Making Up Missed Anti-Seizure Medication Doses: Double or Nothing?

Background and Objectives: Antiseizure medications are the major treatment modality for patients with epilepsy. Delayed or missed doses are common during long-term or lifelong anti-epilepsy treatment. This study aims to explore optimal individualized remedial dosing regimens for delayed or missed doses of 11 commonly used antiseizure medications.Methods: In order to explore remedial dosing regimens, Monte Carlo simulation was employed based on previously identified and published population pharmacokinetic models. Six remedial strategies for delayed or missed doses were investigated. The deviation time outside the individual therapeutic range was used to evaluate each remedial regimen. The influences of patients' demographics, concomitant medication, and scheduled dosing intervals on remedial regimens were assessed. RxODE and Shiny in R were employed to perform Monte Carlo simulation and recommend individual remedial regimens.Results: The recommended remedial regimens were highly correlated to delayed time, scheduled dosing interval, and half-life of the antiseizure medication. Moreover, the optimal remedial regimens for pediatric and adult patients were different. The renal function, along with concomitant medication that affect the clearance of the antiseizure medication, may also influence the remedial regimens. A web-based dashboard was developed to provide individualized remedial regimens for the delayed or missed dose, and a user-defined module with all parameters that could be defined flexibly by the user was also built.Discussion: Monte Carlo simulation based on population pharmacokinetic models may provide a rational approach to propose remedial regimens for delayed or missed doses of antiseizure medications in pediatric and adult patients with epilepsy.

Automated summary

This study aims to explore individualized remedial dosing regimens for delayed or missed doses of commonly used antiseizure medications. Monte Carlo simulation based on population pharmacokinetic models was employed to investigate six remedial strategies. It was found that the recommended remedial regimens were highly correlated to delayed time and the characteristics of the antiseizure medication. A web-based dashboard was developed to provide personalized remedial regimens.