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: Kinetic studies were used to investigate the interactions between the three GSTs and each of glutathione, 1-chloro-2,4-dinitrobenzene, cibacron blue, ethacrynic acid, S-hexyl glutathione, hemin and protoporphyrin IX. Since hemin displacement is intended for PfGST inhibitors, the interactions between hemin and other ligands at PfGST binding sites were studied kinetically. Computationally determined binding modes and energies were interlinked with the kinetic results to resolve enzymes-ligands interaction models at atomic level.
RESULTS: The results showed that hemin and cibacron blue have different binding modes in the three GSTs. Hemin has two binding sites (A and B) with two binding modes at site-A depending on presence of GSH. None of the ligands were able to compete hemin binding to PfGST except ethacrynic acid. Besides bind differently in GSTs, the isolated anthraquinone moiety of cibacron blue is not maintaining sufficient interactions with GSTs to be used as a lead. Similarly, the ethacrynic acid uses water bridges to mediate interactions with GSTs and at least the conjugated form of EA is the true hemin inhibitor, thus EA may not be a suitable lead.
CONCLUSIONS: Glutathione analogues with bulky substitution at thiol of cysteine moiety or at γ-amino group of γ-glutamine moiety may be the most suitable to provide GST inhibitors with hemin competition.
METHODS: Data from 43 lung transplant recipients (1021 tacrolimus concentrations) administered an immediate-release oral formulation of tacrolimus were used to evaluate the predictive performance of 17 published population pharmacokinetic models for tacrolimus. Data were collected from immediately after transplantation up to 90 days after transplantation. Model performance was evaluated using (1) prediction-based assessments (bias and imprecision) of individual predicted tacrolimus concentrations at the fourth dosing based on 1 to 3 previous dosings and (2) simulation-based assessment (prediction-corrected visual predictive check; pcVPC). Both assessments were stratified based on concomitant azole antifungal use. Model performance was clinically acceptable if the bias was within ±20%, imprecision was ≤20%, and the 95% confidence interval of bias crossed zero.
RESULTS: In the presence of concomitant antifungal therapy, no model showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33), and pcVPC plots displayed poor model fit to the data set. However, this fit slightly improved in the absence of azole antifungal use, where 4 models showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33).
CONCLUSIONS: Although none of the evaluated models were appropriate in guiding tacrolimus dosing in lung transplant recipients receiving concomitant azole antifungal therapy, 4 of these models displayed potential applicability in guiding dosing in recipients not receiving concomitant azole antifungal therapy. However, further model refinement is required before the widespread implementation of such models in clinical practice.