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Pharmacokinetic (PK) models exist for most antiepileptic drugs (AEDs). Yet their use in clinical practice to assess interindividual differences and derive individualized doses has been limited. Here we show how model-based dosing algorithms can be used to ensure attainment of target exposure and improve treatment response in patients. Using simulations, different treatment scenarios were explored for 11 commonly used AEDs. For each drug, five scenarios were considered: 1) all patients receive the same dose. 2) Individual clearance (CL), as predicted by population PK models, is used to personalize treatment. 3-5) Individual CL, obtained by therapeutic drug monitoring (TDM) according to different sampling schemes, is used to personalize treatment. Attainment of steady-state target exposure was used as the performance criterion to rank each scenario. In contrast to current clinical guidelines, our results show that patient demographic and clinical characteristics should be used in conjunction with TDM to personalize the treatment of seizures.