NUMBER: PROSPERO 2022 CRD42022356977.

Efficacy and Safety of Vamorolone Over 48 Weeks in Boys With Duchenne Muscular Dystrophy: A Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: Vamorolone is a dissociative agonist of the glucocorticoid receptor that has shown similar efficacy and reduced safety concerns in comparison with prednisone in Duchenne muscular dystrophy (DMD). This study was conducted to determine the efficacy and safety of vamorolone over 48 weeks and to study crossover participants (prednisone to vamorolone; placebo to vamorolone). METHODS: A randomized, double-blind, placebo-controlled and prednisone-controlled clinical trial of 2 doses of vamorolone was conducted in participants with DMD, in the ages from 4 years to younger than 7 years at baseline. The interventions were 2 mg/kg/d of vamorolone and 6 mg/kg/d of vamorolone for 48 weeks (period 1: 24 weeks + period 2: 24 weeks) and 0.75 mg/kg/d of prednisone and placebo for the first 24 weeks (before crossover). Efficacy was evaluated through gross motor outcomes and safety through adverse events, growth velocity, body mass index (BMI), and bone turnover biomarkers. This analysis focused on period 2. RESULTS: A total of 121 participants with DMD were randomized. Vamorolone at a dose of 6 mg/kg/d showed maintenance of improvement for all motor outcomes to week 48 (e.g., for primary outcome, time to stand from supine [TTSTAND] velocity, week 24 least squares mean [LSM] [SE] 0.052 [0.0130] rises/s vs week 48 LSM [SE] 0.0446 [0.0138]). After 48 weeks, vamorolone at a dose of 2 mg/kg/d showed similar improvements as 6 mg/kg/d for North Star Ambulatory Assessment (NSAA) (vamorolone 6 mg/kg/d-vamorolone 2 mg/kg/d LSM [SE] 0.49 [1.14]; 95% CI -1.80 to 2.78, p = 0.67), but less improvement for other motor outcomes. The placebo to vamorolone 6 mg/kg/d group showed rapid improvements after 20 weeks of treatment approaching benefit seen with 48-week 6 mg/kg/d of vamorolone treatment for TTSTAND, time to run/walk 10 m, and NSAA. There was significant improvement in linear growth after crossover in the prednisone to vamorolone 6 mg/kg/d group, and rapid reversal of prednisone-induced decline in bone turnover biomarkers in both crossover groups. There was an increase in BMI after 24 weeks of treatment that then stabilized for both vamorolone groups. DISCUSSION: Improvements of motor outcomes seen with 6 mg/kg/d of vamorolone at 24 weeks of treatment were maintained to 48 weeks of treatment. Vamorolone at a dose of 6 mg/kg/d showed better maintenance of effect compared with vamorolone at a dose of 2 mg/kg/d for most (3/5) motor outcomes. Bone morbidities of prednisone (stunting of growth and declines in serum bone biomarkers) were reversed when treatment transitioned to vamorolone. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT03439670. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that for boys with DMD, the efficacy of vamorolone at a dose of 6 mg/kg/d was maintained over 48 weeks.

Population pharmacokinetics and dose optimization of levofloxacin in elderly patients with pneumonia.

AIMS: Levofloxacin is a quinolone antibiotic with a broad antibacterial spectrum. It is frequently used in elderly patients with pneumonia. The pharmacokinetic profile of elderly patients changes with age, but data on the pharmacokinetics of levofloxacin in these patients are limited. The aim of this study was to establish a population pharmacokinetic model of levofloxacin in elderly patients with pneumonia and to optimize individualized dosing regimens based on this newly developed model. METHODS: This is a prospective, open-label pharmacokinetic study in elderly patients with pneumonia. Blood samples were collected using an opportunistic approach. The plasma concentrations of levofloxacin were determined by high-performance liquid chromatography. A population pharmacokinetic model was established using nonlinear mixed-effect model software. Monte Carlo simulations were used for dose simulation and dose optimization. RESULTS: Data from 51 elderly patients with pneumonia were used for the population pharmacokinetic analysis. A one-compartment model with first-order elimination was most suitable for describing the data, and the estimated glomerular filtration rate was the only covariate that had a significant impact on the model. The final model estimated that the mean clearance of levofloxacin in elderly patients with pneumonia was 5.26 L/h. Monte Carlo simulation results showed that the optimal dosing regimen for levofloxacin was 750 mg once a day in elderly patients with pneumonia, with a minimum inhibitory concentration of 2 mg/L. CONCLUSIONS: The population pharmacokinetic model of levofloxacin in elderly patients with pneumonia was established, and the dose optimization of levofloxacin was completed through Monte Carlo simulation.

Individualized Use of 6-Mercaptopurine in Chinese Children with ALL: A Multicenter Randomized Controlled Trial.

Continuous 6-mercaptopurine (6-MP) dose titration is necessary because of its narrow therapeutic index and frequently encountered dose-limiting hematopoietic toxicity. However, evidence-based guidelines for gene-based 6-MP dosing have not been established for Chinese children with acute lymphoblastic leukemia (ALL). This multicenter, randomized, open-label, active-controlled clinical trial randomly assigned Chinese children with low- or intermediate-risk ALL in a 1:1 ratio to receive TPMT-NUDT15 gene-based dosing of 6-MP (N = 44, 10 to 50 mg/m2 /day) or standard dosing (N = 44, 50 mg/m2 /day) during maintenance therapy. The primary end point was the incidence of 6-MP myelosuppression in both groups. Secondary end points included frequencies of 6-MP hepatotoxicity, duration of myelosuppression and leukopenia, event-free survival, and steady-state concentrations of active metabolites (6-thioguaninenucleotides and 6-methylmercaptopurine nucleotides) in erythrocytes. A 2.2-fold decrease in myelosuppression, the primary end point, was observed in the gene-based-dose group using ~ 50% of the standard initial 6-MP dose (odds ratio, 0.26, 95% confidence interval, 0.11 to 0.64, P = 0.003). Patients in the gene-based-dose group had a significantly lower risk of developing thiopurine-induced myelosuppression and leukopenia (P = 0.015 and P = 0.022, respectively). No significant differences were observed in the secondary end points of the incidence of hepatotoxicity and steady-state concentrations of active metabolites in erythrocytes between the two groups. TPMT- and NUDT15-based dosing of 6-MP will significantly contribute toward further reducing the incidence of leukopenia in Chinese children with ALL. This trial is registered at www.clinicaltrial.gov as #NCT04228393.