Bayesian Forecasting for Intravenous Tobramycin Dosing in Adults With Cystic Fibrosis Using One Versus Two Serum Concentrations in a Dosing Interval

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.

Population Pharmacokinetics and AUC-Guided Dosing of Tobramycin in the Treatment of Infections Caused by Glucose-Nonfermenting Gram-Negative Bacteria

PURPOSE

Tobramycin (TOB) exhibits variable pharmacokinetic properties due to the clinical condition of patients. This study aimed to investigate the AUC-guided dosing of TOB based on population pharmacokinetic analysis in the treatment of infections caused by Pseudomonas aeruginosa, Acinetobacter baumannii, and Stenotrophomonas maltophilia.

METHODS

This retrospective study was conducted between January 2010 and December 2020 after obtaining approval from our institutional review board. For 53 patients who received therapeutic drug monitoring of TOB, a population pharmacokinetic model was developed with covariates of estimated glomerular filtration rate using serum creatinine (eGFRcre) on clearance (CL) and weight on both CL and V_d in exponential error modeling (CL = 2.84 × [weight/70] × eGFRcre^0.568, interindividual variability [IIV] = 31.1%; V_d = 26.3 × [weight/70], IIV = 20.2%; residual variability = 28.8%).

FINDINGS

The final regression model for predicting 30-day mortality was developed with risk factors of AUC during a 24-hour period after the first dose to MIC ratio (odds ratio [OR] = 0.996; 95% CI, 0.968-1.003) and serum albumin (OR = 0.137; 95% CI, 0.022-0.632). The final regression model for predicting acute kidney injury was developed with the risk factors of C-reactive protein (OR = 1.136; 95% CI, 1.040-1.266) and AUC during a 72-hour period after the first dose (OR = 1.004; 95% CI, 1.000-1.001). A dose of 8 or 15 mg/kg was beneficial for achievement of AUC during a 24-hour period after the first dose/MIC >80 and trough concentration <1 µg/mL in patients with preserved kidney function and TOB CL >4.47 L/h/70 kg in the events of MIC of 1 or 2 µg/mL, respectively. We propose that the first dose of 15, 11, 10, 8, and 7 mg/kg for eGFRcre >90, 60 to 89, 45 to 59, 30 to 44, and 15 to 29 mL/min/1.73 m² be followed by therapeutic drug monitoring at peak and 24 hours after the first dose.

IMPLICATIONS

This study suggests that TOB use encourages the replacement of trough- and peak-targeted dosing with AUC-guided dosing.

New Recommendations of a Height-Based Dosing Regimen of Tobramycin for Cystic Fibrosis in Adults: A Population Pharmacokinetic Analysis

BACKGROUND

Acute pulmonary exacerbations (APEs) in patients with adult cystic fibrosis (CF) are treated with a beta-lactam and an aminoglycoside for activity against Pseudomonas aeruginosa (PA). Emerging drug resistance and changing pharmacokinetic profile in an aging population involve a reevaluation of tobramycin dosing recommendations. The objective of this study was to develop a population pharmacokinetic model and establish optimal dosing recommendations for tobramycin using Monte Carlo simulations.

METHODS

This retrospective clinical study and data collection were performed at the CF center of the McGill University Health Center (MUHC), Canada. Model development and simulations were performed using a nonlinear mixed-effect modeling approach (NONMEM, version 7.4.2). The ratios of maximal concentration (C max ) to the minimal inhibitory concentration (MIC) (C max /MIC ≥8 and ≥10) and area under the curve (AUC) to the MIC (AUC/MIC ≥70 and ≥100) were evaluated.

RESULTS

Adult patients with CF (n = 51) treated with tobramycin were included in the study. Plasma concentrations of tobramycin were obtained for 699 samples from the MUHC database. The two-compartmental model best described the pharmacokinetics of tobramycin. The association of patient height with the central volume of distribution significantly improved this model. Height, rather than weight, induced the best reduction in objective function. According to simulations, doses between 3.4 mg/cm and 4.4 mg/cm were necessary to achieve C max /MIC values of ≥8 and ≥10, respectively. However, higher doses were required to achieve the AUC/MIC targets.

CONCLUSIONS

This study demonstrated that height of the patients seems to be more suitable than their weight for dosing adjustments in adult patients with CF. According to this model, initial doses of tobramycin between 3.4 and 4.4 mg/cm should be recommended for patients with a median height of 164 cm and weight of 55 kg to achieve the target plasma concentrations.

Novel Applications of Biomarkers and Personalized Medicine in Cystic Fibrosis

As routine care in cystic fibrosis (CF) becomes increasingly personalized, new opportunities to further focus care on the individual have emerged. These opportunities are increasingly filled through research in tools aiding drug selection, drug monitoring and titration, disease-relevant biomarkers, and evaluation of therapeutic benefits. Herein, we will discuss such research tools presently being translated into the clinic to improve the personalization of care in CF.

Implementation and Comparison of Two Pharmacometric Tools for Model-Based Therapeutic Drug Monitoring and Precision Dosing of Daptomycin

Daptomycin is a candidate for therapeutic drug monitoring (TDM). The objectives of this work were to implement and compare two pharmacometric tools for daptomycin TDM and precision dosing. A nonparametric population PK model developed from patients with bone and joint infection was implemented into the BestDose software. A published parametric model was imported into Tucuxi. We compared the performance of the two models in a validation dataset based on mean error (ME) and mean absolute percent error (MAPE) of individual predictions, estimated exposure and predicted doses necessary to achieve daptomycin efficacy and safety PK/PD targets. The BestDose model described the data very well in the learning dataset. In the validation dataset (94 patients, 264 concentrations), 21.3% of patients were underexposed (AUC_24h < 666 mg.h/L) and 31.9% of patients were overexposed (C_min > 24.3 mg/L) on the first TDM occasion. The BestDose model performed slightly better than the model in Tucuxi (ME = -0.13 ± 5.16 vs. -1.90 ± 6.99 mg/L, p < 0.001), but overall results were in agreement between the two models. A significant proportion of patients exhibited underexposure or overexposure to daptomycin after the initial dosage, which supports TDM. The two models may be useful for model-informed precision dosing.

PBPK Modeling and Simulation and Therapeutic Drug Monitoring: Possible Ways for Antibiotic Dose Adjustment

Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.

Parametric and Nonparametric Methods in Population Pharmacokinetics: Experts' Discussion on Use, Strengths, and Limitations

Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.

PBPK Modeling and Simulation of Antibiotics Amikacin, Gentamicin, Tobramycin, and Vancomycin Used in Hospital Practice

The importance of closely observing patients receiving antibiotic therapy, performing therapeutic drug monitoring (TDM), and regularly adjusting dosing regimens has been extensively demonstrated. Additionally, antibiotic resistance is a contemporary concerningly dangerous issue. Optimizing the use of antibiotics is crucial to ensure treatment efficacy and prevent toxicity caused by overdosing, as well as to combat the prevalence and wide spread of resistant strains. Some antibiotics have been selected and reserved for the treatment of severe infections, including amikacin, gentamicin, tobramycin, and vancomycin. Critically ill patients often require long treatments, hospitalization, and require particular attention regarding TDM and dosing adjustments. As these antibiotics are eliminated by the kidneys, critical deterioration of renal function and toxic effects must be prevented. In this work, clinical data from a Portuguese cohort of 82 inpatients was analyzed and physiologically based pharmacokinetic (PBPK) modeling and simulation was used to study the influence of different therapeutic regimens and parameters as biological sex, body weight, and renal function on the biodistribution and pharmacokinetic (PK) profile of these four antibiotics. Renal function demonstrated the greatest impact on plasma concentration of these antibiotics, and vancomycin had the most considerable accumulation in plasma over time, particularly in patients with impaired renal function. Thus, through a PBPK study, it is possible to understand which pharmacokinetic parameters will have the greatest variation in a given population receiving antibiotic administrations in hospital context.