Search

Objective: The aim of this study was to develop routinely applicable limited sampling strategies for assessing cyclosporin (CsA) AUC(0-12 h), and possibly other exposure indices such as AUC(0-4 h) and C(max), in heart transplant patients over the first year post-transplantation., Methods: First, the individual pharmacokinetics (PKs) of 14 adult heart-transplant patients receiving Neoral were assessed at three post-transplantation periods, at the end of the first week (W1), the third month (M3) and the first year (Y1). To fit blood concentrations, a PK model specially developed for oral CsA was applied. Second, two statistical methods were compared for AUC(0-12 h) estimation using a limited sampling strategy (maximum of three blood samples): multiple regression analysis (MR) and Bayesian estimation (BE)., Results: No significant difference was observed between the individual PK parameters at M3 and Y1, so population modelling was performed taking as a whole the concentration data collected at M3 and Y1. On the contrary, a significant difference ( P<0.05) was found for the C2/dose ratio between W1 and M3 and between W1 and Y1 (mean+/-SD =5.47+/-2.33; 7.78+/-1.05; 6.98+/-2.17 ml(-1 )for W1, M3 and Y1, respectively). Also, C(max)/dose and A were found significantly lower at W1 than at M3 ( P<0.01 and P<0.005, respectively), while lambda(1) was significantly higher at W1 than at both M3 and Y1 ( P<0.01). Using three sampling times (t0 h, t1 h and t3 h), BE allowed an accurate prediction of AUC(0-12 h) (mean bias =3.06+/-12.16%; +1.50+/-1.61%; and -0.20+/-11.42% at W1, M3 and Y1, respectively), AUC(0-4 h )and C(max). MR led to satisfactory estimation of AUC(0-12 h) using only two blood samples collected 2 h and 6 h post-dose (R=0.956-0.993; bias =-5.22 to +4.41; precision =6.38 to 9.90%), but this method is unable to estimate any other exposure index and requires strict respect of sampling times, contrary to BE., Conclusion: Neoral monitoring based on full or abbreviated AUC is possible using BE or MR in heart transplant patients over the first year post-transplantation. BE provides a good description of the individual PK profiles and thus might be useful not only in case of potential discrepancies between C2 and clinical findings, but also for clinical trials aimed at finding optimum PK monitoring in heart recipients.

Objective: To develop a maximum a posteriori probability (MAP) Bayesian estimator for the pharmacokinetics of oral cyclosporin, based on only three timepoints, and evaluate its performance with respect to a full-profile nonlinear regression approach., Patients: 20 adult patients with stable renal transplants given orally administered microemulsified cyclosporin and mycophenolate., Methods: Cyclosporin was assayed by liquid chromatography-mass spectrometry. Nonlinear regression and MAP Bayesian estimation were performed using a home-made program and a previously designed pharmacokinetic model including an S-shaped absorption profile described by a gamma distribution., Outcome Measures and Results: MAP Bayesian estimation using the best limited sampling strategy (before administration, and 1 and 3 hours after administration) was compared with nonlinear regression (taken as the reference method) for the prediction of the different pharmacokinetic parameters and exposure indices. Median relative prediction error was -0.49 and -3.42% for area under the concentration-time curve over the administration interval of 12 hours (AUC12) and estimated peak drug concentration (Cmax), respectively (nonsignificant). Relative precision was 2.00 and 4.32%, and correlation coefficient (r) was 0.985 and 0.955, for AUC12 and Cmax, respectively., Conclusion: This paper reports preliminary results in a stable renal transplant patient population, showing that MAP Bayesian estimation can allow accurate prediction of AUC12 and Cmax with only three samples (0, 1 and 3 hours). Although these results require confirmation by further studies in other clinical settings, using other drug combinations, other analytical methods and commercially available pharmacokinetic software, the method seems promising as a tool for the therapeutic drug monitoring of cyclosporin in clinical practice or for exposure-controlled studies.

Objective. The aim of this study was to develop routinely applicable limited sampling strategies for assessing cyclosporin (CsA) AUC0–12 h, and possibly other exposure indices such as AUC0–4 h and Cmax, in heart transplant patients over the first year post-transplantation. Methods. First, the individual pharmacokinetics (PKs) of 14 adult heart-transplant patients receiving Neoral were assessed at three post-transplantation periods, at the end of the first week (W1), the third month (M3) and the first year (Y1). To fit blood concentrations, a PK model specially developed for oral CsA was applied. Second, two statistical methods were compared for AUC0–12 h estimation using a limited sampling strategy (maximum of three blood samples): multiple regression analysis (MR) and Bayesian estimation (BE). Results. No significant difference was observed between the individual PK parameters at M3 and Y1, so population modelling was performed taking as a whole the concentration data collected at M3 and Y1. On the contrary, a significant difference (P<0.05) was found for the C2/dose ratio between W1 and M3 and between W1 and Y1 (mean±SD =5.47±2.33; 7.78±1.05; 6.98±2.17 ml-1 for W1, M3 and Y1, respectively). Also, Cmax/dose and A were found significantly lower at W1 than at M3 (P<0.01 and P<0.005, respectively), while λ1 was significantly higher at W1 than at both M3 and Y1 (P<0.01). Using three sampling times (t0 h, t1 h and t3 h), BE allowed an accurate prediction of AUC0–12 h (mean bias =3.06±12.16%; +1.50±1.61%; and -0.20±11.42% at W1, M3 and Y1, respectively), AUC0–4 h and Cmax. MR led to satisfactory estimation of AUC0–12 h using only two blood samples collected 2 h and 6 h post-dose (R=0.956–0.993; bias =-5.22 to +4.41; precision =6.38 to 9.90%), but this method is unable to estimate any other exposure index and requires strict respect of sampling times, contrary to BE. Conclusion. Neoral monitoring based on full or abbreviated AUC is possible using BE or MR in heart transplant patients over the first year post-transplantation. BE provides a good description of the individual PK profiles and thus might be useful not only in case of potential discrepancies between C2 and clinical findings, but also for clinical trials aimed at finding optimum PK monitoring in heart recipients. [ABSTRACT FROM AUTHOR]