Aim: Combined therapy of EGFR TKI and VEGFR TKI may produce a greater therapeutic benefit and overcome EGFR TKI-induced resistance. However, a previous study shows that a combination of EGFR TKI erlotinib (ER) with VEGFR TKI sunitinib (SU) did not improve the overall survival in patients with non-small-cell lung cancer (NSCLC). In this study we examined the anticancer effect of ER, SU and their combination in the treatment of A549 human NSCLC xenograft mice, and conducted PK/PD modeling and simulations to optimize the dose regimen. Methods: ER (20, 50 mg·kg -1 ·d -1 ) or SU (5, 10, 20 mg·kg -1 ·d -1 ) alone, or their combination were administered to BALB/c nude mice bearing A549 tumors for 22 days. The tumor size and body weight were recorded daily. The experimental data were used to develop PK/PD models describing the quantitative relationship between the plasma concentrations and tumor suppression in different dose regimens. The models were further evaluated and validated, and used to predict the efficacy of different combination regimens and to select the optimal regimen. Results: The in vivo anticancer efficacy of the combination groups was much stronger than that of either drug administered alone. A PK/PD model was developed with a combination index (φ) of 4.4, revealing a strong synergistic effect between ER and SU. The model simulation predicted the tumor growth in different dosage regimens, and showed that the dose of SU played a decisive role in the combination treatment, and suggested that a lower dose of ER (≤5 mg·kg -1 ·d -1 ) and adjusting the dose of SU might yield a better dosage regimen for clinical research. Conclusion: The experimental data and modeling confirm synergistic anticancer effect of ER and SU in the treatment of A549 xenograft mice. The optimal dosage regimen determined by the PK/PD modeling and simulation can be used in future preclinical study and provide a reference for clinical application.
PPK models of LTG in different age groups of epileptic children were successfully established. Weight and combination therapy were identified as significant covariates on LTG clearance. Compared with the whole-age model, the age-specific models are more reliable.
Vancomycin, a glycopeptide antibiotic for the treatment of grampositive infections, is mainly eliminated via glomerular filtration. Thus, its therapeutic effects are affected predominantly by renal function. The aim of this study was to develop a population pharmacokinetic model of vancomycin for Chinese adult patients and to investigate the influence of different renal function descriptors on the predictability of the model. A retrospective analysis was performed based on the blood concentrations of vancomycin in 218 Chinese adult patients. Among these patients, the data from 160 were used to establish the population pharmacokinetic model, and the data from the remaining 58 patients were used for external model validation. A simulation was employed to determine the appropriate initial vancomycin dosage regimens in adult Chinese patients for reaching the target steady-state trough concentrations of 10-15 mg/L and 15-20 mg/L. We developed a one-compartment model with first-order absorption to characterize the concentration-time profile of vancomycin. There was a positive correlation between the body clearance of vancomycin and renal function; both creatinine clearance (CL) and age were the covariates that influenced the PK of vancomycin, and the excretion of vancomycin decreased as renal function diminishing with age. The typical clearance (CL) value was 2.829 L/h for 75-year-old patients with CL values of 80 mL/min, and the rate constant of CL with the CL changing at 1 mL/min was 0.00842. The influence coefficient of age on CL was 0.08143. The external validation results revealed that the current different descriptors of renal function behaved similarly to the predicted performance of the models. In conclusion, the developed model is appropriate for Bayesian dose predictions of vancomycin concentrations in the population of Chinese adult patients. Furthermore, the simulation provides a reference for clinical optimized antibacterial therapy with vancomycin.
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