External Validation of the Population Models for Carbamazepine Pharmacokinetics and the Individualizing Carbamazepine Dosage Regimen Procedure
K. Bondareva
student, Moscow State University, Department of Computational Mathematics and Cybernetics, Russia
Objectives: The objective of external validation is to examine whether the model can equally describe a new data set, which has not been used for model parameter estimation. The study is aimed at evaluating the predictability of the patient-specific Bayesian posterior PK models for carbamazepine (CBZ) monotherapy in the post-induction period.
Methods: The PK analysis was performed using the USC*PACK software based on the earlier developed linear one-compartment population PK models for CBZ and routine TDM data (peak – trough strategy). This study included epileptic patients for whom at least two pairs of measured serum levels related to different CBZ dosages were available. These data were not included in the population CBZ PK models. The first pair of each patient’s serum levels on a specific dosage regimen was used to estimate the individual PK parameter values and to predict future serum levels according to the planned changes in CBZ regimen. Then the observed serum levels on the new CBZ regimen were compared with those predicted initially by the patient-specific Bayesian posterior PK model. The percentage prediction error was estimated as the difference between observed and predicted levels compared to observed level.
Results: TDM data of adult epileptic patients on chronic CBZ and CBZ-retard monotherapy were used to estimate predictability of the CBZ PK models separately (98 and 42 predictions, respectively). The Kolmogorov-Smirnov test demonstrated that the residuals had approximately normal distribution (p=0.7 and 0.5), the mean errors were not statistically significantly different from zero (p=0.25 and 0.18) (random errors). Bias of the predictions was not observed. The mean absolute errors (MAE) were 14.7±11.4% and 17.0±10.1%. A statistically significant bias and higher MAE were observed in predictions when patients were switched from CBZ to CBZ-retard (n= 42, p<0.001). TDM data of patients that provided 3 to 6 pairs of measured levels in different periods of CBZ monotherapy (multiple repeated measurements) were used to estimate intraindividual variability and influence of time horizon. In some patients, precision of predictions decreased with increasing of prognosis horizon.
Conclusions: The study demonstrated that predictions of future CBZ concentrations (for each dosage form) based on the population PK models, TDM data and a patient-specific Bayesian posterior parameter values provided clinically acceptable estimates.
