TDMx: A novel web-based open-access support tool for optimising antimicrobial dosing regimens in clinical routine

Linezolid in liver failure: exploring the value of the maximal liver function capacity (LiMAx) test in a pharmacokinetic pilot study

Patients in the intensive care unit frequently require antibiotic treatment. Liver impairment poses substantial challenges for dose selection in these patients. The aim of the present pilot study was to assess the novel maximal liver function capacity (LiMAx test) in comparison with conventional liver function markers as covariates of drug clearance in liver failure using linezolid as a model drug. A total of 28 patients with different degrees of liver failure were recruited. LiMAx test as well as plasma, dialysate and urine sampling were performed under linezolid steady-state therapy (600 mg twice daily). NONMEM^® was used for a pharmacometric analysis in which the different clearance routes of linezolid were elucidated. Linezolid pharmacokinetics was highly variable in patients with liver failure. The LiMAx score displayed the strongest association with non-renal clearance (CL_non-renal) [ = 4.46∙(body weight/57.9) ^0.75∙(LiMAx/221.5)^0.388 L/h], which reduced interindividual variability in CL_non-renal from 46.6% to 33.6%, thereby being superior to other common markers of liver function (international normalised ratio, gamma-glutaryl transferase, bilirubin, thrombocytes, alanine aminotransferase, aspartate aminotransferase). For LiMAx < 100 µg/kg/h, 64% of linezolid trough concentrations were above the recommended trough concentration of 8 mg/L, indicating the necessity of therapeutic drug monitoring in these patients. This is the first pilot application of the LiMAx test in a pharmacokinetic (PK) study demonstrating its potential to explain PK variability in linezolid clearance. Further studies with a larger patient collective and further drugs are highly warranted to guide dosing in patients with severe liver impairment.

Utility of Microdialysis in Infectious Disease Drug Development and Dose Optimization

Adequate drug penetration to a site of infection is absolutely imperative to ensure sufficient antimicrobial treatment. Microdialysis is a minimally invasive, versatile technique, which can be used to study the penetration of an antiinfective agent in virtually any tissue of interest. It has been used to investigate drug distribution and pharmacokinetics in variable patient populations, as a tool in dose optimization, a potential utility in therapeutic drug management, and in the study of biomarkers of disease progression. While all of these applications have not been fully explored in the field of antiinfectives, this review provides an overview of how microdialysis has been applied in various phases of drug development, a focus on the specific applications in the subspecialties of infectious disease (treatment of bacterial, fungal, viral, parasitic, and mycobacterial infections), and developing applications (biomarkers and therapeutic drug management).

Bayesian Estimation of Tobramycin Exposure in Patients with Cystic Fibrosis

Fixed tobramycin (mg/kg) dosing is often inappropriate in patients with cystic fibrosis (CF), as pharmacokinetics are highly variable. The area under the concentration-time curve (AUC) is an exposure metric suited to monitoring in this population. Bayesian strategies to estimate AUC have been available for over 20 years but are not standard practice in the clinical setting. To assess their suitability for use in clinical practice, three AUC estimation methods using limited sampling were compared to measured true exposure by using intensive sampling tobramycin data. Adults prescribed once daily intravenous tobramycin had eight concentrations taken over 24 h. An estimate of true exposure within one dosing interval was calculated using the trapezoidal method and compared to three alternate estimates determined using (i) a two-sample log-linear regression (LLR) method (local hospital practice); (ii) a Bayesian estimate using one concentration (AUC₁); and (iii) a Bayesian estimate using two concentrations (AUC₂). Each method was evaluated against the true measured exposure by a Bland-Altman analysis. Twelve patients with a median (range) age and weight of 25 (18 to 36) years and 66.5 (51 to 76) kg, respectively, were recruited. There was good agreement between the true exposure and the three alternate estimates of AUC, with a mean AUC bias of <10 mg/liter · h in each case, i.e., -8.2 (LLR), 3.8 (AUC₁), and 1.0 (AUC₂). Bayesian analysis-based and LLR estimation methods of tobramycin AUC are equivalent to true exposure estimation. All three methods may be suitable for use in the clinical setting; however, a one-sample Bayesian method may be most useful in ambulatory patients for which coordinating blood samples is difficult. Suitably powered, randomized clinical trials are required to assess patient outcomes.

Development and Evaluation of a Gentamicin Pharmacokinetic Model That Facilitates Opportunistic Gentamicin Therapeutic Drug Monitoring in Neonates and Infants

Trough gentamicin therapeutic drug monitoring (TDM) is time-consuming, disruptive to neonatal clinical care, and a patient safety issue. Bayesian models could allow TDM to be performed opportunistically at the time of routine blood tests. This study aimed to develop and prospectively evaluate a new gentamicin model and a novel Bayesian computer tool (neoGent) for TDM use in neonatal intensive care. We also evaluated model performance for predicting peak concentrations and the area under the concentration-time curve from time 0 h to time t h (AUC0- t). A pharmacokinetic meta-analysis was performed on pooled data from three studies (1,325 concentrations from 205 patients). A 3-compartment model was used with the following covariates: allometric weight scaling, postmenstrual and postnatal age, and serum creatinine concentration. Final parameter estimates (standard errors) were as follows: clearance, 6.2 (0.3) liters/h/70 kg of body weight; central volume (V), 26.5 (0.6) liters/70 kg; intercompartmental disposition (Q), 2.2 (0.3) liters/h/70 kg; peripheral volume V2, 21.2 (1.5) liters/70 kg; intercompartmental disposition (Q2), 0.3 (0.05) liters/h/70 kg; peripheral volume V3, 148 (52.0) liters/70 kg. The model's ability to predict trough concentrations from an opportunistic sample was evaluated in a prospective observational cohort study that included data from 163 patients and 483 concentrations collected in five hospitals. Unbiased trough predictions were obtained; the median (95% confidence interval [CI]) prediction error was 0.0004 (-1.07, 0.84) mg/liter. Results also showed that peaks and AUC0- t values could be predicted (from one randomly selected sample) with little bias but relative imprecision, with median (95% CI) prediction errors being 0.16 (-4.76, 5.01) mg/liter and 10.8 (-24.9, 62.2) mg · h/liter, respectively. neoGent was implemented in R/NONMEM and in the freely available TDMx software.