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Aim： To establish a population pharmacokinetics （PPK） model of levetiracetam in Chinese children with epilepsy. Methods： A total of 418 samples from 361 epileptic children in Peking University First Hospital were analyzed. These patients were divided into two groups： the PPK model group （n=311） and the PPK validation group （n=50）. Levetiracetam concentrations were determined by HPLC. The PPK model of levetiracetam was established using NONMEM, according to a one-compartment model with firstorder absorption and elimination. To validate the model, the mean prediction error （MPE）, mean squared prediction error （MSPE）, root mean-squared prediction error （RMSPE）, weight residues （WRES）, and the 95% confidence intervals （95% CI） were calculated. Results： A regression equation of the basic model of levetiracetam was obtained, with clearance （CL/F）=O.988 L/h, volume of distribution （V/F）=12.3 L, and Ka=1.95 h-1. The final model was as follows： Ka=1.56 h-1, V/F=12.1 （L）, CL/F=1.04x（WEIG/25）63 （L/h）. For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95%Cl were 9.834 （-0.587-197.720）, 50.919 （0.012-1286.429）, 1.680 （0.021-34.184）, and 0.0621 （-1.100-1.980）. For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% Cl were 0.199 （-0.369-0.563）, 0.002082 （0.00001-0.01054）, 0.0293 （0.001-0.110）, and 0.153 （-0.030-1.950）. Conclusion： A one-compartment model with firstrder absorption adequately described the levetiracetam concentrations. Body weight was identified as a significant covariate for levetiracetam clearance in this study. This model will be valuable to facilitate individualized dosage regimens.

Aim: To establish a population pharmacokinetics (PPK) model of levetiracetam in Chinese children with epilepsy. Methods: A total of 418 samples from 361 epileptic children in Peking University First Hospital were analyzed. These patients were divided into two groups: the PPK model group ( n =311) and the PPK validation group ( n =50). Levetiracetam concentrations were determined by HPLC. The PPK model of levetiracetam was established using NONMEM, according to a one-compartment model with first-order absorption and elimination. To validate the model, the mean prediction error (MPE), mean squared prediction error (MSPE), root mean-squared prediction error (RMSPE), weight residues (WRES), and the 95% confidence intervals (95% CI) were calculated. Results: A regression equation of the basic model of levetiracetam was obtained, with clearance ( CL/F )=0.988 L/h, volume of distribution ( V / F )=12.3 L, and K a =1.95 h −1 . The final model was as follows: K a =1.56 h −1 , V / F =12.1 (L), CL/F =1.04×(WEIG/25) 0.583 (L/h). For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95%CI were 9.834 (−0.587–197.720), 50.919 (0.012–1286.429), 1.680 (0.021–34.184), and 0.0621 (−1.100–1.980). For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were 0.199 (−0.369–0.563), 0.002082 (0.00001–0.01054), 0.0293 (0.001−0.110), and 0.153 (−0.030–1.950). Conclusion: A one-compartment model with first-order absorption adequately described the levetiracetam concentrations. Body weight was identified as a significant covariate for levetiracetam clearance in this study. This model will be valuable to facilitate individualized dosage regimens.