Immunosuppressive drugs exhibit high variability in metabolism and pharmacokinetics, that may result in drug toxicity or lack of efficacy. Low immunosuppressant drug exposure increases the risk of transplant rejection in the acute post-transplant period, while supratherapeutic drug concentration entails higher risk of adverse drug reactions1. These issues may be resolved by population pharmacokinetic modeling.
Population pharmacokinetic modeling might be performed and researched by clinical pharmacologists, recently established clinical pharmacology residency in Lithuania may play a role in this area as well2.
Aims:to broaden the competence of Lithuanian clinical pharmacologists by developing one-compartment model with first-order absorption of tacrolimus.
Methods.Anonymized medical records of kidney recipients receiving immunosuppressant tacrolimus and hospitalized at Limoges University Hospital(France) were included in the study. Tacrolimus analyses were performed using a liquid chromatography-tandem mass spectrometry method. A one-compartment model with first-order absorption was used as implemented in the NLMIXED procedure3, which fits nonlinear mixed models. Data analysis was performed by using SAS University Edition software. Model parameter estimated are provided with p-values and confidence limits computed by NLMIXED procedure. The p-values and confidence limits were computed from approximate standard errors (using the delta method) for the estimates.
Results.Anonymized medical records of 189 patients receiving immunosuppressant tacrolimus (2-20mg/d BID regimen) were analyzed and a one-compartment model with first-order absorption was constructed. The population estimates in the final population model of tacrolimus were: clearance 14.64L/h(CI 9.66; 19.62),p<0.0001, elimination rate 0.001657 min-1(CI:0.00098;0.002336),p<0.0001 and absorption rate 2.7119(CI:-45.7083; 51.1321),p=0.912. Mean value of concentration was 13.62(SD:7.5)µg/L, predicted concentration 10.83(SD:10.83)µg/L. Pearson correlation between measured and predicted concentrations was r=0.79(p<0.0001).
Conclusions.
1.Population pharmacokinetic models should be developed in-house.
2.Clinical pharmacologists should participate in pharmacokinetic modeling process.
This research was funded by a grant (No.P-MIP-17-445) from the Research Council of Lithuania. This research was performed in cooperation with the Limoges University Hospital,France.
References
1.Noreikaite,A; Saint-Marcoux,F; Marquet,P; Kadusevicius,E; Stankevicius,E. Influence of cyclosporine and everolimus on the main mycophenolate mofetil pharmacokinetic parameters: Cross-sectional study. Medicine(Baltimore). 2017;96(13):e6469. doi:10.1097/MD.0000000000006469.
2.Maciulaitis,R. Pharmacology in Estonia,Latvia and Lithuania: From historical roots to nowadays achievements. Pharmacol Res.2016;113:723-730. doi:10.1016/J.PHRS.2016.04.024.
3.PROC NLMIXED:Introduction: SAS/STAT(R) 9.22 User's Guide. https://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_nlmixed_sect002.htm. Accessed January9,2018.
Figure.Predicted vs. observed concentration (µg/L)
