The effect of poor compliance on the pharmacokinetics of carbamazepine and its epoxide metabolite using Monte Carlo simulation

How drug onset rate and duration of action affect drug forgiveness

Medication nonadherence is one of the largest problems in healthcare today, particularly for patients undergoing long-term pharmacotherapy. To combat nonadherence, it is often recommended to prescribe so-called "forgiving" drugs, which maintain their effect despite lapses in patient adherence. Nevertheless, drug forgiveness is difficult to quantify and compare between different drugs. In this paper, we construct and analyze a stochastic pharmacokinetic/pharmacodynamic (PK/PD) model to quantify and understand drug forgiveness. The model parameterizes a medication merely by an effective rate of onset of effect when the medication is taken (on-rate) and an effective rate of loss of effect when a dose is missed (off-rate). Patient dosing is modeled by a stochastic process that allows for correlations in missed doses. We analyze this "on/off" model and derive explicit formulas that show how treatment efficacy depends on drug parameters and patient adherence. As a case study, we compare the effects of nonadherence on the efficacy of various antihypertensive medications. Our analysis shows how different drugs can have identical efficacies under perfect adherence, but vastly different efficacies for adherence patterns typical of actual patients. We further demonstrate that complex PK/PD models can indeed be parameterized in terms of effective on-rates and off-rates. Finally, we have created an online app to allow pharmacometricians to explore the implications of our model and analysis.

Assessment of adherence to carbamazepine using plasma and saliva samples, a study from Jordan

Background

The measurement of carbamazepine levels in a biological sample is required to guide dosing, and prevent toxicity, and can be useful to assess medication adherence.

Aim

The primary aim of the presented study is to analyze carbamazepine levels in saliva and plasma samples of outpatients and to assess adherence to carbamazepine using saliva and plasma levels.

Methods

Adults who used carbamazepine for at least one month were recruited from the outpatient clinic department of Princess Basma Hospital, a public hospital in Irbid. Saliva and blood samples (1 ml) were collected simultaneously from subjects, and using a microanalytical method with high-performance liquid chromatography coupled with an ultraviolet detector, the level of carbamazepine (in micrograms per milliliter) was ascertained. Analysis of adherence to carbamazepine was carried out using plasma and saliva levels.

Results

A total of 69 consecutive patients attending the neurology clinic were recruited, of whom 85.5% had epilepsy. Approximately one-third (34.8%) used carbamazepine as monotherapy, whereas the remainder used a combination of antiepileptic drugs to control seizures. Overall, about two-thirds (71.9%) of the studied samples were non-adherent in either plasma or saliva samples. By referring to the plasma sample carbamazepine concentration, 75.4% of the respondents were adherents, 15.9% had under-adherence, and 8.7% had over-adherence. A total of 85.9% of the responders were adherent using the carbamazepine level in saliva samples. Plasma and saliva carbamazepine levels were linearly correlated to one another. Polypharmacy was commonly utilized with the patients, as 42% of the patients used two medications, with a range of 1-7 drugs used concomitantly. The predictor associated with higher plasma and saliva carbamazepine levels, as determined by multiple linear regression analysis, was the occurrence of seizures less than once a month, as compared to seizures with higher frequencies.

Conclusion

Saliva carbamazepine levels show the potential to be used as an alternative matrix to assess medication adherence, with a considerable correlation with the plasma carbamazepine level. Healthcare professionals can address routine care non-adherence through such measures.

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.

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.

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.

The effect of nonadherence on phenobarbital concentrations and recommendations on the replacement dose using Monte Carlo simulation

OBJECTIVES

To determine the impacts of missed phenobarbital (PB) doses on its pharmacokinetics and to investigate the appropriate replacement dosing scheme for various PB missed dose scenarios.

METHODS

Monte Carlo simulations were performed using parameters from the selected population pharmacokinetic study. The impacts of missed PB dose and the proper replacement dosing scheme were assessed based on the percent deviation of simulated concentrations outside the reference range from the full adherence scenario.

RESULTS

The impact of missed PB dose on its concentrations depended on the daily dose. The replacement with a respective regular dose and one and a half regular dose was appropriate for the one and two missed doses scenarios for patients receiving PB monotherapy. For patients receiving PB with valproic acid or phenytoin, the same replacement scheme was still appropriate. The results also indicated that weight did not influence the proper replacement dosing scheme.

CONCLUSIONS

The impacts of missed PB doses on its pharmacokinetics were identified and the proper replacement dosing schemes for different missed dose scenarios were proposed. These schemes should be implemented based on the clinician's justification of the patient's seizure control.

Lithium replacement dose recommendations using Monte Carlo simulations

OBJECTIVES

Missed medication doses are a common clinical problem, and cause consternation when prescribing lithium because its plasma levels must be kept within a narrow therapeutic window. Therefore, this study set out to determine the potential impact of missed lithium doses on its pharmacokinetics, and to explore the optimal compensatory dosing scheme. This is difficult to determine clinically and in research because of ethical constraints and therefore we modelled the effects using simulations.

METHODS

Monte Carlo simulations were used to simulate lithium concentrations under different missed dose scenarios. For patients with normal renal function, the optimal replacement dosing scheme was selected based on the lowest percentage of deviation from the full adherence scenario. However, for patients with renal impairment the appropriate dosing schedule was selected based on the lowest number of simulated concentrations above the upper range of 1.2 mEq/L.

RESULTS

The impact of a missed lithium dose depended on its daily dose. The higher the daily dose, the higher the deviation from full adherence. In patients with normal renal function, replacement with a regular dose was most appropriate. But in patients with renal impairment, replacement with a partial dose appeared to be most suitable.

CONCLUSIONS

This study has enabled insights into the optimal suitable lithium replacement dosing schemes for patients with normal renal function and renal impairment. These proposed schemes can be used cautiously in clinical practice in conjunction with clinician judgment and can also be used as a basis for future clinical research.

Assessment of the long-term efficacy and safety of adjunctive perampanel in adolescent patients with epilepsy: Post hoc analysis of open-label extension studies

OBJECTIVE

This post hoc analysis of four open-label extension (OLEx) studies evaluated the long-term efficacy and safety of adjunctive perampanel in adolescent patients (aged 12 to ≤17 years) with focal-onset seizures (FOS), with/without focal to bilateral tonic-clonic seizures (FBTCS), or generalized tonic-clonic seizures (GTCS).

METHODS

Patients who completed one of six double-blind, placebo-controlled studies could enter one of four OLEx studies comprising a blinded Conversion Period (6-16 weeks) followed by a Maintenance Phase (27 to ≤256 weeks; perampanel dose: ≤12 mg/day). Exposure, retention, seizure outcomes, and treatment-emergent adverse events (TEAEs) were analyzed. Efficacy outcomes were analyzed using observed case and last observation carried forward (LOCF) approaches; the latter was used to account for early dropouts.

RESULTS

The Full Analysis Set comprised 309 adolescents with FOS (FBTCS, n = 109) and 19 with GTCS, and the Safety Analysis Set comprised 311 with FOS (FBTCS, n = 110) and 19 with GTCS. Mean (standard deviation) cumulative duration of perampanel exposure (weeks) was: FOS, 77.7 (58.7); FBTCS, 88.7 (63.8); and GTCS, 97.0 (35.5). Retention rates were maintained for ≤2 years (FOS, 50.0 %; FBTCS, 57.1 %; GTCS, 41.7 %). Seizure control (median percent reduction in seizure frequency/28 days) was sustained for up to 2 years; FOS (59.4 %, n = 113), FBTCS (64.6 %, n = 53), and GTCS (86.5 %, n = 17). At Year 2, 50 % responder rates were: FOS, 58.4 % (n = 66); FBTCS, 54.7 % (n = 29); and GTCS, 82.4 % (n = 14); seizure-freedom rates were: FOS, 5.3 % (n = 6); FBTCS, 24.5 % (n = 13); and GTCS, 35.3 % (n = 6). Long-term seizure control was observed even in LOCF analyses. The incidence of TEAEs was highest during Year 1 (FOS, n = 269 [86.5 %]; FBTCS, n = 95 [86.4 %]; GTCS, n = 15 [78.9 %]), compared with Years 2-4; the most common (≥10 % of patients) were dizziness, somnolence, and nasopharyngitis. No new safety signals emerged with long-term treatment.

CONCLUSIONS

This post hoc analysis suggests that long-term (≤2 years) adjunctive perampanel (≤12 mg/day) is efficacious and generally well tolerated in adolescent patients with FOS, with or without FBTCS, or GTCS.

Simulations of topiramate dosage recommendations for poor compliance events

PURPOSE

To determine the influences of one or two consecutive missed topiramate (TPM) doses on TPM pharmacokinetics and to suggest the proper TPM replacement dosing schemes using Monte Carlo simulations.

METHODS

Monte Carlo simulations were performed for various replacement dosing schemes using the parameters from the published population pharmacokinetic models. The lowest percentage of deviation of simulated concentrations outside the reference range of 5-20 mg/L from the compliance scenario for each replacement dosing scheme was used as a criterion for choosing the proper replacement dosing scheme.

RESULTS

For the one missed dose, the replacement with an immediate regular dose and a partial dose resulted in the lowest and highest percentages of concentration below 5 mg/L, respectively. While the opposite results were observed for the upper bound of the reference range (20 mg/L). For the two consecutive missed doses, the replacement with one and a half-missed doses resulted in a lower percentage of deviation of concentrations below 5 mg/L from the compliance scenario than the replacement with one regular dose.

CONCLUSIONS

For the one missed dose, taking an immediate regular dose might be suitable for patients who require higher TPM levels, while for patients who require lower TPM levels, an immediate partial dose could be used. For the two consecutive missed doses, an immediate one and a half regular dose might be suitable. However, these results were merely based on simulations; thus, they should be used alongside the clinician's justification based on seizure control.

Effect of Nonadherence on Levetiracetam Pharmacokinetics and Remedial Dose Recommendations Using Monte Carlo Simulations

BACKGROUND AND OBJECTIVE

Nonadherence to levetiracetam (LEV) use can result in subtherapeutic concentrations and increase the risk of the occurrence of seizures. The impact of missing LEV doses on its pharmacokinetics and evidence of the appropriate remedial dose is lacking. This study has determined the influence of missed LEV doses on its pharmacokinetics and has explored the appropriate remedial dosage regimens.

METHODS

Monte Carlo simulation was used to assess the impacts of different remedial dosage regimens on LEV concentrations. Simulated LEV concentrations outside the individual therapeutic range were calculated for the compliance scenario and for each of the remedial dosage regimens. The percentage of deviation from the full compliance scenario was also calculated. The regimen with the lowest percentage of deviation was considered the most appropriate.

RESULTS

The suitable LEV remedial dose varied across the delay times. For one missed dose, a remedial regimen with a regular dose followed by the usual dose was suitable for a delay time of less than 6 h, while a replacement with a regular dose followed by a partial dose appeared to be appropriate for a delay time of 6 h and longer. This was justified based on the concerns of LEV toxicity when the remedial dose is close to the next scheduled dose. For two consecutive missed doses, a remedial dose with one and a half of the regular dose was suitable if the gap between that and the next dose was greater than 6 h.

CONCLUSIONS

The appropriate remedial dosage regimen for one and two consecutive missed doses of LEV have been proposed. These remedial regimens, however, should be applied with clinicians' judgment based on the clinical status of the patients.

Should patients skip late doses of medication? A pharmacokinetic perspective

Missed doses, late doses, and other dosing irregularities are major barriers to effective pharmacotherapy, especially for the treatment of chronic conditions. What should a patient do if they did not take their last dose at the prescribed time? Should they take it late or skip it? In this paper, we investigate the pharmacokinetic effects of taking a late dose. We consider a single compartment model with linear absorption and elimination for a patient instructed to take doses at regular time intervals. We suppose that the patient forgets to take a dose and then realizes some time later and must decide what remedial steps to take. Using mathematical analysis, we derive several metrics which quantify the effects of taking the dose late. The metrics involve the difference between the drug concentration time courses for the case that the dose is taken late and the case that the dose is taken on time. In particular, the metrics are the integral of the absolute difference over all time, the maximum of the difference, and the maximum of the integral of the difference over any single dosing interval. We apply these general mathematical formulas to levothyroxine, atorvastatin, and immediate release and extended release formulations of lamotrigine. We further show how population variability can be immediately incorporated into these results. Finally, we use this analysis to propose general principles and strategies for dealing with dosing irregularities.

The effect of nonadherence on phenobarbital concentrations and recommendations on the replacement dose using Monte Carlo simulation

OBJECTIVES

To determine the impacts of missed phenobarbital (PB) doses on its pharmacokinetics and to investigate the appropriate replacement dosing scheme for various PB missed dose scenarios.

METHODS

Monte Carlo simulations were performed using parameters from the selected population pharmacokinetic study. The impacts of missed PB dose and the proper replacement dosing scheme were assessed based on the percent deviation of simulated concentrations outside the reference range from the full adherence scenario.

RESULTS

The impact of missed PB dose on its concentrations depended on the daily dose. The replacement with a respective regular dose and one and a half regular dose was appropriate for the one and two missed doses scenarios for patients receiving PB monotherapy. For patients receiving PB with valproic acid or phenytoin, the same replacement scheme was still appropriate. The results also indicated that weight did not influence the proper replacement dosing scheme.

CONCLUSIONS

The impacts of missed PB doses on its pharmacokinetics were identified and the proper replacement dosing schemes for different missed dose scenarios were proposed. These schemes should be implemented based on the clinician's justification of the patient's seizure control.

Designing Drug Regimens that Mitigate Nonadherence

Medication adherence is a well-known problem for pharmaceutical treatment of chronic diseases. Understanding how nonadherence affects treatment efficacy is made difficult by the ethics of clinical trials that force patients to skip doses of the medication being tested, the unpredictable timing of missed doses by actual patients, and the many competing variables that can either mitigate or magnify the deleterious effects of nonadherence, such as pharmacokinetic absorption and elimination rates, dosing intervals, dose sizes, and adherence rates. In this paper, we formulate and analyze a mathematical model of the drug concentration in an imperfectly adherent patient. Our model takes the form of the standard single compartment pharmacokinetic model with first-order absorption and elimination, except that the patient takes medication only at a given proportion of the prescribed dosing times. Doses are missed randomly, and we use stochastic analysis to study the resulting random drug level in the body. We then use our mathematical results to propose principles for designing drug regimens that are robust to nonadherence. In particular, we quantify the resilience of extended release drugs to nonadherence, which is quite significant in some circumstances, and we show the benefit of taking a double dose following a missed dose if the drug absorption or elimination rate is slow compared to the dosing interval. We further use our results to compare some antiepileptic and antipsychotic drug regimens.

The PHARMACOM-EPI Framework for Integrating Pharmacometric Modelling Into Pharmacoepidemiological Research Using Real-World Data: Application to Assess Death Associated With Valproate

In pharmacoepidemiology, it is usually expected that the observed association should be directly or indirectly related to the pharmacological effects of the drug/s under investigation. Pharmacological effects are, in turn, strongly connected to the pharmacokinetic and pharmacodynamic properties of a drug, which can be characterized and investigated using pharmacometric models. Recently, the use of pharmacometrics has been proposed to provide pharmacological substantiation of pharmacoepidemiological findings derived from real-world data. However, validated frameworks suggesting how to combine these two disciplines for the aforementioned purpose are missing. Therefore, we propose PHARMACOM-EPI, a framework that provides a structured approach on how to identify, characterize, and apply pharmacometric models with practical details on how to choose software, format dataset, handle missing covariates/dosing data, how to perform the external evaluation of pharmacometric models in real-world data, and how to provide pharmacological substantiation of pharmacoepidemiological findings. PHARMACOM-EPI was tested in a proof-of-concept study to pharmacologically substantiate death associated with valproate use in the Danish population aged ≥ 65 years. Pharmacological substantiation of death during a follow-up period of 1 year showed that in all individuals who died (n = 169) individual predictions were within the subtherapeutic range compared with 52.8% of those who did not die (n = 1,084). Of individuals who died, 66.3% (n = 112) had a cause of death possibly related to valproate and 33.7% (n = 57) with well-defined cause of death unlikely related to valproate. This proof-of-concept study showed that PHARMACOM-EPI was able to provide pharmacological substantiation for death associated with valproate use in the study population.

What should patients do if they miss a dose of medication? A theoretical approach

Medication adherence is a major problem for patients with chronic diseases that require long term pharmacotherapy. Many unanswered questions surround adherence, including how adherence rates translate into treatment efficacy and how missed doses of medication should be handled. To address these questions, we formulate and analyze a mathematical model of the drug concentration in a patient with imperfect adherence. We find exact formulas for drug concentration statistics, including the mean, the coefficient of variation, and the deviation from perfect adherence. We determine how adherence rates translate into drug concentrations, and how this depends on the drug half-life, the dosing interval, and how missed doses are handled. While clinical recommendations require extensive validation and should depend on drug and patient specifics, as a general principle our theory suggests that nonadherence is best mitigated by taking double doses following missed doses if the drug has a long half-life. This conclusion contradicts some existing recommendations that cite long drug half-lives as the reason to avoid a double dose after a missed dose. Furthermore, we show that a patient who takes double doses after missed doses can have at most only slightly more drug in their body than a perfectly adherent patient if the drug half-life is long. We also investigate other ways of handling missed doses, including taking an extra fractional dose following a missed dose. We discuss our results in the context of hypothyroid patients taking levothyroxine.

What to Do About Missed Doses? A Retrospective Study of Olanzapine in the Elderly

Background

Schizophrenia is characterized by a high disease burden. Olanzapine is a common drug used in antipsychotic medication. Little is known about the population pharmacokinetics of olanzapine in elderly patients. Missed doses are a common and unavoidable issue during the treatment of psychiatric diseases, especially in elderly patients. This study aimed to identify what an elderly person should do if doses are inadvertently missed.

Methods

Data were collected from 140 elderly psychiatric patients (aged ≥65 years) who received olanzapine therapy. Olanzapine concentrations were determined by high pressure liquid chromatographic tandem mass spectrometry (HPLC-MS/MS) and a population-based approach was used to quantify the characteristics of elderly patients. A non-linear mixed-effects model was used for data analysis. Simulations based on the final model were applied to predict situations involving a single missed dose or three consecutive missed doses under several remedial regimens.

Results

A total of 474 samples from 140 elderly patients were included in the therapeutic drug monitoring (TDM) data analysis. A one-compartment model, with no significant covariates, was developed to describe the population pharmacokinetics of olanzapine in elderly patients. The population predicted systematic clearance (CL/F) and volumes of distribution (V/F) were 18 L/h and 785 L, respectively. The simulation demonstrated that in a missed dose situation, elderly patients should take the regular dose immediately; the refill dose used at the second remedial time point depends on the length of the time delay.

Conclusion

Here, we used a simulation to provide a remedial regimen for missed doses of olanzapine in the elderly population. Our simulation can provide valuable suggestions for individualized therapy in elderly patients.

Determination of serum carbamazepine and its metabolite by validated tandem mass spectrometric method and the effect of carbamazepine on various hematological and biochemical parameters

OBJECTIVES

The study aimed to develop a validated LC-MS / MS method for the measurement of carbamazepine and carbamazepine-10,11-epoxide (CBZE) levels, to compare the carbamazepine concentrations measured by AbSciex API 3200 LC-MS/MS and Beckman Coulter Emit® 2000 immunoassay and to investigate the effect of carbamazepine concentrations on various hematological and biochemical parameters.

METHODS

For the measurement of carbamazepine and CBZE levels, a validated LC-MS / MS method was developed. Serum carbamazepine levels of patients were measured by AbSciex API 3200 LC-MS / MS and Beckman Coulter Emit® 2000 immunoassay. Biochemical, hematological parameters, and hormone levels were measured by Beckman-Coulter AU 5800 (Beckman Coulter, Brea, USA), Beckman Coulter LH 780 (Beckman Coulter, Miami, FL, USA), and Cobas 6000 (Roche Diagnostics, Germany) analyzers, respectively.

RESULTS

The imprecision values for all analytes were less than 7.0 %. The correlation coefficient between the methods was 0.981 (95 % confidence interval: 0.975 to 0.985). Linear regression analysis demonstrated highly significant associations of carbamazepine concentrations with albumin (B = -0.300, p = 0.040), calcium (B = -0.262, p = 0.004), phosphorus (B = -0.241, p = 0.022), WBC (B = -0.288, p = <0.001), PLT (B = -0.236, p = 0.003), RBC (B = -0.257, p = 0.001), NEU% (B = -0.289, p = <0.001), LYM% (B = -0.268, p = 0.001), D vitamini (B = -0.344, p = 0.006) levels.

CONCLUSIONS

A robust, rapid, and simple method has been developed. Our study revealed that carbamazepine and its metabolite have a significant correlation and likely impact on bone metabolism, blood cell counts, serum protein, albumin levels, and electrolyte concentrations.

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

BACKGROUND

Rivaroxaban is an oral anticoagulant widely used for stroke prevention in patients with non-valvular atrial fibrillation (NVAF). During long-term anticoagulant therapy, delayed or missed doses are common. This study aimed to explore appropriate remedial dosing regimens for non-adherent rivaroxaban-treated patients.

METHODS

Monte Carlo simulation based on a previously established rivaroxaban population pharmacokinetic/pharmacodynamic (PK/PD) model for patients with NVAF was employed to design remedial dosing regimens. The proposed regimens were compared with remedial strategies in the European Heart Rhythm Association (EHRA) guide by assessing deviation time in terms of drug concentration, factor Xa activity, and prothrombin time.

RESULTS

The proposed remedial dosing regimens were dependent on delay duration. The missed dose should be taken immediately when the delay does not exceed 6 h; a half dose is advisable when the delay is between 6 and 20 h. A missed dose should be skipped if less than 4 h remains before the next dose. The proposed regimens resulted in shorter deviation time than that of the EHRA guide.

CONCLUSION

PK/PD modeling and simulation provide valid evidence on the remedial dosing regimen of rivaroxaban, which could help to minimize the risk of bleeding and thromboembolism.

Use of extended-release and immediate-release anti-seizure medications with a long half-life to improve adherence in epilepsy: A guide for clinicians

Poor adherence to anti-seizure medications (ASMs) is associated with breakthrough seizures and potentially increased toxicity in patients with epilepsy. Extended-release (ER) drugs and immediate-release (IR) drugs with a long half-life (t_1/2) that permit once-daily dosing (such as, perampanel, zonisamide, lamotrigine [IR, ER] and topiramate [ER]) have a number of advantages over short t_1/2 ASMs that require multiple daily dosing. These advantages include simplification of dosing regimens, reduction in pill burden, and a decrease in the peak-to-trough fluctuations in serum drug concentration that may be associated with a decreased risk of adverse effects and seizures. Such properties have wider implications in improving patient adherence to treatment. This article is intended as a practical guide for clinicians that provides an overview of the features of ER ASMs and long t_1/2 IR ASMs that are advantageous in the context of patient adherence and pharmacokinetic "forgiveness" (after missing a dose). In addition, we note that efforts to improve adherence should not depend solely on drug dosing regimens and drug pharmacokinetics, but should be part of a wider strategy that includes therapeutic drug monitoring, improved healthcare provider-patient dialogue, patient education, and the use of "reminder" technology.

Estrogen profile- and pharmacogenetics-based lamotrigine dosing regimen optimization: Recommendations for pregnant women with epilepsy

During pregnancy, various physiological changes occur that can alter the pharmacokinetics of antiepileptic drugs, such as lamotrigine (LTG). Anticipating the change in LTG dose required to achieve a pre-pregnancy target concentration is challenging. This study aimed to develop a refined population pharmacokinetic (PopPK) model of LTG in pregnant women with epilepsy (WWE) to identify factors explaining the variability in pharmacokinetics and to establish a model-informed individualized dosing regimen. On that basis, a coarsened model containing only clinical variables was also developed to examine its predictive performance compared to the refined model. In total, 322 concentration-time points from 51 pregnant WWE treated with LTG were employed to establish a refined PopPK model that included endogenous estrogen profiles, variants of candidate genes encoding LTG-metabolizing enzymes and -transporter proteins, and other clinical variables and a coarsened model that included only clinical variables, respectively. Data from an additional 11 patients were used for external validation of these two models. A nonlinear mixed-effect modeling approach was used for PopPK analysis of LTG. The standard goodness-of-fit method, bootstrap, normalized prediction distribution errors and external evaluation were adopted to estimate the stability and predictive performance of the candidate models. Akaike information criterion (AIC) was used to compare the goodness of fit between these two models. A lower AIC indicates a better fit of the data and the preferred model. Recommended dosing regimens for pregnant WWE were selected using Monte Carlo simulation based on the established optimal model. In the refined PopPK model, the population mean of apparent LTG clearance (CL/F) in pregnant WWE was estimated to be 2.82 L/h, with an inter-individual variability of 23.6%. PopPK analysis indicated that changes in estrogen profile during pregnancy were the predominant reason for the significant variations in LTG-CL/F. Up to the 3rd trimester, the concentration accumulation effect of E2 increased LTG-CL/F by 5.109 L/h from baseline levels. Contrary to effect of E2, E3 as the main circulating estrogen in pregnancy with a peak value of 34.41 ng/mL is 1000-fold higher than that in non-pregnancy reduced LTG-CL/F by 1.413 L/h. In addition, the UGT2B7 rs4356975 C > T and ABCB1 rs1128503 A > G variants may contribute to a better understanding of the inter-individual variability in LTG-CL/F. LTG-CL/F was 1.66-fold higher in UGT2B7 rs4356975 CT or TT genotype carriers than in CC genotype carriers. In contrast, ABCB1 rs1128503 GG genotype carriers had only 71.9% of the LTG-CL/F of AA or AG genotype carriers. In the coarsened PopPK model, the gestational age was a promising predictor of changes in LTG-CL/F. When comparing these two models, the refined PopPK model was favored over the coarsened PopPK model (AIC = -30.899 vs. -20.017). Monte Carlo simulation based on optimal PopPK model revealed that the LTG dosage administered to carriers of the UGT2B7 rs4356975 CT or TT genotype required a 33-50% increase to reach the pre-pregnancy target concentration, and carriers of the ABCB1 rs1128503 GG genotype required a 33-66% lower dose of LTG than carriers of the ABCB1 rs1128503 AA or AG genotype. Changes in estrogen profile during pregnancy was a better predictor of variations in LTG-CL/F than gestational age. The developed model based on estrogen profile and pharmacogenetics can serve as a foundation for further optimization of dosing regimens of LTG in pregnant WWE.

Therapeutic monitoring of carbamazepine and its active metabolite during the 1st postnatal month: Influence of drug interactions

OBJECTIVE

To receive information about carbamazepine and its active metabolite 10,11-epoxide transport into mature milk and suckling infants.

METHODS

In this cohort study, maternal serum, mature milk, and infant serum carbamazepine and epoxide levels were measured between the 6th and 29th postnatal day (carbamazepine in 1990-2017, epoxide in 1997-2017). Paired maternal serum, infant serum and milk levels were used for the assessment of ratios of this levels. The influence of combined treatment with enzyme-inducing antiepileptic drugs and valproic acid was assessed. Relationship between maternal serum, infant serum, and milk levels was also evaluated.

RESULTS

Maternal carbamazepine levels were 1.4-10.4 mg/L, milk 0.5-6.7 mg/L and infant 0.5-2.6 mg/L. Maternal 10,11-epoxide levels were 0.3-5.4 mg/L, milk 0.3-3.7 mg/L and infant 0.3-0.6 mg/L. Highly significant correlations were observed exclusively between milk and maternal serum levels of both carbamazepine and 10,11-epoxide. Concomitant administration of enzyme-inducing antiepileptic drugs significantly increased the maternal apparent oral clearance of carbamazepine by approximately 130%. Carbamazepine combined with valproic acid significantly increased epoxide levels in milk and maternal serum but not in breastfed infants.

CONCLUSIONS

In breastfed infants, carbamazepine levels did not reach the lower limit of the therapeutic range used for the general epileptic population, and the majority of epoxide levels were less than the lower limit of quantification. Routine monitoring of carbamazepine in these infants is not compulsory. However, observation of breastfed infants is desirable. If signs of potential adverse reactions are evident, infant serum concentrations should be monitor.

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.

Changing the Drug Delivery System: Does It Add to Non-Compliance Ramifications Control? A Simulation Study on the Pharmacokinetics and Pharmacodynamics of Atypical Antipsychotic Drug

This study investigates the pharmacokinetic (PK) and pharmacodynamic (PD) consequences of shifting from Quetiapine fumarate immediate-release (IR) to extended-release (XR) formulation in non-adherent schizophrenia patients. Monte-Carlo simulations using population PK and PD models were implemented to predict the time course of plasma concentration and Brief Psychiatric Rating Scale (BPRS) scores following the oral administration of 200 mg Seroquel^® every 12 h and 400 mg Seroquel XR^® every 24 h in patients experiencing dose delay, omission or doubling. Parameters were computed and their distributions were compared using the Kolmogorov–Smirnov test. Dose irregularities with both formulations had different effects on plasma concentration and %reduction in BPRS scores from baseline. However, the odds ratio of getting a %reduction in BPRS below 14%, or plasma concentration exceeding 500 µg/L, were comparable for adherent and non-adherent patients. Plasma therapeutic concentration after treatment cessation was maintained for <24 h in 48% and 29.6% of patients, and a steady state recovery time of <48 h was achieved in 51% and 13.4% of patients on the IR and XR formulations, respectively. Monte-Carlo simulations predict that the risks associated with the IR dose irregularities are not worsened when the XR formulation is used instead. Non-adherence events involving a single dose of either formulation do not require rescue doses.

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.

Beyond Adherence Thresholds: A Simulation Study of the Optimal Classification of Longitudinal Adherence Trajectories From Medication Refill Histories

Background: The description of adherence based on medication refill histories relies on the estimation of continuous medication availability (CMA) during an observation period. Thresholds to distinguish adherence from non-adherence typically refer to an aggregated value across the entire observation period, disregarding differences in adherence over time. Sliding windows to divide the observation period into smaller portions, estimating adherence for these increments, and classify individuals with similar trajectories into clusters can retain this temporal information. Optimal methods to estimate adherence trajectories to identify underlying patterns have not yet been established. This simulation study aimed to provide guidance for future studies by analyzing the effect of different longitudinal adherence estimates, sliding window parameters, and sample characteristics on the performance of a longitudinal clustering algorithm.

Methods: We generated samples of 250–25,000 individuals with one of six longitudinal refill patterns over a 2-year period. We used two longitudinal CMA estimates (LCMA1 and LCMA2) and their dichotomized variants (with a threshold of 80%) to create adherence trajectories. LCMA1 assumes full adherence until the supply ends while LCMA2 assumes constant adherence between refills. We assessed scenarios with different LCMA estimates and sliding window parameters for 350 independent samples. Individual trajectories were clustered with kml, an implementation of k-means for longitudinal data in R. We compared performance between the four LCMA estimates using the adjusted Rand Index (cARI).

Results: Cluster analysis with LCMA2 outperformed other estimates in overall performance, correct identification of groups, and classification accuracy, irrespective of sliding window parameters. Pairwise comparison between LCMA estimates showed a relative cARI-advantage of 0.12–0.22 (p < 0.001) for LCMA2. Sample size did not affect overall performance.

Conclusion: The choice of LCMA estimate and sliding window parameters has a major impact on the performance of a clustering algorithm to identify distinct longitudinal adherence trajectories. We recommend (a) to assume constant adherence between refills, (b) to avoid dichotomization based on a threshold, and (c) to explore optimal sliding windows parameters in simulation studies or selecting shorter non-overlapping windows for the identification of different adherence patterns from medication refill data.

Minocycline attenuates bone cancer pain in rats by inhibiting NF-κB in spinal astrocytes

AIM

To investigate the mechanisms underlying the anti-nociceptive effect of minocycline on bone cancer pain (BCP) in rats.

METHODS

A rat model of BCP was established by inoculating Walker 256 mammary carcinoma cells into tibial medullary canal. Two weeks later, the rats were injected with minocycline (50, 100 μg, intrathecally; or 40, 80 mg/kg, ip) twice daily for 3 consecutive days. Mechanical paw withdrawal threshold (PWT) was used to assess pain behavior. After the rats were euthanized, spinal cords were harvested for immunoblotting analyses. The effects of minocycline on NF-κB activation were also examined in primary rat astrocytes stimulated with IL-1β in vitro.

RESULTS

BCP rats had marked bone destruction, and showed mechanical tactile allodynia on d 7 and d 14 after the operation. Intrathecal injection of minocycline (100 μg) or intraperitoneal injection of minocycline (80 mg/kg) reversed BCP-induced mechanical tactile allodynia. Furthermore, intraperitoneal injection of minocycline (80 mg/kg) reversed BCP-induced upregulation of GFAP (astrocyte marker) and PSD95 in spinal cord. Moreover, intraperitoneal injection of minocycline (80 mg/kg) reversed BCP-induced upregulation of NF-κB, p-IKKα and IκBα in spinal cord. In IL-1β-stimulated primary rat astrocytes, pretreatment with minocycline (75, 100 μmol/L) significantly inhibited the translocation of NF-κB to nucleus.

CONCLUSION

Minocycline effectively alleviates BCP by inhibiting the NF-κB signaling pathway in spinal astrocytes.

Pharmacokinetic simulations of topiramate plasma concentrations following dosing irregularities with extended-release vs. immediate-release formulations

BACKGROUND

Once-daily extended-release (XR) antiepileptic drugs (AEDs) offer potential adherence and tolerability advantages over their BID immediate-release (IR) counterparts. However, patients with epilepsy will inevitably be at least occasionally nonadherent with a prescribed dosing regimen, regardless of formulation. Although perturbations in plasma concentrations due to dosing irregularities may have clinical consequences for AEDs with concentration-response relationships, clinical studies that deliberately expose patients to specific dosing irregularities in order to assess the effect on plasma concentrations and determine appropriate corrective actions would be unethical.

METHODS

Computer simulation was used to assess the impact of irregular dosing on topiramate (TPM) concentrations in noninduced (monotherapy/neutral cotherapy) and induced (adjunctive therapy with enzyme-inducing AEDs) states using a population pharmacokinetic (PK) model developed to predict steady-state plasma concentration-time profiles produced by once-daily Trokendi XR (extended-release topiramate capsules, Supernus Pharmaceuticals) and BID TPM-IR.

RESULTS

Computer simulations predicted that, relative to adherent dosing, delaying a dose 4 to 24h in noninduced patients would decrease trough (Cmin) levels 9% to 31% in the case of TPM-IR and 6% to 27% with Trokendi XR; a single omitted dose would reduce Cmin by 21% (TPM-IR) and 27% (Trokendi XR). After dose recovery to correct for a delayed or omitted dose, simulated peak concentration (Cmax) was higher than steady-state Cmax, regardless of formulation, although the magnitude of "overshoot" was consistently lower with Trokendi XR vs. TPM-IR. Doubling of a dose would increase Cmax by 26% and 28%, respectively. Predicted changes for nonadherent vs. adherent dosing were greater in the induced vs. noninduced state but were generally comparable for the two TPM formulations. Because the long half-life of TPM has been cited as a justification for QD dosing of TPM-IR, simulations also compared steady-state PK profiles of once-daily Trokendi XR and QD TPM-IR. Predicted TPM plasma concentration-time profiles were markedly different, as demonstrated by peak-trough fluctuation (QD TPM-IR, 64%; QD Trokendi XR, 18%) and 34% lower Cmin with QD TPM-IR.

CONCLUSIONS

Based on these simulations, dosing irregularities with once-daily Trokendi XR should pose no greater risk than with BID TPM-IR. In the event of a delayed or omitted Trokendi XR dose, TPM concentrations can be restored in noninduced and induced states by administering the delayed/omitted dose at any time during the next dosing interval or by adding the missed dose to the next scheduled dose.