Optimization of Vancomycin Initial Dosing Regimen in Neonates Using an Externally Evaluated Population Pharmacokinetic Model.

BACKGROUND: Vancomycin therapeutic monitoring guidelines were revised in March 2020, and a population pharmacokinetics-guided Bayesian approach to estimate the 24-hour area under the concentration-time curve to the minimum inhibitory concentration ratio has since been recommended instead of trough concentrations. To comply with these latest guidelines, we evaluated published population pharmacokinetic models of vancomycin using an external dataset of neonatal patients and selected the most predictive model to develop a new initial dosing regimen. METHODS: The models were identified from the literature and tested using a retrospective dataset of Canadian neonates. Their predictive performance was assessed using prediction- and simulation-based diagnostics. Monte Carlo simulations were performed to develop the initial dosing regimen with the highest probability of therapeutic target attainment. RESULTS: A total of 144 vancomycin concentrations were derived from 63 neonates in the external population. Five of the 28 models retained for evaluation were found predictive with a bias of 15% and an imprecision of 30%. Overall, the Grimsley and Thomson model performed best, with a bias of -0.8% and an imprecision of 20.9%; therefore, it was applied in the simulations. A novel initial dosing regimen of 15 mg/kg, followed by 11 mg/kg every 8 hours should favor therapeutic target attainment. CONCLUSIONS: A predictive population pharmacokinetic model of vancomycin was identified after an external evaluation and used to recommend a novel initial dosing regimen. The implementation of these model-based tools may guide physicians in selecting the most appropriate initial vancomycin dose, leading to improved clinical outcomes.

Development and Evaluation of a Height-Based Tobramycin Initial Dosing Nomogram for the Treatment of Adult Cystic Fibrosis Pulmonary Exacerbations.

ABSTRACT: Tobramycin is widely used to treat pulmonary exacerbations of cystic fibrosis. Height has been previously found to be significantly more predictive of tobramycin pharmacokinetics than body weight. This study aimed to develop a height-based initial dosing nomogram and evaluate its performance in peak concentration (Cmax) precision relative to standard and fixed dosing. Monte Carlo simulations were performed to develop a nomogram representing the doses required to reach Cmax targets at different heights. Cmax data observed at 2 clinical centers [McGill University Health Centre (MUHC) and Institut universitaire de cardiologie et pneumologie de Québec (IUCPQ-UL)] were compared with population-predicted Cmax using the doses derived from the nomogram alongside a fixed dose. Height-based dosing resulted in significantly less variable-predicted Cmax values [coefficient of variation (CV) MUHC = 15.7% and IUCPQ-UL = 10.8%] than the Cmax values observed in clinical practice (CV MUHC = 30.0% and CV IUCPQ-UL = 26.9%) and predicted Cmax values obtained from a fixed dose (CV MUHC = 21.2% and CV IUCPQ-UL = 16.3%). An initial dosing nomogram was developed to help reduce pharmacokinetic variability in the observed Cmax. More precise dosing would allow for better clinical outcomes in adult patients with cystic fibrosis.

Consideration of height-based tobramycin dosing regimens for the treatment of adult cystic fibrosis pulmonary exacerbations.

AIMS: Some population pharmacokinetic models have been developed using height to explain some of the interindividual variability in tobramycin pharmacokinetics in cystic fibrosis patients. However, their predictive performance when extrapolated to other clinical centres is unclear. Therefore, the aim of this study was to externally evaluate the predictability of tobramycin population pharmacokinetic models with an independent dataset and perform simulations using previously recommended height-based dosing regimens. METHODS: A literature search was conducted through the PubMed database to identify relevant population pharmacokinetic models. Tobramycin plasma concentration data from April 2014 to November 2019 were retrospectively collected from the Institut universitaire de cardiologie et de pneumologie de Québec, Canada. External evaluations were performed using NONMEM® v7.5 and RStudio® v1.3.1073. Monte Carlo simulations were performed to evaluate the probability of target attainment of Cmax /MIC ratios for several dosing regimens. RESULTS: The validation dataset included 27 patients and 143 concentration samples. Three models were evaluated. Only the ones by Crass et al. and Alghanem et al. performed satisfactorily in terms of prediction-based diagnostics with MDPE values of -3.4% and 29.3% and MDAPE values of 19.0 and 29.5%, respectively. In simulation-based evaluations, both pcVPC and NPDE showed no evidence of model misspecification. Our simulations suggest that patients treated with a once-daily dose of 3.4 mg/cm should produce peak and trough levels consistent with current guidelines. CONCLUSION: Our results show that the models by Crass et al. and Alghanem et al. are appropriate for simulation-based applications to aid individualized dosing in our population and that height-based dosing regimens could be considered in cystic fibrosis patients.

Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data.

Improved pharmacokinetics/pharmacodynamics (PK/PD) prediction in the early stages of drug development is essential to inform lead optimization strategies and reduce attrition rates. Recently, there have been significant advancements in the development of new in vitro and in vivo strategies to better characterize pharmacokinetic properties and efficacy of drug leads. Herein, we review advances in experimental and mathematical models for clearance predictions, advancements in developing novel tools to capture slowly metabolized drugs, in vivo model developments to capture human etiology for supporting drug development, limitations and gaps in these efforts, and a perspective on the future in the field.

Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?

BACKGROUND AND OBJECTIVES: Precision dosing requires selecting the appropriate population pharmacokinetic model, which can be assessed through external evaluations (EEs). The lack of understanding of how different study design factors influence EE study outcomes makes it challenging to select the most suitable model for clinical use. This study aimed to evaluate the impact of sample size, sampling strategy, and handling of concentrations below the lower limit of quantification (BLQ) on the outcomes of EE for four population pharmacokinetic models using vancomycin and tobramycin as examples. METHODS: Three virtual patient populations undergoing vancomycin or tobramycin therapy were simulated with varying sample size and sampling scenarios. The three approaches used to handle BLQ data were to (1) discard them, (2) impute them as LLOQ/2, or (3) use a likelihood-based approach. EEs were performed with NONMEM and R. RESULTS: Sample size did not have an important impact on the EE results for a given scenario. Increasing the number of samples per patient did not improve predictive performance for two out of the three evaluated models. Evaluating a model developed with rich sampling did not result in better performance than those developed with regular therapeutic drug monitoring. A likelihood-based method to handle BLQ samples impacted the outcomes of the EE with lower bias for predicted troughs. CONCLUSIONS: This study suggests that a large sample size may not be necessary for an EE study, and models selected based on TDM may be more generalizable. The study highlights the need for guidelines for EE of population pharmacokinetic models for clinical use.

Risk Factors for Retinal Detachment in Marfan Syndrome After Pediatric Lens Removal.

PURPOSE: To determine retinal detachment (RD) risk factors after lens removal surgery in children with Marfan syndrome (MS). DESIGN: Retrospective, case control study. METHODS: This was an institutional case series including children (age <18 years) with MS who underwent lens removal surgery. Clinical and surgical characteristics were extracted from the children's electronic files: age, axial length (AL), gender, number of surgeries received, intraocular lens (IOL) implantation at the first surgery, complete removal of the capsular bag, and final best-corrected visual acuity. Risk factors associated with RD occurrence were identified. RESULTS: Among 158 eyes included (85 children), 35 eyes (22.2%) developed RD during follow-up. Bilateral detachment occurred in 11 patients (45.8%). Age at the time of the lens removal surgery was not different between groups. Children in the RD group had a higher AL (P < .001), longer follow-up, IOL implantation, and capsular residue. Multivariate analysis identified capsular residue (odds ratio, 16.8; 95% CI, 1.9-148.8; P = .01) and AL (odds ratio, 1.3; 95% CI, 1.01-1.7; P = .03) as predictors for RD. CONCLUSIONS: Children with MS and increased AL were more likely to develop an RD after lens surgery. When considering lens removal surgery in a pediatric population presenting with MS, a complete capsular removal seemed to be the safer option regarding RD risk.

External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps.

Predicting drug exposures using population pharmacokinetic models through Bayesian forecasting software can improve individual pharmacokinetic/pharmacodynamic target attainment. However, selecting the most adapted model to be used is challenging due to the lack of guidance on how to design and interpret external evaluation studies. The confusion around the choice of statistical metrics and acceptability criteria emphasises the need for further research to fill this methodological gap as there is an urgent need for the development of standards and guidelines for external evaluation studies. Herein we discuss the scientific challenges faced by pharmacometric researchers and opportunities for future research with a focus on antibiotics.

Antibiotics in Adult Cystic Fibrosis Patients: A Review of Population Pharmacokinetic Analyses.

BACKGROUND: Lower respiratory tract infections are common in adult patients with cystic fibrosis (CF) and are frequently caused by Pseudomonas aeruginosa, resulting in chronic lung inflammation and fibrosis. The progression of multidrug-resistant strains of P. aeruginosa and alterations in the pharmacokinetics of many antibiotics in CF make optimal antimicrobial therapy a challenge, as reflected by high between- and inter-individual variability (IIV). OBJECTIVES: This review provides a synthesis of population pharmacokinetic models for various antibiotics prescribed in adult CF patients, and aims at identifying the most reported structural models, covariates and sources of variability influencing the dose-concentration relationship. METHODS: A literature search was conducted using the PubMed database, from inception to August 2020, and articles were retained if they met the inclusion/exclusion criteria. RESULTS: A total of 19 articles were included in this review. One-, two- and three-compartment models were reported to best describe the pharmacokinetics of various antibiotics. The most common covariates were lean body mass and creatinine clearance. After covariate inclusion, the IIV (range) in total body clearance was 27.2% (10.40-59.7%) and 25.9% (18.0-33.9%) for ß-lactams and aminoglycosides, respectively. IIV in total body clearance was estimated at 36.3% for linezolid and 22.4% for telavancin. The IIV (range) in volume of distribution was 29.4% (8.8-45.9%) and 15.2 (11.6-18.0%) for ß-lactams and aminoglycosides, respectively, and 26.9% for telavancin. The median (range) of residual variability for all studies, using a combined (proportional and additive) model, was 12.7% (0.384-30.80%) and 0.126 mg/L (0.007-1.88 mg/L), respectively. CONCLUSION: This is the first review that highlights key aspects of different population pharmacokinetic models of antibiotics prescribed in adult CF patients, effectively proposing relevant information for clinicians and researchers to optimize antibiotic therapy in CF.