We report a PopPK model for cyclosporine in Tunisian HSCT patients. Bayesian estimation using only three concentrations provides good prediction of cyclosporine exposure. These tools allow us to routinely estimate cyclosporine AUC in a clinical setting.

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Measurements of Cyclosporine (CsA) systemic exposure permit its dose adjustment in allogenic stem cell transplantation recipients to prevent graft-versus-host disease. CsA LSSs were developed and validated from 60 ASCT patients via multiple linear regressions. All whole-blood samples were analyzed by fluorescence polarization immunoassay (FPIA-Axym). The 10 models that have used CsA concentrations at a single time point did not have a good fit with AUC0–12 (R2 < 0.90). C 2 and C 4 were the time points that correlated best with AUC0–12 h, R2 were respectively 0.848, and 0.897. The LSS equation with the best predictive performance (bias, precision and number of samples) utilized three sampling concentrations was AUC0–12 h = 0.607 + 1.569 × C 0.5 + 2.098 × C 2 + 3.603 × C 4 (R2 = 0.943). Optimal LSSs equations which limited to those utilizing three timed concentrations taken within 4 hours post-dose developed from ASCT recipient's patients yielded a low bias <5% ranged from 1.27% to 2.68% and good precision <15% ranged from 9.60% and 11.02%. We propose an LSS model with equation AUC0–12 h = 0.82 + 2.766 × C 2 + 3.409 × C 4 for a practical reason. Bias and precision for this model are respectively 2.68% and 11.02%.

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