Remedial dosing recommendations for delayed or missed doses of valproic acid in patients with epilepsy based on Monte Carlo simulations.

OBJECTIVE: Delayed or missed doses are unavoidable in the pharmacotherapy of epilepsy and significantly compromise the efficacy of antiepileptic drug treatment. An inappropriate remedial regimen can cause seizure relapse or serious adverse events. This study investigated the effect of delayed or missed doses on the pharmacokinetics (PK) of valproic acid (VPA) in patients with epilepsy and established remedial dosing recommendations for nonadherent patients. METHODS: Monte Carlo simulations are based on all previous population pharmacokinetic models for pediatric, adult and elderly patients with epilepsy. The following four remedial strategies were investigated for each delayed dose: A) A partial dose or a regular dose is taken immediately; a regular dose is taken at the next scheduled time. B) The delayed dose was administered immediately, followed by a partial dose at the next scheduled time. C) The delayed dose and a partial dose are taken; the next scheduled time is skipped, and the regular regimen is resumed. D) Double doses are taken when missed one dose or two doses, and the regular regimen at the subsequent scheduled time is resumed. RESULTS: The recommended remedial dose was related to the delay duration and daily dose. Remedial dosing strategies A and B were almost equivalent, whereas Strategy C was recommended when the delayed dose was close to the next scheduled dose. Strategy D was only suggested for delayed two doses. CONCLUSION: Simulations provide quantitative insight into the remedial regimens for nonadherent patients, and clinicians should select the optimal regimen for each patient based on the individual's status.

Remedial dosing recommendations for delayed or missed doses of lamotrigine in pediatric patients with epilepsy using Monte Carlo simulations.

OBJECTIVE: This study investigated the effect of delayed or missed doses on the pharmacokinetics (PK) of lamotrigine (LTG) in children with epilepsy and established remedial dosing recommendations for nonadherent patients. METHODS: The Monte Carlo simulation based on a published LTG population PK model was used to assess the effect of different scenarios of nonadherence and the subsequently administered remedial regimens. The following three remedial approaches were investigated for each delayed dose: A) A partial dose was administered immediately, and the regular dose was administered at the next scheduled time. B) The delayed dose was administered immediately, followed by a partial dose at the next scheduled time. C) The delayed and partial doses were coadministered immediately, the next scheduled dose was skipped, and the regular dosing was resumed at the subsequent scheduled time. The most appropriate remedial regimen was that with the shortest deviation time from the individual therapeutic window. RESULTS: The effect of nonadherence on PK was dependent on the delay duration and daily dose, and the recommended remedial dose was related to the delay duration and concomitant antiepileptic drugs. Remedial dosing strategies A and B were almost equivalent, whereas C showed a larger PK deviation time. If one dose was missed, double doses were not recommended for the next scheduled time. CONCLUSIONS: Simulations provide quantitative insight into the remedial regimens for nonadherent patients, and clinicians should select the optimal regimen based on the status of patients.

Population pharmacokinetic and pharmacogenetics of imatinib in Chinese patients with chronic myeloid leukemia.

AIM: This study aimed to establish a population pharmacokinetic (PPK) model in Chinese patients with chronic myeloid leukemia, and to quantify the effects of pharmacogenetics on pharmacokinetic parameters of imatinib. METHODS: A total of 229 plasma concentrations from 170 patients were analyzed. Nonlinear mixed effect model was used to establish the PPK model. RESULTS: A one-compartment model with first-order absorption and first-order elimination adequately describes imatinib pharmacokinetics. Actual bodyweight shows slight effect on the estimated apparent clearance (CL/F) of imatinib in this study population. The final PPK model is: Ka (1/h) = 0.329; CL/F (l/h) = 9.25 × (actual bodyweight/70)0.228; V/F(l) = 222. CONCLUSION: Actual bodyweight has a slight effect on CL/F. Demographics, physiopathology and pharmacogenetics covariates have no significant effects on imatinib pharmacokinetics.