Therapeutic Drug Monitoring Based on Early Measurements of Serum Teicoplanin Levels in Japanese Patients

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.

Model-informed precision dosing of teicoplanin for the rapid achievement of the target area under the concentration-time curve: A simulation study

Teicoplanin, a glycopeptide antimicrobial, is recommended for therapeutic drug monitoring, but it remains unclear how to target the area under the concentration-time curve (AUC). This simulation study purposed to demonstrate the potential of the Bayesian forecasting approach for the rapid achievement of the target AUC for teicoplanin. We generated concordant and discordant virtual populations against a Japanese population pharmacokinetic model. The predictive performance of the Bayesian posterior AUC in limited sampling on the first day against the reference AUC was evaluated as an acceptable target AUC ratio within the range of 0.8-1.2. In the concordant population, the probability for the maximum a priori or Bayesian posterior AUC on the first day (AUC_0-24 ) was 61.3% or more than 77.0%, respectively. The Bayesian posterior AUC on the second day (AUC_24-48 ) was more than 75.1%. In the discordant population, the probability for the maximum a priori or Bayesian posterior AUC_0-24 was 15.5% or 11.7-80.7%, respectively. The probability for the maximum a priori or Bayesian posterior AUC_24-48 was 23.4%, 30.2-82.1%. The AUC at steady-state (AUC_SS ) was correlated with trough concentration at steady-state, with a coefficient of determination of 0.930; the coefficients on days 7 and 4 were 0.442 and 0.125, respectively. In conclusion, this study demonstrated that early sampling could improve the probability of AUC_0-24 and AUC_24-48 but did not adequately predict AUC_SS . Further studies are necessary to apply early sampling-based model-informed precision dosing in the clinical settings.

Performance of Area under the Concentration-Time Curve Estimations of Vancomycin with Limited Sampling by a Newly Developed Web Application

PURPOSE

Therapeutic drug monitoring guided by the area under the concentration-time curve (AUC-guided TDM) is recommended for vancomycin. However, validated efficient software remains elusive to popularize AUC-guided TDM in Japan. The aim of this study was to validate a newly developed web application, PAT, for AUC estimation.

METHODS

PAT was developed on the R ver. 3.6.2 platform for use with mobile phones and personal computers. AUC estimated by PAT (AUC_PAT) was evaluated against the reference AUC (AUC_REF) calculated with the log-linear trapezoidal rule using eight measured concentrations, or against AUC (AUC_BM-P) calculated using an evaluated available software with clinical data.

RESULTS

Investigating the best sampling points with limited sampling, PAT produced the least bias using two concentrations at 1 h and 11 h after the end of infusion (slope 1.18, intercept -15.57, median AUC_PAT/AUC_REF 0.93 [range 0.81-1.24]), where only one estimation (6%) was out of the predetermined acceptable range of 0.8-1.2. Employment of only a trough concentration was more biased (AUC_PAT/AUC_REF range 0.73-1.30 for 11 h, AUC_PAT/AUC_REF range 0.62-1.40 for 23 h). In comparison with the evaluated software, AUC_PAT was not biased against the AUC_BM-P (slope 1.04, intercept -15.80, median AUC_PAT/AUC_BM-P 1.00 [range 0.86-1.10]).

CONCLUSIONS

The new application using two concentrations was appropriately validated and might be efficient in popularizing the AUC-guided TDM of vancomycin.

Development of Vancomycin Dose Individualization Strategy by Bayesian Prediction in Patients Receiving Continuous Renal Replacement Therapy

PURPOSE

Vancomycin (VCM) concentration is often out of therapeutic range (10-20 μg/ml) in patients receiving continuous renal replacement therapy (CRRT). The purposes of this study were to develop a practical VCM population pharmacokinetic (PPK) model and to evaluate the potential of Bayesian prediction-based therapeutic drug monitoring (Bayes-TDM) in VCM dose individualization for patients receiving CRRT.

METHODS

We developed a VCM PPK model using 80 therapeutic concentrations in 17 patients receiving CRRT. Bayes-TDM with the VCM PPK model was evaluated in 23 patients after PPK modeling.

RESULTS

We identified the covariates reduced urine output (RUO, <0.5 ml/kg/h) and effluent flow rate of CRRT for the VCM PPK model. The mean VCM non CRRT clearance (CL_nonCRRT) was 2.12 l/h. RUO lowered CL_nonCRRT to 0.34 l/h. The volume of distribution was 91.3 l/70 kg. The target concentration attainment rate by Bayes-TDM was higher (87.0%) than that by the PPK modeling period (53.8%, P = 0.046). The variance of the second measured concentrations by the Bayes-TDM was lower (11.5, standard deviation: 3.4 μg/ml) than that by the PPK modeling period (50.5, standard deviation: 7.1 μg/ml, P = 0.003).

CONCLUSIONS

Bayes-TDM could be a useful tool for VCM dose individualization in patients receiving CRRT.

LC-MS for Simultaneous Determination of Vancomycin and Teicoplanin in Patient Plasma and its Application to Therapeutic Drug Monitoring

Background:

Therapeutic drug monitoring is recommended for patients taking vancomycin and teicoplanin to ensure pharmaceutical efficacy and prevent toxicity. Only few studies were reported regarding the simultaneous determination of vancomycin and teicoplanin in human plasma.

Objective:

The study aimed at developing and validating a Liquid Chromatography-Mass Spectrometry (LC-MS) method for simultaneous determination and therapeutic drug monitoring of vancomycin and teicoplanin in patients with severe infection.

Method:

Plasma was processed by protein precipitation extraction. The analytes were separated on a C18 column by gradient elution with 0.1% formic acid and acetonitrile as mobile phase and measured by electrospray ionization source in positive selective ion monitoring mode at m/z 724.7 (vancomycin), 940.7 (teicoplanin) and 329.0 (bergenin). The plasma samples (104) were obtained from patients who were taking vancomycin or teicoplanin for further analysis.

Results:

The calibration curves were linear within the range of 0.25–40 µg/mL for vancomycin, and 0.5-40 µg/mL for teicoplanin. Either inter- or intra-day precision was less than 10.01 %. The extraction recoveries ranged from 89.99 to 94.29% for vancomycin and from 39.83 to 40.16 % for teicoplanin. Vancomycin and teicoplanin in plasma were stable at various storage conditions. The measured mean trough concentrations were 12.313 µg/mL for vancomycin and 8.765 µg/mL for teicoplanin.

Conclusion:

This method was successfully applied to therapeutic drug monitoring of vancomycin and teicoplanin in patients. It is with great clinic value for monitoring and predicting the individual response of patients under treatment.

Improvement of Predictivity of Teicoplanin Serum Trough Concentrations at Steady State Calculated by Vancomycin Pharmacokinetic Parameter

 According to a recent study and meta-analysis, trough levels of >10 μg/mL teicoplanin (TEIC) may be acceptable for the treatment of uncomplicated infection, but no method of TEIC personalized medicine has been established. Vancomycin (VCM) and TEIC are glycopeptide antibiotic agents effective against methicillin-resistance Staphyloccocus aureus. This study aimed to establish TEIC personalized medicine at a steady state calculated by VCM pharmacokinetic parameters. Bayesian forecasting and population mean methods were employed to estimate individual total VCM clearance (CL) using existing population pharmacokinetics (PPK) parameter, and the differences between the CL calculated by these two methods were defined as ΔCL. Serum drug concentration data for patients treated with TEIC were collected at a steady state concentration (>96 h post infusion). There was a significant relationship between the prediction error of TEIC trough level and ΔCL. The relation between ΔCL and TEIC trough concentration at steady state was used to develop the following equation to determine the maintenance dose: TEIC (μg/mL)=1.1119X-6.124ΔCL+3.9164 (X is defined as TEIC trough concentration calculated from the PPK parameter). The results of this study indicated that it is possible to improve the prediction error of TEIC trough concentration at a steady state for patients who have received VCM therapy.

Effects of teicoplanin on cell number of cultured cell lines

Teicoplanin is a glycopeptide antibiotic with a wide variation in human serum half-life. It is also a valuable alternative of vancomycin. There is however no study on its effect on cultured cells. The aim of the present study was to test the effect of teicoplanin on cultured cell lines CHO, Jurkat E6.1 and MCF-7. The cultured cells were exposed to teicoplanin at final concentrations of 0-11000 μg/ml for 24 hours. To determine cell viability, the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test was performed. At low concentrations of teicoplanin the numbers of cultured cells (due to cell proliferation) were increased in the three cell lines examined. The maximum cell proliferation rates were observed at concentrations of 1000, 400, and 200 μg/ml of teicoplanin for CHO, MCF-7 and Jurkat cell lines, respectively. Cell toxicity was observed at final concentrations over 2000, 6000, and 400 μg/ml of teicoplanin for CHO, MCF-7 and Jurkat cell lines, respectively. A dose-dependent manner of cell toxicity was observed. Our present findings indicated that teicoplanin at clinically used concentrations induced cell proliferation. It should therefore be used cautiously, particularly in children, pregnant women and patients with cancer.