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Population Pharmacokinetics Of Cyclosporine In Patient Undergoingallogeneic Kidney Transplantation

Posted on:2018-02-16Degree:MasterType:Thesis
Country:ChinaCandidate:Y Y ZhuFull Text:PDF
GTID:2334330515999610Subject:Pharmacokinetics
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Objective: Allogeneic renal transplant patients are prone to severe acute rejection,the immunosuppressive agents such as cyclosporine A(Cs A)was frequently used in clinical treatment.Cyclosporine A pharmacokinetic individual differences in the treatment of narrow,renal transplant patients prescribed by the unified administration,a serious impact on patients with treatment and prognosis.According to the provisions of uniform administration,the individual pharmacokinetic differences is very large in kidney transplant patients,and the therapeutic window of Cyclosporine A is narrow,which seriously affect the treatment and prognosis of patients.The population pharmacokinetic model of Cs A in allogeneic renal transplantation patients was established,and the individual differences were better estimated.The pharmacokinetic parameters of Cs A in allogeneic renal transplant recipients were also studied.And the population pharmacokinetic model of Cs A is to be used in clinical practice,in order to achieve clinical individualized drug delivery to provide a scientific basis to extend the survival time of renal transplant patients,and improve patient quality of life.Methods: A total of 789 copies of concentrations collected from 156 allogeneic renal recipients were retrospectively analyzed.The data were analyzed by non-linear mixed effect model(NONMEM).The data of sex,age,body weight,postoperative time,blood routine,liver and kidney function,genotype(CYP3A4,CYP3A5,CYP2D6,MDR1,MRP2,PXR)were used to establish the population pharmacokinetic model of Cs A in allogeneic renal transplant recipients.The model was validated by the bootstrap method,which was verified by the US food and drug administration.Results:1)In this study,NONMEM method was used to establish the pharmacokinetic model of Cs A population in allogeneic renal transplantation patients with good precision and stability.The demographic data,pathophysiological data,combination therapy and patient gene were observed in allogeneic renal transplant patients.The results showed that?-glutamyltransferase(GGT),postoperative time(POD)and CYP3A4 15820 C / G * 5(GENE1,rs55901263)had a significant effect on the cyclosporin A clearance rate(CL)in renal transplant patients,and only the patients' sex(SEX)had a significant effect on the apparent volume(V).The pharmacokinetic model of allogeneic renal transplant patients with good precision and stability was established.The results of Model validation showed that the final model was stable and reliable.The equation of final model:CL=43.3*(GGT/34.74)**0.712*(POD/7.03)**0.722*1.09**GENE1*e?1V=4760*0.786**SEX*e?2KA=3.86 h-12)The final model was used in 6 patients with allogeneic kidney transplantation(male 5 female 1 cases).One patient had a valley concentration of less than 150 ng · m L-1,which may be associated with the clinical cyclosporine A specifications fixed,and it is difficult to accurately adjust the dose-related.The other 5 patients achieved the desired plasma concentration,and the average plasma concentration was 153.08 ng · m L-1,and the error between the predicted plasma concentration and measured blood concentration was2.05%.Conclusion: In this study,the pharmacokinetic model of cyclosporine A population in allogeneic renal transplant recipients was established.The final model was proved by the bootstrap method,which showed that it was stable and reliable.The final model seen was used in allogeneic patients,the results of predicting the patients' concentration was accurate.It indicated that it can be used for dosing regimen of cyclosporine A in clinical allogeneic kidney transplant patients,to improve the effectiveness of clinical treatment,and reduce the incidence of adverse reactions in patients.
Keywords/Search Tags:Allogeneic renal transplantation, Cyclosprin A, Population Pharmacokinetics, Individualized drug administration, Nonlinear mixed effect model
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