OBJECTIVE: To establish a population pharmacokinetics (PPK) model of lamotrigine, an antiepileptic drug, in Chinese children with epilepsy to formulate an individualized dosage guideline. METHODS: A total of 303 data, including the random ones of serum lamotrigine concentrations from 165 epileptic children were analyzed. Lamotrigine concentrations were determined by the RP-HPLC method. PPK model of lamotrigine was established using NONMEM, a population pharmacokinetic computer program, according to one-compartment model with first-order absorption and elimination. To evaluate the accuracy and precision of predicting lamotrigine concentrations, mean error (ME), mean squared prediction error (MSE), standard mean squared prediction error (SME), root mean squared prediction error (RSME), WRES and their 95% confidence interval were calculated in both the base and the final models. RESULTS: Regression equation of the base model of lamotrigine was obtained, ie, clearance (CL/F)=0.664×EXP［ETA(1)］, volume of distribution (V/F)=45×EXP［ETA(2)］, and KA=4.0×EXP ［ETA(3)］, and that of the final model was as follows: CL/F=0.717×(10.601×VPA)×(1+1.18×EI)× (1.62∧［AGE/7.02)］×EXP［ETA(1)］, V/F=40.2×EXP［ETA(2)］, KA=3.27×EXP ［ETA(3)］. The population values of CL/F, V/F and KA were 1.16 L/h (0.042 L/h/kg), 40.2 L(1.46 L/kg) and 3.27/h for lamotrigine respectively in the final model. The final PPK model was demonstrated to be stable and effective in the prediction of serum lamotrigine concentrations by internal and external approaches validation. CONCLUSIONS: A PPK model of lamotrigine in Chinese children with epilepsy was successfully established using NONMEM. Lamotrigine concentrations can be predicted accurately by the model. The model may be helpful to reasonable use of antiepileptic drugs in clinical practice.