Population Pharmacokinetics and Model-Based Dosing Optimization of Teicoplanin in Pediatric Patients

Beyond One-Size-Fits-All: Tailoring Teicoplanin Regimens for Normal Renal Function Patients Using Population Pharmacokinetics and Monte Carlo Simulation

In patients with normal renal function, significant teicoplanin dose adjustments are often necessary. This study aimed to develop a population pharmacokinetic (PK) model for teicoplanin in healthy adults and use it to recommend optimal dosage regimens for patients with normal renal function. PK samples were obtained from 12 subjects and analyzed using a population approach. The derived parameters informed Monte Carlo simulations for dosing recommendations. The PK profile was best described using a three-compartment model, in which the estimated glomerular filtration rate calculated via the CKD-EPI equation and adjusted for body surface area was identified as a significant covariate affecting total clearance. For pathogens with a minimum inhibitory concentration of 1 mg/L, a loading dose (LD) of 14 mg/kg administered every 12 h for four doses, followed by a maintenance dose (MD) of 16 mg/kg administered every 24 h, is recommended. These findings indicate the need for dosage adjustments, such as increasing the LD and MD or decreasing the dosing interval of MD in patients with normal renal function. Because of the long half-life of teicoplanin and the requirement for long-term administration, therapeutic drug monitoring at strategic intervals is important to avoid nephrotoxicity associated with elevated trough concentrations.

Model-based dosing optimization and therapeutic drug monitoring practices of teicoplanin in patients with complicated or non-complicated methicillin-resistant staphylococcus aureus infection

AIMS

This study aims to establish a population pharmacokinetic (PK) model of teicoplanin in Chinese adult patients to evaluate the dosing regimen in the label sheet and optimize it.

METHODS

Nonlinear mixed-effects modelling was used to estimate PK parameters. Monte Carlo simulations were used to evaluate the attainment of various dosing regimens in achieving the target trough concentrations in patients with normal or decreased renal function.

RESULTS

A total of 115 patients were enrolled in this retrospective study. Creatinine clearance (CrCL) and albumin (ALB) were identified as covariates on the clearance of teicoplanin. For the treatment of non-complicated methicillin-resistant Staphylococcus aureus (MRSA) infections in patients with normal renal function and serum ALB concentration, the recommended dosing regimen was 600 mg q12h with five administrations as the loading dose followed by 600 mg qd as the maintenance dose; for the treatment of serious and/or complicated MRSA infections, the recommended dosing regimen was 800 mg q12h with five administrations as the loading dose followed by 800 mg qd as the maintenance dose. It is worth noting that both the loading and maintenance doses ought to be modified based on the patient's renal function and serum ALB concentration. In addition, trough concentrations of teicoplanin were significantly increased every other week.

CONCLUSIONS

Both loading dosing and maintenance dosing regimens were recommended to be adjusted according to patient's renal function and serum ALB concentration. In addition, it is necessary to perform follow-up therapeutic drug monitoring of teicoplanin at least once every week.

Personalized application of antimicrobial drugs in pediatric patients with augmented renal clearance: a review of literature

The effect of renal functional status on drug metabolism is a crucial consideration for clinicians when determining the appropriate dosage of medications to administer. In critically ill patients, there is often a significant increase in renal function, which leads to enhanced drug metabolism and potentially inadequate drug exposure. This phenomenon, known as augmented renal clearance (ARC), is commonly observed in pediatric critical care settings. The findings of the current study underscore the significant impact of ARC on the pharmacokinetics and pharmacodynamics of antimicrobial drugs in critically ill pediatric patients. Moreover, the study reveals a negative correlation between increased creatinine clearance and blood concentrations of antimicrobial drugs. The article provides a comprehensive review of ARC screening in pediatric patients, including its definition, risk factors, and clinical outcomes. Furthermore, it summarizes the dosages and dosing regimens of commonly used antibacterial and antiviral drugs for pediatric patients with ARC, and recommendations are made for dose and infusion considerations and the role of therapeutic drug monitoring.

CONCLUSION

 ARC impacts antimicrobial drugs in pediatric patients.

WHAT IS KNOWN

• ARC is inextricably linked to the failure of antimicrobial therapy, recurrence of infection, and subtherapeutic concentrations of drugs.

WHAT IS NEW

• This study provides an updated overview of the influence of ARC on medication use and clinical outcomes in pediatric patients. • In this context, there are several recommendations for using antibiotics in pediatric patients with ARC: 1) increase the dose administered; 2) prolonged or continuous infusion administration; 3) use of TDM; and 4) use alternative drugs that do not undergo renal elimination.

Pediatric Drug Development: Reviewing Challenges and Opportunities by Tracking Innovative Therapies

The paradigm of pediatric drug development has been evolving in a "carrot-and-stick"-based tactic to address population-specific issues. However, the off-label prescription of adult medicines to pediatric patients remains a feature of clinical practice, which may compromise the age-appropriate evaluation of treatments. Therefore, the United States and the European Pediatric Formulation Initiative have recommended applying nanotechnology-based delivery systems to tackle some of these challenges, particularly applying inorganic, polymeric, and lipid-based nanoparticles. Connected with these, advanced therapy medicinal products (ATMPs) have also been highlighted, with optimistic perspectives for the pediatric population. Despite the results achieved using these innovative therapies, a workforce that congregates pediatric patients and/or caregivers, healthcare stakeholders, drug developers, and physicians continues to be of utmost relevance to promote standardized guidelines for pediatric drug development, enabling a fast lab-to-clinical translation. Therefore, taking into consideration the significance of this topic, this work aims to compile the current landscape of pediatric drug development by (1) outlining the historic regulatory panorama, (2) summarizing the challenges in the development of pediatric drug formulation, and (3) delineating the advantages/disadvantages of using innovative approaches, such as nanomedicines and ATMPs in pediatrics. Moreover, some attention will be given to the role of pharmaceutical technologists and developers in conceiving pediatric medicines.

Bayesian prediction-based individualized dosing of anti-methicillin-resistant Staphylococcus aureus treatment: Recent advancements and prospects in therapeutic drug monitoring

As one of the efficient techniques for TDM, the population pharmacokinetic (popPK) model approach for dose individualization has been developed due to the rapidly growing innovative progress in computer technology and has recently been considered as a part of model-informed precision dosing (MIPD). Initial dose individualization and measurement followed by maximum a posteriori (MAP)-Bayesian prediction using a popPK model are the most classical and widely used approach among a class of MIPD strategies. MAP-Bayesian prediction offers the possibility of dose optimization based on measurement even before reaching a pharmacokinetically steady state, such as in an emergency, especially for infectious diseases requiring urgent antimicrobial treatment. As the pharmacokinetic processes in critically ill patients are affected and highly variable due to pathophysiological disturbances, the advantages offered by the popPK model approach make it highly recommended and required for effective and appropriate antimicrobial treatment. In this review, we focus on novel insights and beneficial aspects of the popPK model approach, especially in the treatment of infectious diseases with anti-methicillin-resistant Staphylococcus aureus agents represented by vancomycin, and discuss the recent advancements and prospects in TDM practice.

Optimal Use and Need for Therapeutic Drug Monitoring of Teicoplanin in Children: A Systematic Review

BACKGROUND

Teicoplanin is a glycopeptide antimicrobial that treats serious invasive infections caused by gram-positive bacteria, such as the methicillin-resistant Staphylococcus aureus. Despite some comparable advantages, there is no guideline or clinical recommendation for teicoplanin in the pediatric population, unlike vancomycin where abundant studies and the recently revised guideline on therapeutic drug level monitoring (TDM) exist.

METHODS

The systematic review was performed in accordance with the preferred reporting items for systematic reviews. Two authors (JSC and SHY) searched PubMed, Embase, and Cochrane Library databases using relevant terms independently.

RESULTS

Fourteen studies were finally included with a total of 1,380 patients. TDM was available in 2,739 samples collected in the nine studies. Dosing regimens varied widely, and eight studies used recommended dosing regimens. Timing for measuring TDM was mostly 72-96 hours or longer after the initiation of the first dose, which was expected to be a steady-state. The majority of studies had target trough levels of 10 µg/mL or above. Three studies reported that the clinical efficacy and treatment success rate of teicoplanin was 71.4%, 87.5%, and 88%. Adverse events associated with teicoplanin use were described in six studies with a focus on renal and/or hepatic impairment. Except for one study, no significant relation was noted between the incidence of adverse events and trough concentration.

CONCLUSION

Current evidence on teicoplanin trough levels in pediatric populations is insufficient due to heterogeneity. However, target trough levels with favorable clinical efficacy are achievable by recommended dosing regimen in the majority of patients.

Population pharmacokinetic analysis and dosing regimen optimization of teicoplanin in critically ill patients with sepsis

Objectives: Teicoplanin has been extensively used in the treatment for infections caused by gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA). However, current teicoplanin treatment is challenging due to relatively low and variable concentrations under standard dosage regimens. This study aimed to investigate the population pharmacokinetics (PPK) characteristics of teicoplanin in adult sepsis patients and provide recommendations for optimal teicoplanin dosing regimens. Methods: A total of 249 serum concentration samples from 59 septic patients were prospectively collected in the intensive care unit (ICU). Teicoplanin concentrations were detected, and patients' clinical data were recorded. PPK analysis was performed using a non-linear, mixed-effect modeling approach. Monte Carlo simulations were performed to evaluate currently recommended dosing and other dosage regimens. The optimal dosing regimens were defined and compared by different pharmacokinetic/pharmacodynamic parameters, including trough concentration (C_min), the ratio of 24-h area under the concentration-time curve to the minimum inhibitory concentration (AUC_0-24/MIC), as well as the probability of target attainment (PTA) and the cumulative fraction of response (CFR) against MRSA. Results: A two-compartment model adequately described the data. The final model parameter estimates for clearance, central compartment volume of distribution, intercompartmental clearance and peripheral compartment volume were 1.03 L/h, 20.1 L, 3.12 L/h and 101 L, respectively. Glomerular filtration rate (GFR) was the only covariate that significantly affected teicoplanin clearance. Model-based simulations revealed that 3 or 5 loading doses of 12/15 mg/kg every 12 h followed by a maintenance dose of 12/15 mg/kg every 24 h-72 h for patients with different renal functions were required to achieve a target C_min of 15 mg/L and a target AUC_0-24/MIC of 610. For MRSA infections, PTAs and CFRs were not satisfactory for simulated regimens. Prolonging the dosing interval may be easier to achieve the target AUC_0-24/MIC than reducing the unit dose for renal insufficient patients. Conclusion: A PPK model for teicoplanin in adult septic patients was successfully developed. Model-based simulations revealed that current standard doses may result in undertherapeutic C_min and AUC, and a single dose of at least 12 mg/kg may be needed. AUC_0-24/MIC should be preferred as the PK/PD indicator of teicoplanin, if AUC estimation is unavailable, in addition to routine detection of teicoplanin C_min on Day 4, follow-up therapeutic drug monitoring at steady-state is recommended.

Population pharmacokinetics and initial dose optimization of tacrolimus in children with severe combined immunodeficiency undergoing hematopoietic stem cell transplantation

The present study aimed to explore the population pharmacokinetics and initial dose optimization of tacrolimus in children with severe combined immunodeficiency (SCID) undergoing hematopoietic stem cell transplantation (HSCT). Children with SCID undergoing HSCT treated with tacrolimus were enrolled for analysis. Population pharmacokinetics of tacrolimus was built up by a nonlinear mixed-effects model (NONMEM), and initial dose optimization of tacrolimus was simulated with the Monte Carlo method in children weighing <20 kg at different doses. A total of 18 children with SCID undergoing HSCT were included for analysis, with 130 tacrolimus concentrations. Body weight was included as a covariable in the final model. Tacrolimus CL/F was 0.36–0.26 L/h/kg from body weights of 5–20 kg. Meanwhile, we simulated the tacrolimus concentrations using different body weights (5–20 kg) and different dose regimens (0.1–0.8 mg/kg/day). Finally, the initial dose regimen of 0.6 mg/kg/day tacrolimus was recommended for children with SCID undergoing HSCT whose body weights were 5–20 kg. It was the first time to establish tacrolimus population pharmacokinetics in children with SCID undergoing HSCT; in addition, the initial dose optimization of tacrolimus was recommended.

Effects of cimetidine on ciclosporin population pharmacokinetics and initial dose optimization in aplastic anemia patients

The present study aimed to explore the effects of cimetidine on ciclosporin population pharmacokinetics and initial dose optimization in aplastic anemia patients. Aplastic anemia patients were used to establish a population pharmacokinetic model by the nonlinear mixed effect (NONMEM), and concentrations of ciclosporin were simulated by Monte Carlo method. With the same weight, the ciclosporin clearance rates were 0.387:1 in patients with or without cimetidine, respectively. In the measured ciclosporin concentrations, compared to aplastic anemia patients without cimetidine, ciclosporin concentrations were higher in patients with cimetidine (P < 0.01). Further research found that at the same body weight and same dose, ciclosporin concentrations in aplastic anemia patients with cimetidine were indeed higher than those in patients without cimetidine (P < 0.01). The initial recommended ciclosporin dose for patients without cimetidine were 7mg/kg splited into two doses for weight of 40-60kg, and 6mg/kg splited into two doses for weight of 60-100kg. The patients with cimetidine were recommended to take 3mg/kg ciclosporin splited into two doses for weight of 40-100kg. It was the first time to explore the effects of cimetidine on ciclosporin population pharmacokinetics and initial dose optimization in aplastic anemia patients. Patients coadministration of cimetidine, may need low ciclosporin dose.

Construction and Interpretation of Prediction Model of Teicoplanin Trough Concentration via Machine Learning

Objective

To establish an optimal model to predict the teicoplanin trough concentrations by machine learning, and explain the feature importance in the prediction model using the SHapley Additive exPlanation (SHAP) method.

Methods

A retrospective study was performed on 279 therapeutic drug monitoring (TDM) measurements obtained from 192 patients who were treated with teicoplanin intravenously at the First Affiliated Hospital of Army Medical University from November 2017 to July 2021. This study included 27 variables, and the teicoplanin trough concentrations were considered as the target variable. The whole dataset was divided into a training group and testing group at the ratio of 8:2, and predictive performance was compared among six different algorithms. Algorithms with higher model performance (top 3) were selected to establish the ensemble prediction model and SHAP was employed to interpret the model.

Results

Three algorithms (SVR, GBRT, and RF) with high R² scores (0.676, 0.670, and 0.656, respectively) were selected to construct the ensemble model at the ratio of 6:3:1. The model with R² = 0.720, MAE = 3.628, MSE = 22.571, absolute accuracy of 83.93%, and relative accuracy of 60.71% was obtained, which performed better in model fitting and had better prediction accuracy than any single algorithm. The feature importance and direction of each variable were visually demonstrated by SHAP values, in which teicoplanin administration and renal function were the most important factors.

Conclusion

We firstly adopted a machine learning approach to predict the teicoplanin trough concentration, and interpreted the prediction model by the SHAP method, which is of great significance and value for the clinical medication guidance.

Pharmacokinetics and pharmacodynamics of peptide antibiotics

Antimicrobial resistance is a major global health challenge. As few new efficacious antibiotics will become available in the near future, peptide antibiotics continue to be major therapeutic options for treating infections caused by multidrug-resistant pathogens. Rational use of antibiotics requires optimisation of the pharmacokinetics and pharmacodynamics for the treatment of different types of infections. Toxicodynamics must also be considered to improve the safety of antibiotic use and, where appropriate, to guide therapeutic drug monitoring. This review focuses on the pharmacokinetics/pharmacodynamics/toxicodynamics of peptide antibiotics against multidrug-resistant Gram-negative and Gram-positive pathogens. Optimising antibiotic exposure at the infection site is essential for improving their efficacy and minimising emergence of resistance.

Physiologically Based Pharmacokinetic Modeling and Dose Adjustment of Teicoplanin in Pediatric Patients With Renal Impairment

The pharmacokinetics of teicoplanin differs in children as compared with adults, and especially in renally impaired pediatric patients. Inappropriate empirical antibacterial therapy may lead to treatment-related antibacterial resistance and increased toxicity, making adjustment of the dosage regimen essential. In the present study, physiologically based pharmacokinetic (PBPK) models were developed to define the appropriate dosage regimen for pediatric patients with differing renal function. Our PBPK models accurately predicted teicoplanin exposures in both adult and pediatric subjects after single and multiple intravenous infusions, with a <1.36-fold error between predicted and observed data, and all observed data were within minimal and maximal data of the corresponding population simulation. The area under the plasma concentration-time curve was predicted to increase 1.25-fold, 1.95-fold, and 2.82-fold in pediatric patients with mild, moderate, and severe renal impairment, respectively, relative to that of healthy children. Subsequently, the results of Monte Carlo simulations indicated that the recommended dosing of 12, 9.5, 6, and 4 mg/kg at 12-hour intervals would be appropriate in pediatric patients with normal renal function and in those with mild, moderate, and severe renal impairment, respectively, at a susceptible minimum inhibitory concentration <2 mg/L. In conclusion, our PBPK model with an incorporated Monte Carlo simulation can provide improved guidance on dosing in pediatric patients with differing renal function and provide a basis for precision therapy with teicoplanin.