METHODS: A pooled population-pharmacokinetic model was built in NONMEM based on data from 14 different studies in different patient populations. Steady-state exposure was simulated and compared across patient subgroups for two US Food and Drug Administration/European Medicines Agency-approved drug labels and optimised doses were derived.
RESULTS: The final model uses postmenstrual age, weight and serum creatinine as covariates. A 35-year-old, 70-kg patient with a serum creatinine level of 0.83 mg dL-1 (73.4 µmol L-1) has a V1, V2, CL and Q2 of 42.9 L, 41.7 L, 4.10 L h-1 and 3.22 L h-1. Clearance matures with age, reaching 50% of the maximal value (5.31 L h-1 70 kg-1) at 46.4 weeks postmenstrual age then declines with age to 50% at 61.6 years. Current dosing guidelines failed to achieve satisfactory steady-state exposure across patient subgroups. After optimisation, increased doses for the Food and Drug Administration label achieve consistent target attainment with minimal (± 20%) risk of under- and over-dosing across patient subgroups.
CONCLUSIONS: A population model was developed that is useful for further development of age and kidney function-stratified dosing regimens of vancomycin and for individualisation of treatment through therapeutic drug monitoring and Bayesian forecasting.
METHODS: There were 5 patients, with a median age of 1.75 (range 0.1-6.25) years, a median weight of 10.7 (2.9-21.5) kg, and a median creatinine clearance of 179 (44-384) mL/min/1.73m2, who received intravenous infusions of colistimethate each 8 hours. The median daily dose was 0.21 (0.20-0.21) million international units/kg, equivalent to 6.8 (6.5-6.9) mg of colistin base activity per kg/day. Plasma concentrations of colistimethate and formed colistin were subjected to population pharmacokinetic modeling to explore the patient factors influencing the concentration of colistin.
RESULTS: The median, average, steady-state plasma concentration of colistin (Css,avg) was 0.88 mg/L; individual values ranged widely (0.41-3.50 mg/L), even though all patients received the same body weight-based daily dose. Although the daily doses were ~33% above the upper limit of the FDA- and EMA-recommended dose range, only 2 patients achieved Css,avg ≥2mg/L; the remaining 3 patients had Css,avg <1mg/L. The pharmacokinetic covariate analysis revealed that clearances of colistimethate and colistin were related to creatinine clearance.
CONCLUSIONS: The FDA and EMA dosage recommendations may be suboptimal for many pediatric patients. Renal functioning is an important determinant of dosing in these patients.
RECENT FINDINGS: Optimal antibiotic treatment is challenging in critically ill patients with nosocomial pneumonia; most dosing guidelines do not consider the altered physiology and illness severity associated with severe lung infections. Antibiotic dosing can be guided by plasma drug concentrations, which do not reflect the concentrations at the site of infection. The application of aggressive dosing regimens, in accordance to the antibiotic's pharmacokinetic/pharmacodynamic characteristics, may be required to ensure rapid and effective drug exposure in infected lung tissues.
SUMMARY: Conventional antibiotic dosing increases the likelihood of therapeutic failure in critically ill patients with nosocomial pneumonia. Alternative dosing strategies, which exploit the pharmacokinetic/pharmacodynamic properties of an antibiotic, should be strongly considered to ensure optimal antibiotic exposure and better therapeutic outcomes in these patients.
METHODS: Hospitalised adult patients on EID gentamicin were selected. We considered a DFP of between 2 and 8 h as appropriate. Data from two blood samples (2 and 6 h postdose) from each patient were used to estimate the duration of DFP (i.e. DFP method 1). DFP was also calculated for the same patient using an empirically estimated elimination rate constant (Ke ) and the same 6 h postdose concentration value (DFP method 2). Correlation between the two methods was made. An alternative graphical method to estimate DFP was attempted.
KEY FINDINGS: Correlation between Ke and age was favourable (r = -0.453; P = 0.001). Ke derived from this empirical relationship was used to estimate DFP method 2. DFP method 1 correlated well with DFP method 2 (r = 0.742; P