Effect of Individual Patient Characteristics and Treatment Choices on Reliever Medication Use in Moderate-Severe Asthma: A Poisson Analysis of Randomised Clinical Trials

INTRODUCTION

Even though increased use of reliever medication, including short-acting beta agonists (SABA), provides an indirect measure of symptom worsening, there have been limited efforts to assess how different patterns of reliever use correlate with symptom control and future risk of exacerbations. Here, we evaluate the effect of individual baseline characteristics on reliever use in patients with moderate-severe asthma on regular maintenance therapy with fluticasone propionate (FP) or combination therapy with fluticasone propionate/salmeterol (FP/SAL) or budesonide/formoterol (BUD/FOR).

METHODS

A drug-disease model describing the number of 24-h puffs and overnight occasions was developed with data from five clinical studies (N = 6212). The model was implemented using a nonlinear mixed effects approach and a Poisson function, considering clinical and demographic baseline characteristics. Goodness of fit and model predictive performance were assessed. Heatmaps were created to summarise the effect of concurrent baseline factors on reliever utilisation.

RESULTS

The final model accurately described individual patterns of reliever use, which is significantly increased with time since diagnosis, smoking, higher Asthma Control Questionnaire (ACQ-5) score and higher body mass index (BMI) at baseline. Whilst the number of puffs decreases slowly after an initial drop relative to the start of treatment, exacerbating patients utilise significantly more reliever than those who do not exacerbate. The mean effect of FP/SAL (median dose: 250/50 μg BID) on reliever use was slightly higher than that of BUD/FOR (median dose: 160/4.5 μg BID), i.e. a 75.3% vs 69.3% reduction in reliever use, respectively.

CONCLUSIONS

The availability of individual-level patient data in conjunction with a parametric approach enabled the characterisation of interindividual differences in the patterns of reliever use in patients with moderate-severe asthma. Taken together, individual demographic and clinical characteristics, as well as exacerbation history, can be considered an indicator of the degree of asthma control. High SABA reliever use suggests suboptimal clinical management of patients on maintenance therapy.

Cardiac sodium channel inhibition by lamotrigine: in vitro characterization and clinical implications

Lamotrigine, approved for use as an antiseizure medication as well as the treatment of bipolar disorder, inhibits sodium channels in the brain to reduce repetitive neuronal firing and pathological release of glutamate. The shared homology of sodium channels and lack of selectivity associated with channel blocking agents can cause slowing of cardiac conduction and increased proarrhythmic potential. The Vaughan‐Williams classification system differentiates sodium channel blockers using biophysical properties of binding. As such, Class Ib inhibitors, including mexiletine, do not slow cardiac conduction as measured by the electrocardiogram, at therapeutically relevant exposure. Our goal was to characterize the biophysical properties of Na_V1.5 block and to support the observed clinical safety of lamotrigine. We used HEK‐293 cells stably expressing the hNa_V1.5 channel and voltage clamp electrophysiology to quantify the potency (half‐maximal inhibitory concentration) against peak and late channel current, on‐/off‐rate binding kinetics, voltage‐dependence, and tonic block of the cardiac sodium channel by lamotrigine; and compared to clinically relevant Class Ia (quinidine), Ib (mexiletine), and Ic (flecainide) inhibitors. Lamotrigine blocked peak and late Na_V1.5 current at therapeutically relevant exposure, with rapid kinetics and biophysical properties similar to the class Ib inhibitor mexiletine. However, no clinically meaningful prolongation in QRS or PR interval was observed in healthy subjects in a new analysis of a previously reported thorough QT clinical trial (SCA104648). In conclusion, the weak Na_V1.5 block and rapid kinetics do not translate into clinically relevant conduction slowing at therapeutic exposure and support the clinical safety of lamotrigine in patients suffering from epilepsy and bipolar disorder.

Effect of Age-Related Factors on the Pharmacokinetics of Lamotrigine and Potential Implications for Maintenance Dose Optimisation in Future Clinical Trials

BACKGROUND AND AIMS

In this study, we evaluate the performance of allometric concepts to predict the implications of age and size on the pharmacokinetics of lamotrigine, and assess the dose rationale across different age groups from 0.2 to 91 years.

METHODS

An allometrically scaled pharmacokinetic model was developed using adolescent and adult data, taking into account the effect of comedications. Model parameters were then used to extrapolate lamotrigine pharmacokinetics to older adults (> 65 years), children (4-12 years) and infants and toddlers (0.2-2.0 years). In addition, simulations were performed to identify the implication of different doses and dosing regimens for each population, so as to ensure steady-state concentrations within a predefined reference range.

RESULTS

The pharmacokinetics of lamotrigine was best described using a one-compartment model with first-order absorption and elimination. Carbamazepine, phenytoin, and valproic acid changed systemic clearance (CL) by + 76.5, + 129, and - 47.4%, respectively. Allometric principles allowed accurate extrapolation of disposition parameters to older adults and children older than 4 years of age. A maturation function was required to describe changes in exposure in younger patients. Compared with adults, a child aged 1.7 years has a 31.5% higher CL, after correcting for body weight. Patients > 65 years of age showed a decrease in CL of approximately 15%.

CONCLUSION

Population pharmacokinetic models are usually limited to a subgroup of patients, which may mask the identification of factors contributing to interindividual variability. The availability of an integrated model including the whole patient population provides insight into the role of age-related changes in the disposition of lamotrigine, and potential implications for maintenance dose optimisation in any future trials.

TRIAL REGISTRATION

According to GlaxoSmithKline's Clinical Trial Register, data from the GlaxoSmithKline studies LAM100034 and LEP103944, corresponding to ClinicalTrials.gov identifiers NCT00113165 and NCT00264615, used in this work, have been used in previous publications (doi: https://doi.org/10.1212/01.wnl.0000277698.33743.8b , https://doi.org/10.1111/j.1528-1167.2007.01274.x ).

Dose rationale and pharmacokinetics of dexmedetomidine in mechanically ventilated new-borns: impact of design optimisation

PURPOSE

There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates.

METHODS

A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study.

RESULTS

Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA.

CONCLUSIONS

The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population.

Futility of current urine salbutamol doping control

Aims

Salbutamol is used in the management of obstructive bronchospasm, including that of some elite athletes. It is claimed that high salbutamol (oral) doses may also have an anabolic effect. Therefore, inhalation of salbutamol is restricted by the World Anti‐Doping Agency (WADA) to a maximal daily dose. Urine is tested for violations, but recent cases have resulted in a debate regarding the validity of this approach. It was our aim to determine whether current approaches are sufficiently able to differentiate approved usage from violations.

Methods

We extracted pharmacokinetic parameters from literature for salbutamol and its sulphated metabolite. From these parameters, a semi‐physiological pharmacokinetic model of inhaled and orally administered salbutamol was synthesized, validated against literature data, and used to perform clinical trial simulations (n = 1000) of possible urine concentrations over time resulting from WADA‐allowed and oral unacceptable dosages.

Results

The synthesized model was able to predict the literature data well. Simulations showed a very large range of salbutamol concentrations, with a significant portion of virtual subjects (15.4%) exceeding the WADA threshold limit of 1000 ng ml⁻¹ at 1 h post‐dose.

Conclusions

The observed large variability in urine concentrations indicates that determining the administered dose from a single untimed urine sample is not feasible. The current threshold inadvertently leads to incorrect assumptions of violation, whereas many violations will go unnoticed, especially when samples are taken long after drug administration. These issues, combined with the dubious assertion of its anabolic effect, leads us to conclude that the large effort involved in testing should be reconsidered.

Population pharmacokinetics of oxcarbazepine and its metabolite 10-hydroxycarbazepine in healthy subjects

Oxcarbazepine is indicated for the treatment of partial or generalised tonic-clonic seizures. Most of the absorbed oxcarbazepine is converted into its active metabolite, 10-hydroxycarbazepine (MHD), which can exist as R-(-)- and S-(+)-MHD enantiomers. Here we describe the influence of the P-glycoprotein (P-gp) inhibitor verapamil, on the disposition of oxcarbazepine and MHD enantiomers, both of which are P-gp substrates. Healthy subjects (n=12) were randomised to oxcarbazepine or oxcarbazepine combined with verapamil at doses of 300mg b.i.d. and 80mg t.i.d., respectively. Blood samples (n=185) were collected over a period of 12h post oxcarbazepine dose. An integrated PK model was developed using nonlinear mixed effects modelling using a meta-analytical approach. The pharmacokinetics of oxcarbazepine was described by a two-compartment model with absorption transit compartments and first-order elimination. The concentration-time profiles of both MHD enantiomers were characterised by a one-compartment distribution model. Clearance estimates (95% CI) were 84.9L/h (69.5-100.3) for oxcarbazepine and 2.0L/h (1.9-2.1) for both MHD enantiomers. The volume of distribution was much larger for oxcarbazepine (131L (97-165)) as compared to R-(-)- and S-(+)-MHD (23.6L (14.4-32.8) vs. 31.7L (22.5-40.9), respectively). Co-administration of verapamil resulted in a modest increase of the apparent bioavailability of oxcarbazepine by 12% (10-28), but did not affect parent or metabolite clearances. Despite the evidence of comparable systemic levels of OXC and MHD following administration of verapamil, differences in brain exposure to both moieties cannot be excluded after P-glycoprotein inhibition.

Biomarkers in epilepsy-A modelling perspective

Biomarkers can be categorised from type 0 (genotype or phenotype), through 6 (clinical scales), each level representing a part of the processes involved in the biological system and drug treatment. This classification facilitates the identification and connection of information required to fully (mathematically) model a disease and its treatment using integrated information from biomarkers. Two recent reviews thoroughly discussed the current status and development of biomarkers for epilepsy, but a path towards the integration of such biomarkers for the personalisation of anti-epileptic drug treatment is lacking. Here we aim to 1) briefly categorise the available epilepsy biomarkers and identify gaps, and 2) provide a modelling perspective on approaches to fill such gaps. There is mainly a lack of biomarker types 2 (target occupancy) and 3 (target activation). Current literature typically focuses on qualitative biomarkers for diagnosis and prediction of treatment response or failure, leaving a need for biomarkers that help to quantitatively understand the overall system to explain and predict differences in disease and treatment outcome. Due to the complexity of epilepsy, filling the biomarker gaps will require collaboration and expertise from the fields of systems biology and systems pharmacology.

Pharmacokinetic interactions and dosing rationale for antiepileptic drugs in adults and children

AIMS

Population pharmacokinetic modelling has been widely used across many therapeutic areas to identify sources of variability, which are incorporated into models as covariate factors. Despite numerous publications on pharmacokinetic drug-drug interactions (DDIs) between antiepileptic drugs (AEDs), such data are not used to support the dose rationale for polytherapy in the treatment of epileptic seizures. Here we assess the impact of DDIs on plasma concentrations and evaluate the need for AED dose adjustment.

METHODS

Models describing the pharmacokinetics of carbamazepine, clobazam, clonazepam, lamotrigine, levetiracetam, oxcarbazepine, phenobarbital, phenytoin, topiramate, valproic acid and zonisamide in adult and paediatric patients were collected from the published literature and implemented in NONMEM v7.2. Taking current clinical practice into account, we explore simulation scenarios to characterize AED exposure in virtual patients receiving mono- and polytherapy. Steady-state, maximum and minimum concentrations were selected as parameters of interest for this analysis.

RESULTS

Our simulations show that DDIs can cause major changes in AED concentrations both in adults and children. When more than one AED is used, even larger changes are observed in the concentrations of the primary drug, leading to significant differences in steady-state concentration between mono- and polytherapy for most AEDs. These results suggest that currently recommended dosing algorithms and titration procedures do not ensure attainment of appropriate therapeutic concentrations.

CONCLUSIONS

The effect of DDIs on AED exposure cannot be overlooked. Clinical guidelines must consider such covariate effects and ensure appropriate dosing recommendations for adult and paediatric patients who require combination therapy.

Pharmacotherapy in pediatric epilepsy: from trial and error to rational drug and dose selection - a long way to go

INTRODUCTION

Whereas ongoing efforts in epilepsy research focus on the underlying disease processes, the lack of a physiologically based rationale for drug and dose selection contributes to inadequate treatment response in children. In fact, limited information on the interindividual variation in pharmacokinetics and pharmacodynamics of anti-epileptic drugs (AEDs) in children drive prescription practice, which relies primarily on dose regimens according to a mg/kg basis. Such practice has evolved despite advancements in pediatric pharmacology showing that growth and maturation processes do not correlate linearly with changes in body size.

AREAS COVERED

In this review we aim to provide 1) a comprehensive overview of the sources of variability in the response to AEDs, 2) insight into novel methodologies to characterise such variation and 3) recommendations for treatment personalisation.

EXPERT OPINION

The use of pharmacokinetic-pharmacodynamic principles in clinical practice is hindered by the lack of biomarkers and by practical constraints in the evaluation of polytherapy. The identification of biomarkers and their validation as tools for drug development and therapeutics will require some time. Meanwhile, one should not miss the opportunity to integrate the available pharmacokinetic data with modeling and simulation concepts to prevent further delays in the development of personalised treatments for pediatric patients.