Identification of factors influencing the pharmacokinetics of voriconazole and the optimization of dosage regimens based on Monte Carlo simulation in patients with invasive fungal infections

Objectives: There have been few clinical studies of ECMO-related alterations of the PK of meropenem and conflicting results were reported. This study investigated the pharmacokinetics (PK) of meropenem in critically ill adult patients receiving extracorporeal membrane oxygenation (ECMO) and used Monte Carlo simulations to determine appropriate dosage regimens.Methods: After a single 0.5 or 1 g dose of meropenem, 7 blood samples were drawn. A population PK model was developed using nonlinear mixed-effects modeling. The probability of target attainment was evaluated using Monte Carlo simulation. The following treatment targets were evaluated: the cumulative percentage of time during which the free drug concentration exceeds the minimum inhibitory concentration of at least 40% (40% fT>MIC), 100% fT>MIC, and 100% fT>4xMIC.Results: Meropenem PK were adequately described by a two-compartment model, in which creatinine clearance and ECMO flow rate were significant covariates of total clearance and central volume of distribution, respectively. The Monte Carlo simulation predicted appropriate meropenem dosage regimens. For a patient with a creatinine clearance of 50–130 ml/min, standard regimen of 1 g q8h by i. v. infusion over 0.5 h was optimal when a MIC was 4 mg/L and a target was 40% fT>MIC. However, the standard regimen did not attain more aggressive target of 100% fT>MIC or 100% fT>4xMIC.Conclusion: The population PK model of meropenem for patients on ECMO was successfully developed with a two-compartment model. ECMO patients exhibit similar PK with patients without ECMO. If more aggressive targets than 40% fT>MIC are adopted, dose increase may be needed.

Download Full-text

Observational Study of the Clinical Efficacy of Voriconazole and Its Relationship to Plasma Concentrations in Patients

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.01083-10 ◽

2011 ◽

Vol 55 (10) ◽

pp. 4782-4788 ◽

Cited By ~ 139

Author(s):

Peter F. Troke ◽

Hans P. Hockey ◽

William W. Hope

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Clinical Response ◽

Response Rate ◽

Fungal Infections ◽

Lower Probability ◽

Therapeutic Drug ◽

The Impact ◽

The Relationship ◽

Probability Of Response

ABSTRACTVoriconazole is approved for treating invasive fungal infections. We examined voriconazole exposure-response relationships for patients from nine published clinical trials. The relationship between the mean voriconazole plasma concentration (Cavg) and clinical response and between the freeCavg/MIC ratio versus the clinical response were explored using logistic regression. The impact of covariates on response was also assessed. Monte Carlo simulation was used to estimate the relationship between the trough concentration/MIC ratio and the probability of response. The covariates individually related to response were as follows: study (P< 0.001), therapy (primary/salvage,P< 0.001), primary diagnosis (P< 0.001), race (P= 0.004), baseline bilirubin (P< 0.001), baseline alkaline phosphatase (P= 0.014), and pathogen (yeast/mold,P< 0.001). TheCavgfor 72% of the patients was 0.5 to 5.0 μg/ml, with the maximum response rate (74%) at 3.0 to 4.0 μg/ml. TheCavgshowed a nonlinear relationship to response (P< 0.003), with a lower probability at the extremes. For patients withCavg< 0.5 μg/ml, the response rate was 57%. The lowest response rate (56%) was seen with aCavg≥ 5.0 μg/ml (18% of patients) and was associated with significantly lower mold infection responses compared to yeasts (P< 0.001) but not with voriconazole toxicity. Higher freeCavg/MIC ratios were associated with a progressively higher probability of response. Monte Carlo simulation suggested that a trough/MIC ratio of 2 to 5 is associated with a near-maximal probability of response. The probability of response is lower at the extremes ofCavg. Patients with higher freeCavg/MIC ratios have a higher probability of clinical response. A trough/MIC ratio of 2 to 5 can be used as a target for therapeutic drug monitoring.

Download Full-text

Pharmacokinetic/pharmacodynamic analysis of weight- and height-scaled tobramycin dosage regimens for patients with cystic fibrosis

Journal of Antimicrobial Chemotherapy ◽

10.1093/jac/dkz192 ◽

2019 ◽

Vol 74 (8) ◽

pp. 2311-2317

Author(s):

S S Alghanem ◽

D J Touw ◽

A H Thomson

Keyword(s):

Cystic Fibrosis ◽

Pseudomonas Aeruginosa ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Simulated Dataset ◽

Dosage Regimens ◽

Pharmacodynamic Analysis ◽

Dosing Regimens ◽

Lower Height ◽

Higher Doses

Abstract Objectives To determine the outcomes of weight- and height-based tobramycin dosing regimens for patients with cystic fibrosis (CF). Methods A simulated dataset of 5000 patients based on 331 patients with CF was created using NONMEM. Pharmacokinetic (PK) parameters were derived for each patient from a published model using Monte Carlo simulation. The abilities of 10 and 12 mg/kg/day and 3 and 4 mg/cm/day to achieve standard and extended Cmax (20–30 and 20–40 mg/L) and AUC0–24 (80–120 and 80–150 mg·h/L) targets were evaluated. PK/pharmacodynamic (PK/PD) indices were a Cmax/MIC ratio ≥10 and an AUC0–24/MIC ratio ≥110. For these indices and a range of MICs, cumulative fractions of response (CFRs) for Pseudomonas aeruginosa were also determined. Results More patients achieved standard Cmax and AUC0–24 targets with 3 mg/cm/day (64% and 62%, respectively) than with 10 mg/kg/day (43% and 48%, respectively). AUC0–24 estimates >120 mg·h/L were more common with weight-based dosing. With higher doses, 72% achieved high target peaks with 4 mg/cm/day and 65% with 12 mg/kg/day. For the Cmax/MIC index, the maximal MIC for the target microorganism was 2 mg/L with lower doses, 2.5 mg/L with higher doses and 0.5 mg/L for AUC0–24/MIC-based regimens. The CFR for all regimens was >90% for Cmax targets and 66% to 79% for AUC0–24 targets. Conclusions A tobramycin dose of 3 mg/cm/day rather than 10 mg/kg/day achieved similar PK/PD outcomes but dose and AUC0–24 ranges were narrower and the incidence of high AUC0–24 values was lower. Height-based doses should therefore be considered for patients with CF.

Download Full-text

Evaluating amikacin dosage regimens in intensive care unit patients: A pharmacokinetic/pharmacodynamic analysis using Monte Carlo simulation

International Journal of Antimicrobial Agents ◽

10.1016/j.ijantimicag.2013.04.021 ◽

2013 ◽

Vol 42 (2) ◽

pp. 155-160 ◽

Cited By ~ 10

Author(s):

Hinojal Zazo ◽

Ana Martín-Suárez ◽

José M. Lanao

Keyword(s):

Intensive Care Unit ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Intensive Care ◽

Dosage Regimens ◽

Pharmacodynamic Analysis

Download Full-text

Population Pharmacokinetics of Voriconazole in Adults

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.00702-11 ◽

2011 ◽

Vol 56 (1) ◽

pp. 526-531 ◽

Cited By ~ 62

Author(s):

William W. Hope

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Healthy Volunteers ◽

Clinical Response ◽

Population Pharmacokinetics ◽

Drug Exposure ◽

Fungal Infections ◽

Parameter Estimates ◽

Pharmacokinetic Studies ◽

Pharmacokinetic Data

ABSTRACTVoriconazole is a first-line agent for the treatment of invasive fungal infections. The pharmacology of voriconazole is characterized by extensive interindividual variability and nonlinear pharmacokinetics. The population pharmacokinetics of voriconazole in 64 adults is described. The patient population consisted of 21 healthy volunteers, who received a range of intravenous (i.v.) and oral voriconazole regimens, and 43 patients with proven or probable invasive aspergillosis, who received the currently licensed dosage. Voriconazole concentrations were measured using high-performance liquid chromatography (HPLC). The pharmacokinetic data were modeled using a nonparametric methodology and with a nonlinear pharmacokinetic structural model. The extent and consequences of pharmacokinetic variability were explored using Monte Carlo simulation. The relationship between drug exposure and clinical response was explored using logistic regression. Optimal sampling times were identified using D-optimal design. The fit of the nonlinear model was acceptable. Data from the healthy volunteers provided robust estimates forKmand the maximum rate of enzyme activity (Vmax). The Bayesian parameter estimates were more variable and statistically different in patients than in volunteers. There was a linear relationship between the trough concentration and area under the concentration-time curve (AUC0-12). There was no relationship between the AUC0-12and clinical response. The original parameter values were readily recapitulated using Monte Carlo simulation. Initial i.v. dosing resulted in higher AUC0-12and trough concentrations compared with oral dosing. Sample collection times of 1, 2, 3, 4, 8, and 12 h after an i.v. infusion are maximally informative times for future pharmacokinetic studies.

Download Full-text