Handling Delayed or Missed Dose of Antiseizure Medications: A Model-Informed Individual Remedial Dosing

External Validation of the Population Pharmacokinetic Models of Amisulpride and Remedial Strategies for Delayed or Missed Doses

Objective

This study aimed to evaluate the predictive performance of published amisulpride population pharmacokinetic (PopPK) models in schizophrenia patients with an external data set and establish remedial dosing regimens for nonadherent amisulpride-treated patients.

Methods

A systematic search was conducted on PubMed, Embase, and Web of Science to identify PopPK models for evaluation. The evaluation process involved analyzing 390 serum concentration samples obtained from 361 Chinese adult inpatients diagnosed with schizophrenia. Model predictability was evaluated by prediction-based and simulation-based diagnostics. Based on validation results, a modified PopPK model was constructed to characterize amisulpride pharmacokinetic in our patients. Monte Carlo simulation was employed to investigate non-adherence scenarios and the impact of subsequently administered remedial regimens.

Results

In the five assessed published models, four included trough concentrations from schizophrenia patients, and one combined single-dose data from healthy older adults and trough concentrations from older adults with Alzheimer's disease. The PE for population and individual predictions ranged from -92.89% to 27.02% and -24.82% to 4.04%, respectively. In the simulation-based diagnostics, the NPDE results indicated noticeable bias in all models. Therefore, a modified one-compartment model, with estimated creatinine clearance(eCLcr) as covariates on the apparent clearance (CL/F) of amisulpride, was developed. For delays in medication dosing, if the delay is within 12 hours, take half the missed dose right away, then resume the normal schedule; if the delay is up to 24 hours, just continue with the regular dosing schedule.

Conclusion

Existing published models lack the necessary reliability for cross-center application. Future prospective studies are required to assess our model before integrating it into clinical practice. Model-based simulations provided a rational approach to propose remedial strategies for delayed or missed doses.

Handling delayed or missed direct oral anticoagulant doses: model-informed individual remedial dosing

ABSTRACT

Nonadherence to direct oral anticoagulant (DOAC) pharmacotherapy may increase the risk of thromboembolism or bleeding, and delayed or missed doses are the most common types of nonadherence. Current recommendations from regulatory agencies or guidelines regarding this issue lack evidence and fail to consider individual differences. This study aimed to develop individual remedial dosing strategies when the dose was delayed or missed for DOACs, including rivaroxaban, apixaban, edoxaban, and dabigatran etexilate. Remedial dosing regimens based on population pharmacokinetic (PK)-pharmacodynamic (PD) modeling and simulation strategies were developed to expeditiously restore drug concentration or PD biomarkers within the therapeutic range. Population PK-PD characteristics of DOACs were retrieved from previously published literature. The effects of factors that influence PK and PD parameters were assessed for their impact on remedial dosing regimens. A web-based dashboard was established with R-shiny to recommend remedial dosing regimens based on patient traits, dosing schedules, and delay duration. Addressing delayed or missed doses relies on the delay time and specific DOACs involved. Additionally, age, body weight, renal function, and polypharmacy may marginally affect remedial strategies. The proposed remedial dosing strategies surpass current recommendations, with less deviation time beyond the therapeutic range. The online dashboard offers quick and convenient solutions for addressing missed or delayed DOACs, enabling individualized remedial dosing strategies based on patient characteristics to mitigate the risks of bleeding and thrombosis.

Model-Informed individualized dosage regimen of sirolimus in pediatric patients with intractable lymphatic malformations

Intractable lymphatic malformations (iLM) pose a significant threat to affected children, demonstrating limited responses to conventional treatments. Sirolimus, effectively inhibiting endothelial cell proliferation in lymphatic vessels, plays a crucial role in iLM treatment. However, the drug's narrow therapeutic window and substantial interindividual variability necessitate customized dosing strategies. This study aims to establish a Population Pharmacokinetic Model (PopPK model) for sirolimus in pediatric iLM patients, identifying quantitative relationships between covariates and sirolimus clearance and volume of distribution. Initial dosages are recommended based on a target concentration range of 5-15 ng/mL. Retrospective data from our institution, encompassing 53 pediatric patients with 275 blood concentration results over the past five years (average age: 4.64 ± 4.19 years), constituted the foundation of this analysis. The final model, adopting a first-order absorption and elimination single-compartment model, retained age as the sole covariate. Results indicated a robust correlation between apparent clearance (CL/F) at 5.56 L/h, apparent volume of distribution (V/F) at 292.57 L, and age. Monte Carlo simulation guided initial dosages for patients aged 0-18 years within the target concentration range. This study presents the first PopPK model using a large Therapeutic Drug Monitoring (TDM) database to describe personalized sirolimus dosing for pediatric iLM patients, contributing to pharmacokinetic guidance and potentially improving long-term clinical outcomes.

How to handle a missed or delayed dose of lacosamide in pediatric patients with epilepsy? a mode-informed individual dosing

This study aims to investigate the effects on the pharmacokinetic (PK) of lacosamide (LCM), and to guide the individual dosing regimens for children and ones with poor medication adherence. Population PK research was performed based on 164 plasma samples of 113 pediatric patients aged from 1.75 to 14.42 years old. The PK characteristic of LCM was developed by a one-compartment model with first-order elimination. The typical value of apparent clearance (CL) and apparent volume of distribution (Vd) was 1.91 L·h-1 and 56.53 L respectively. In the final model, the variability of CL was significantly associated with the body surface area (BSA) and elevated uric acid (UA) level. In contrast, the impact of some prevalent anti-seizure medicines, such as valproic acid, levetiracetam, oxcarbazepine, lamotrigine, and perampanel, and gene polymorphisms of Cytochrome P450 (CYP)2C19, ATP-binding cassette (ABC)B1, and ABCC2 had no clinical significance on the PK parameters of LCM. BSA-based dosing regimen of LCM was provided according to Monte Carlo simulation approach; while the dosage should reduce half in patients with an UA level of more than 400 μmol·L-1 comparing with an UA level of 100 μmol·L-1. Individualize remedial doses of about 0.5- to 1.5-fold of regular doses were recommended in six common scenarios of missed or delayed doses, that depended on the delayed time. In current study, the population PK model of LCM in children with epilepsy was developed successfully. The BSA-based dosing regimen and individualized remedial strategy were recommended to guarantee the precise administration of LCM.

Managing delayed or missed pregabalin doses in patients with focal epilepsy: a Monte Carlo simulation study

BACKGROUND

Delayed or missed doses are inevitable in epilepsy pharmacotherapy. The current remedial measures recommended by the United States Food and Drug Administration (FDA) for non-adherence are generic and lack clinical evidence.

AIM

To assess remedial strategies for delayed or missed pregabalin doses in patients with epilepsy using Monte Carlo simulations.

METHOD

Monte Carlo simulations were performed using a published population pharmacokinetic model for pregabalin. The applicability of five proposed remedial regimens as well as FDA recommendations was evaluated by simulating various poor adherence scenarios in eight populations, including those with renal dysfunction.

RESULTS

All proposed remedial strategies were associated with delay duration and renal function. When delays are relatively short, an immediate regular dose is advised. The cut-off time points for taking the regular dose as a remedial regimen were 1, 2, 4, and 12 h for patients with mild renal impairment and normal renal function, moderate renal impairment, severe renal impairment, and end-stage renal disease, respectively. However, when delay aligns closely with a dosing interval, a regular dose combined with a partial dose proves effective. Generally, supplementing 1.3-fold the regular dose at the next scheduled time adequately compensates for the missed dose.

CONCLUSION

Model-based simulations provided quantitative evidence for the effectiveness and feasibility of remedial strategies for missed or delayed pregabalin doses.

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

Handling Delayed or Missed Dose of Antiseizure Medications: A Model-Informed Individual Remedial Dosing Li ZR, Wang CY, Lin WW, Chen YT, Liu XQ, Jiao Z. Neurology . 2023;100(9):e921-e931. doi:10.1212/WNL.0000000000201604 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.