Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67–0.76)] and validation cohorts [0.73 (0.63–0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.
What is already known about this subject
• Schisandra sphenanthera extract (SchE) and tacrolimus are often co‐administrated in treating renal and liver transplant recipients in China.
• We discovered occasionally that blood tacrolimus concentrations are markedly increased in some patients who receive tacrolimus and concomitant SchE.
• This is the first study to investigate the effects of SchE on the pharmacokinetics of tacrolimus.
What this study adds
• Following administration of SchE in healthy volunteers, the mean AUC, AUMC and Cmax of tacrolimus substantially increases, whereas its CL/F and V/F decreases significantly.
• Blood tacrolimus concentrations need to be closely monitored and dose adjustments of tacrolimus have to be made accordingly in the presence of SchE.
Aim
To assess the effect of Schisandra sphenanthera extract (SchE) on the pharmacokinetics of tacrolimus in healthy volunteers.
Methods
Twelve healthy male volunteers were orally treated with SchE, three capsules twice daily for 13 days. Pharmacokinetic investigations of oral tacrolimus administration at 2 mg were performed both before and at the end of the SchE treatment period. Whole blood tacrolimus concentrations were determined by enzyme‐linked immunosorbent assay. Estimated pharmacokinetic parameters before and with SchE were calculated with noncompartmental techniques.
Results
Following administration of SchE, the average percentage increases of individual increases in AUC, AUMC and Cmax of tacrolimus were 164.2% [95% confidence interval (CI) 70.1, 258.4], 133.1% (95% CI 49.5, 261.3) and 227.1% (95% CI 155.8, 298.4), respectively (P < 0.01 or 0.05). On average, there was a 36.8% (95% CI 13.4, 60.2) increase in tacrolimus tmax (P < 0.01). The average percentage decreases in CL/F and V/F were 49.0% (95% CI 31.1, 66.9) and 53.7% (95% CI 40.1, 67.4), respectively (P < 0.01).
Conclusions
SchE can increase the oral bioavailability of tacrolimus. The results of this study will add important information to the interaction area between drugs and herbal products.
The BBR can markedly elevate the blood concentration of CsA in renal-transplant recipients in both clinical and pharmacokinetic studies. This combination may allow a reduction of the CsA dosage. The mechanism for this interaction is most likely explained by inhibition of CYP3A4 by BBR in the liver and/or small intestine.
SUMMARYBackground: Based on in vitro experiments using recombinant human thiopurine S-methyltransferase this enzyme is inhibited by sulfasalazine (sulphasalazine) and 5-aminosalicylate. Thus, during treatment with azathioprine or mercaptopurine, both metabolized by thiopurine S-methyltransferase, sulfasalazine or 5-aminosalicylate could modify the action of azathioprine/ mercaptopurine. Aims: To examine whether this interaction is effective under ex vivo conditions. Methods: In 18 azathioprine-free patients and in 12 patients on azathioprine the inhibitory potential of sulfasalazine, 5-aminosalicylate and its metabolite (Ac-5-aminosalicylate) was assessed by ex vivo measurement of thiopurine S-methyltransferase in red blood cells.
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