How to handle the delayed or missed dose of rivaroxaban in patients with non-valvular atrial fibrillation: model-informed remedial dosing

Remedial Dosing Recommendations for Sirolimus Delayed or Missed Dosages Caused by Poor Medication Compliance in Pediatric Tuberous Sclerosis Complex Patients

BACKGROUND

Delayed or missed dosages caused by poor medication compliance significantly affected the treatment of diseases in children.

AIMS

The present study aimed to investigate the influence of delayed or missed dosages on sirolimus pharmacokinetics (PK) in pediatric tuberous sclerosis complex (TSC) patients and to recommend remedial dosages for nonadherent patients.

METHODS

A published sirolimus population PK model in pediatric TSC patients was used to assess the influence of different nonadherence scenarios and recommend optimally remedial dosages based on Monte Carlo simulation. Thirteen nonadherent scenarios were simulated in this study, including delayed 2h, 4 h, 6 h, 8 h, 10 h, 12 h, 14 h, 16 h, 18 h, 20 h, 22 h, 23.5 h, and missed one dosage. Remedial dosing strategies contained 10-200% of scheduled dosages. The optimal remedial dosage was that with the maximum probability of returning the individual therapeutic range.

RESULTS

For delayed or missed sirolimus dosages in pediatric TSC patients, when the delayed time was 0-8 h, 8-10 h, 10-18 h, 18-22.7 h, 22.7-24 h, 70%, 60%, 40%, 30%, 20% scheduled dosages were recommended to take immediately. When one dosage was missed, 120% of scheduled dosages were recommended at the next dose.

CONCLUSION

It was the first time to recommend remedial dosages for delayed or missed sirolimus therapy caused by poor medication compliance in pediatric TSC patients based on Monte Carlo simulation. Meanwhile, the present study provided a potential solution for delayed or missed dosages in clinical practice.

Safety, pharmacokinetics and exploratory exposure-response analysis of CX3002, a novel inhibitor of Xa, in Chinese healthy subjects

BACKGROUND AND OBJECTIVE

CX3002 is a structurally novel inhibitor of factor Xa, with promising prospects. This study aims to report the results of a first-in-human ascending-dose study of CX3002 in Chinese healthy subjects, and to establish an exploratory population pharmacokinetic/pharmacodynamic (PK/PD) model to investigate the exposure-response relationship of CX3002.

METHODS

The randomized, double-blind, placebo-controlled study included six single-dose groups and three multiple-dose groups, with a dose range of 1-30 mg. Safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) of CX3002 were evaluated. PK of CX3002 was analyzed using both non-compartment method and population modeling. PK/PD model was developed using nonlinear mixed effect modeling approach and was evaluated by prediction-corrected visual predictive check and bootstrap methods.

RESULTS

A total of 84 subjects were enrolled and all participants completed the study. CX3002 exhibited satisfactory safety and tolerability in healthy subjects. C_max and AUC of CX3002 increased with dose from 1 mg to 30 mg, but less-than-proportional increases were observed. There was no obvious accumulation with multiple doses. Anti-Xa activity showed dose-related increases after administration of CX3002 but not placebo. The PK of CX3002 was well described by a two-compartment model with a modification of bioavailability according to dose, and anti-Xa activity was described by a Hill function. No covariate was identified significant based on the limited data in this study.

CONCLUSIONS

CX3002 was well tolerated and resulted in dose-related anti-Xa activity across the dose range. The PK of CX3002 were predictable, and correlated with PD effects. Continued clinical investigation of CX3002 was supported. Chinadrugtrials.org.cn identifier: CTR20190153.

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

BACKGROUND AND OBJECTIVES

Delayed or missed antiseizure medications (ASMs) doses are common during long-term or lifelong antiepilepsy treatment. This study aims to explore optimal individualized remedial dosing regimens for delayed or missed doses of 11 commonly used ASMs.

METHODS

To explore remedial dosing regimens, Monte Carlo simulation was used 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 used to perform Monte Carlo simulation and recommend individual remedial regimens.

RESULTS

The recommended remedial regimens were highly correlated with delayed time, scheduled dosing interval, and half-life of the ASM. Moreover, the optimal remedial regimens for pediatric and adult patients were different. The renal function, along with concomitant medication that affects the clearance of the ASM, 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 ASMs in pediatric and adult patients with epilepsy.

Machine learning advances the integration of covariates in population pharmacokinetic models: Valproic acid as an example

Background and Aim: Many studies associated with the combination of machine learning (ML) and pharmacometrics have appeared in recent years. ML can be used as an initial step for fast screening of covariates in population pharmacokinetic (popPK) models. The present study aimed to integrate covariates derived from different popPK models using ML.

Methods: Two published popPK models of valproic acid (VPA) in Chinese epileptic patients were used, where the population parameters were influenced by some covariates. Based on the covariates and a one-compartment model that describes the pharmacokinetics of VPA, a dataset was constructed using Monte Carlo simulation, to develop an XGBoost model to estimate the steady-state concentrations (Css) of VPA. We utilized SHapley Additive exPlanation (SHAP) values to interpret the prediction model, and calculated estimates of VPA exposure in four assumed scenarios involving different combinations of CYP2C19 genotypes and co-administered antiepileptic drugs. To develop an easy-to-use model in the clinic, we built a simplified model by using CYP2C19 genotypes and some noninvasive clinical parameters, and omitting several features that were infrequently measured or whose clinically available values were inaccurate, and verified it on our independent external dataset.

Results: After data preprocessing, the finally generated combined dataset was divided into a derivation cohort and a validation cohort (8:2). The XGBoost model was developed in the derivation cohort and yielded excellent performance in the validation cohort with a mean absolute error of 2.4 mg/L, root-mean-squared error of 3.3 mg/L, mean relative error of 0%, and percentages within ±20% of actual values of 98.85%. The SHAP analysis revealed that daily dose, time, CYP2C19*2 and/or *3 variants, albumin, body weight, single dose, and CYP2C19*1*1 genotype were the top seven confounding factors influencing the Css of VPA. Under the simulated dosage regimen of 500 mg/bid, the VPA exposure in patients who had CYP2C19*2 and/or *3 variants and no carbamazepine, phenytoin, or phenobarbital treatment, was approximately 1.74-fold compared to those with CYP2C19*1/*1 genotype and co-administered carbamazepine + phenytoin + phenobarbital. The feasibility of the simplified model was fully illustrated by its performance in our external dataset.

Conclusion: This study highlighted the bridging role of ML in big data and pharmacometrics, by integrating covariates derived from different popPK models.

Optimization of initial dose regimen of tacrolimus in paediatric lung transplant recipients based on Monte Carlo simulation

WHAT IS KNOWN AND OBJECTIVES

The initial tacrolimus dose regimen in paediatric lung transplant recipients is unknown. The present study optimized the initial tacrolimus dose regimen for paediatric lung transplant recipients.

METHODS

This study was based on a published population pharmacokinetic model of tacrolimus in lung transplant recipients and used Monte Carlo simulations to recommend an initial dose regimen of tacrolimus in paediatric lung transplant recipients.

RESULTS

Without voriconazole, the tacrolimus doses recommended for paediatric lung transplant recipients who were not CYP3A5*1 carriers were 0.02, 0.03, and 0.04 mg/kg/day, split into two doses, for weights of 10-16, 16-30, and 30-40 kg, respectively. For paediatric lung transplant recipients who were CYP3A5*1 carriers, the tacrolimus doses of 0.03, 0.04, 0.05, and 0.06 mg/kg/day, split into two doses, were recommended for weights of 10-16, 16-25, 25-30, and 30-40 kg, respectively. With voriconazole, the tacrolimus dose recommended for paediatric lung transplant recipients who were not CYP3A5*1 carriers was 0.02 mg/kg/day, split into two doses, for weights of 10-40 kg. For paediatric lung transplant recipients who were CYP3A5*1 carriers, tacrolimus doses of 0.02 and 0.03 mg/kg/day, split and two doses, were recommended for weights of 10-24 and 24-40 kg, respectively.

WHAT IS NEW AND CONCLUSIONS

This study developed tacrolimus dose regimens for the first time for paediatric lung transplant recipients using Monte Carlo simulation and optimized initial dosage in paediatric lung transplant recipients.

How to handle a delayed or missed dose of edoxaban in patients with non-valvular atrial fibrillation? A model-informed remedial strategy

AIM

Edoxaban is a non-vitamin K antagonist oral anticoagulant (NOAC) widely used for the long-term prevention of stroke in patients with non-valvular atrial fibrillation (NVAF). Adherence to NOAC therapy has been unsatisfactory and decreases over time. Remedial strategies are currently used to address the non-adherence events. Current recommendations, however, are generic and not well supported by evidence. The aim of this study was to explore appropriate remedial dosing regimens for non-adherent edoxaban-treated NVAF patients through the Monte Carlo simulation.

METHODS

Six regimens were compared with the current recommendations of the European Heart Rhythm Association (EHRA) guide based on total deviation time. Both edoxaban plasma concentration and intrinsic Factor Xa activity were considered. Monte Carlo simulations were performed using RxODE based on a published population pharmacokinetics/pharmacodynamics (PK/PD) model.

RESULTS

The proposed remedial strategies were different than the EHRA recommendations and were related to the delay time. However, it was found that the missed dose can be administered immediately if the delay time is within 11 h. When the delay is between 12 and 19 h, a half dose followed by a regular dosing schedule is recommended. When the delay time exceeds 19 h, a full dose followed by a half dose is preferred.

CONCLUSION

PK/PD modelling and simulation are effective in developing and evaluating the remedial strategies of edoxaban, which can help maximise its therapeutic effect.