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OBJECTIVE To establis h and validate a population pharmacokinetic model of docetaxel in malignant tumor patients. METHODS The clinical data of malignant tumor patients treated with chemotherapy regimen containing docetaxel in our hospital from June 2019 to December 2021 were retrospectively collected . According to the results of blood concentration detection ， based on the three -compartment model the nonlinear mixed effect model （NONMEM）was used ；covariates（age，weight，height， body surface area ，Karnofsky performance scale ，total protein ，albumin，total bilirubin ，aspartate aminotransferase ，alanine aminotransferase and serum creatinine ）affecting clearance （CL）were screened by “forward inclusion and backward exclusion ”； the population pharmacokinetic model of docetaxel was established . The model was tested for goodness -of-fit diagnosis and internal validation by Bootstrap . RESULTS A total of 264 measured blood concentrations of 132 patients with malignant tumors during chemotherapy were included . The covariates that had significant effect on CL of docetaxel were serum creatinine and total bilirubin （P＜0.01）. The results of Bootstrap analysis （parameter median values and 95% confidence intervals ）were close to predict results of the established model ；the final model estimated that the population typical value of docetaxel CL was 37.82 L/h. CONCLUSIONS The population pharmacokinetic model of docetaxel in malignant tumor patients is established successfully ， which can be used for the formulation and optimization of clinical individualized regimen .
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In recent years， the role of quantitative pharmacological models in applicable population of drugs and dose optimization has been widely recognized. In order to improve the efficiency of clinical development and optimize clinical rational drug use， quantitative pharmacological models are being gradually introduced into the research of traditional Chinese medicine （TCM）. There are various types of quantitative pharmacological models， among which the following three models are commonly used：①Population pharmacokinetic （PPK） model， which is mainly used to explore the pharmacokinetic characteristics in different populations.②Pharmacokinetic-pharmacodynamic （PK-PD） model， which is used to reveal the internal relationship among dose， time and efficacy. ③PPK-PD model， which integrates both the characteristics of PPK model and PK-PD model. The paper summarizes the application of the above three models in TCM， and extracts the main ideas and methods of TCM model research， in order to provide reference for clinical research and rational use of TCM.
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Valproic acid is a commonly used and broad-spectrum antiepileptic drug in clinical practice with a narrow therapeutic window. Valproic acid has a great individual difference in its metabolism which is influenced by many factors. The gene polymorphism of drug metabolic enzymes is one of the critical factors. Through consulting relevant articles, the affection of genomics and clinical treatment on valproic acid clinical application were reviewed in this paper, which provided a reference for clinical individualized treatment.
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AIM: The population pharmacokinetic model (PKK) of linezolid was constructed with the retrospective data of linezolid therapeutic drug monitoring from the 3 hospitals of ENZE medical center, which could be used to predict individualized pharmacokinetic parameters with Bayesian feedback method based on single point trough concentration and support scientific experimental method for rational drug use of linezolid in the future. METHODS: A total of 115 monitoring serum concentration data of 72 patients from Mar. 2016. to Dec. 2018 were included in this study. Stepwise regression method was used to screen the concomitant variable (age, weight, blood routine examination, biochemical index and drug combination etc.) for Vd and K by kinetica software. The internal and external validation were analyzed with maximum likihood method and Bayesian feedback. RESULTS: As the final model Vd=25.864-0.034×Fur(mg) shown, combination use of furosemide has a significant effect on Vd of linezolid. The level of age, Scr and the burn status of the patients have a significant effect on K of linezolid and the final model was K=0.324-0.0003×Scr-0.003×age +0.04×burn. Finally, the population mean value of Vd and K were 29.719 L(5.32, 52.36), 0.160 h-1 (0.05, 0.23) and 25.322 L (2.50, 52.51), 0.193 h-1 (0.06, 0.32) in basic model and final model. The mean absolute prediction error rate of external validation was 0.620 (0.001, 4.153) in basic model and 0.588 (0.014, 3.942) in final model. CONCLUSION: The final PPK model from the present study could well response the heterogeneous PPK characteristic of the patients from ENZE medical center, which could support scientific experiment method for improving the linezolid therapeutic effect and reducing adverse reaction rate.
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This study aimed to evaluate the predictive performance of a vancomycin population pharmacokinetic model in 0-10 year Chinese pediatric patients. This study was approved by the Ethics Research Committee of the First Affiliated Hospital of Guangxi Medical University, data from hospitalized children ≤ 10 years of age who receiving vancomycin were collected retrospectively. Individual predictive values (IPRED) were estimated by Bayesian Analysis based on a previous published population pharmacokinetic model, and compared with the observed steady state trough concentration. As results, a total of 371 vancomycin serum concentrations from 191 patients were taken for the external validation. The mean error (ME), the mean relative prediction error (ME%), the mean absolute error (MAE) and the root mean square error (RMSE) in individual prediction method for the total patients were -0.50 mg·L-1, 6.03%, 1.84 mg·L-1, 2.86 mg·L-1 respectively. The correlation coefficient between individual predictions and detection values was 0.95. The stability and the predictive performance of model were accepted by goodness-of-fit, visual predictive check (VPC) and Bland-Altman. The percentage of individual prediction error within ± 30% was 82.75%. The above results suggest that, this Chinese pediatric population pharmacokinetic model in 0-10 years old has a good prediction performance. It can be applied to the design of initial treatment plan and predicting the extent of drug exposure.
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Tacrolimus is commonly used in the treatment for the refractory primary nephrotic syndrome (PNS) in the pediatric patients. Data were retrospectively obtained from 100 children with 357 tacrolimus trough concentrations in our center between May 2010 and March 2016. Information of age, sex, body weight, drug dose, co-therapy medications, laboratory tests and sampling time were collected. The population pharmacokinetic model was developed using nonlinear mixed effect modeling (NONMEM) software. A one-compartment model with first-order absorption and elimination best described the data. The population estimate of apparent clearance (CL/F) and apparent volume of distribution (V/F) was 6.54 L·h-1 and 86.2 L, respectively. Body weight (WT, kg), daily dose of tacrolimus (DD, mg·day-1) and co-therapy azole antifungal agent have a significant impact on the CL/F. The final PPK model of CL/F was:CL/F=6.54×((WT)/25)K×((DD)/1.5)0.293×0.657Azole,K=(WT-30.9)/(WT-30.9+10.4-30.9). When combined with azole antifungal agents, Azole was 1, whereas vice versa was 0. This is the first PPK study of tacrolimus conducted in pediatric patients with PNS, which may facilitate individualized drug therapy of tacrolimus.
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Vancomycin has been widely prescribed as the first-line antibiotic in the treatment of methicillin-resistant Staphylococcus aureus and other serious Gram-positive infections. Due to its large pharmacokinetic (PK) variability and narrow therapeutic range, it requires optimization of dosage to achieve target exposure. In this study, SmartDose, a decision support system for individualization of vancomycin dosage is developed using the maximum a posterior Bayesian estimation (MAPB) by the open-source language R combined with the population PK characteristics of vancomycin in Chinese patients. It provides initial design and adjustment of dose regimens based on the therapeutic drug monitoring (TDM) results, as well as a user-defined module to facilitate optimal vancomycin therapy. SmartDose has a high computational reliability, which is validated by NONMEM, the golden standard PK software. Meanwhile, SmartDose is established as a web-based application and its operational flexibility makes it an efficient tool for vancomycin dose optimization in routine clinical settings.
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BACKGROUND: A number of molecularly targeted agents in oncology are tested in clinical studies in combination with conventional chemotherapy and/or radiotherapy. There is the possibility that the pharmacokinetics and dynamics of these targeted agents may be different when administered alone as against when administered in combination with other agents. AIM: The aim of this study is to understand the effects of addition of combination agents on the pharmacokinetics of a new, investigational, cyclin dependent kinase inhibitor anti‑cancer drug (Compound A) using population pharmacokinetic (pop‑PK) analysis. MATERIALS AND METHODS: Integrated pop‑PK analysis of data obtained from multiple phase I/II studies of Compound A, given alone or in combination with other agents. RESULTS: A two compartmental model was found suitable to explain the pharmacokinetics of Compound A. No statistically significant influence of patient covariates or combination agents on the pharmacokinetic parameters of the central compartment was detected up to a significance level of 0.01. Model evaluation showed that the parameter estimates are stable and that the variability in the data was well reproduced by the model. CONCLUSIONS: This study represents the first time that a pop‑PK analysis was performed in India for a targeted anti‑cancer agent being developed in India. Such an analysis is useful to not only understand the influence of patient covariates and combination agents on the pharmacokinetics of a new investigational agent, but would also be valuable in the simulation of later phase clinical trials for the agent under development.
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Objective This study was designed to validate the utility of a population pharmacokinetic model established for vancomycin in patients with severe neurosurgical disease . Methods The clinical data including patient gender , age , body weight ,serum creatinine and albumin were collected retrospectively from patients in Nanjing Drum Tower Hospital to calculate the steady trough concentration of vancomycin using the previously established pharmacokinetic model .The predicted value was compared with the actual value .Results During the period from March 2013 to March 2014 ,53 blood samples with serum trough concentration of vancomycin were collected from 42 patients .The average trough concentration of vancomycin was 10 .9 mg/L (range from 1 .6 to 49 .1 mg/L) .The predicted trough level of vancomycin based on the population pharmacokinetic model was significantly correlated to the actual value(r=0 .857 ,P<0 .001) .The mean absolute percentage error was 0 .407 9 . The confidence interval was 9 .36‐14 .07 for the predicted values ,and 8 .92‐14 .32 for the actual values .Conclusions The pharmacokinetic model is valid and useful for planning intravenous dose of vancomycin in patients with severe neurosurgical disease .Large error (about 30% ) was observed in estimation of body weight due to coma .Reduced renal function following contrast agent and/or diuretic drug has an impact on the predicted results . The accuracy of prediction can be increased to nearly 70% after adjusting the covariates .