Not-in-trial simulation I: Bridging cardiovascular risk from clinical trials to real-life conditions

Understanding the Clinical Implications of Individual Patient Characteristics and Treatment Choice on the Risk of Exacerbation in Asthma Patients with Moderate-Severe Symptoms

INTRODUCTION

The assessment of future risk has become an important feature in the management of patients with asthma. However, the contribution of patient-specific characteristics and treatment choices to the risk of exacerbation is poorly understood. Here we evaluated the effect of interindividual baseline differences on the risk of exacerbation and treatment performance in patients receiving regular maintenance doses of inhaled corticosteroids (ICS) or ICS/long-acting beta-agonists (LABA) combination therapy.

METHODS

Exacerbations and changes to asthma symptoms 5-item Asthma Control Questionnaire (ACQ-5) were simulated over a 12-month period using a time-to-event and a longitudinal model developed from phase III/IV studies in patients with moderate-severe asthma (N = 16,282). Simulations were implemented to explore treatment performance across different scenarios, including randomised designs and real-world settings. Treatment options included regular dosing with ICS monotherapy [fluticasone propionate (FP)] and combination therapy [fluticasone propionate/salmeterol (FP/SAL) or budesonide/formoterol (BUD/FOR)]. Exacerbation rate was analysed using the log-rank test. The cumulative incidence of events was summarised stratified by treatment.

RESULTS

Being a woman, smoker, having higher baseline ACQ-5 and body mass index (BMI) and lower forced expiratory volume in the first second (FEV1) are associated with increased exacerbation risk (p < 0.01). This risk is bigger in winter because of the seasonal variation effect. Across the different scenarios, the use of FP/SAL resulted in a 10% lower annual incidence of exacerbations relative to FP or regular dosing BUD/FOR, independently of baseline characteristics. Similar differences in the annual incidence of exacerbations were also observed between treatments in obese patients (BMI ≥ 25-35 kg/m2) (p < 0.01) and in patients who do not achieve symptom control on FP monotherapy.

CONCLUSIONS

Individual baseline characteristics and treatment choices affect future risk. Achieving comparable levels of symptom control whilst on treatment does not imply comparable risk reduction, as shown by the lower exacerbation rates in FP/SAL vs. BUD/FOR-treated patients. These factors should be considered as a basis for personalised clinical management of patients with moderate-severe asthma.

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.

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.

Characterizing QT interval prolongation in early clinical development: a case study with methadone

Recently, we have shown how pharmacokinetic–pharmacodynamic (PKPD) modeling can be used to assess the probability of QT interval prolongation both in dogs and humans. A correlation between species has been identified for a drug‐specific parameter, making it possible to prospectively evaluate nonclinical signals. Here, we illustrate how nonclinical data on methadone can be used to support the evaluation of dromotropic drug effects in humans. ECG and drug concentration data from a safety pharmacology study in dogs were analyzed using nonlinear mixed effects modeling. The slope of the PKPD model describing the probability of QT interval prolongation was extrapolated from dogs to humans and subsequently combined with methadone pharmacokinetic data as input for clinical trial simulations. Concentration versus time profiles were simulated for doses between 5 and 500 mg. Predicted peak concentrations in humans were then used as reference value to assess the probability of an increase in QT interval of ≥5 and ≥10 ms. Point estimates for the slope in dogs suggested low probability of ≥10 ms prolongation in humans, whereas an effect of approximately 5 ms increase is predicted when accounting for the 90% credible intervals of the drug‐specific parameter in dogs. Interspecies differences in drug disposition appear to explain the discrepancies between predicted and observed QT prolonging effects in humans. Extrapolation of the effects of racemic compound may not be sufficient to describe the increase in QT interval observed after administration of methadone to patients. Assessment of the contribution of enantioselective metabolism and active metabolites is critical.

Impact of disease, drug and patient adherence on the effectiveness of antiviral therapy in pediatric HIV

INTRODUCTION

Maintaining effective antiretroviral treatment for life is a major problem in both resource-limited and resource-rich countries. Despite the progress observed in paediatric antiretroviral therapy, approximately 12% of children still experience treatment failure due to drug resistance, inadequate dosing and poor adherence. We explore the current status of antiretroviral therapy in children with focus on the interaction between disease, drug pharmacokinetics and patient behavior, all of which are strongly interconnected and determine treatment outcome. Areas covered: An overview is provided of the viral characteristics and available drug combinations aimed at the prevention of resistance. In this context, the role of patient adherence is scrutinized. A detailed assessment of factors affecting adherence is presented together with the main strategies to enhance treatment response in children. Expert opinion: Using modeling and simulation, a framework for characterizing the forgiveness of non-adherence for specific antiretroviral drugs in children is proposed in which information on pharmacokinetics, pharmacokinetic-pharmacodynamic relationships and viral dynamics is integrated. This approach represents an opportunity for the simplification of dosing regimens taking into account the interaction between these factors. Based on clinical trial simulation scenarios, we envisage the possibility of assessing the impact of variable adherence to antiretroviral drug combinations in HIV-infected children.

Pharmacokinetic-pharmacodynamic modelling of drug-induced QTc interval prolongation in man: prediction from in vitro human ether-à-go-go-related gene binding and functional inhibition assays and conscious dog studies

BACKGROUND AND PURPOSE

Functional measures of human ether-à-go-go-related gene (hERG; Kv 11.1) channel inhibition have been prioritized as an in vitro screening tool for candidate molecules. However, it is unclear how these results can be translated to humans. Here, we explore how data on drug binding and functional inhibition in vitro relate to QT prolongation in vivo. Using cisapride, sotalol and moxifloxacin as paradigm compounds, we assessed the relationship between drug concentrations, binding, functional measures and in vivo effects in preclinical species and humans.

EXPERIMENTAL APPROACH

Pharmacokinetic-pharmacodynamic modelling was used to characterize the drug effects in hERG functional patch clamp, hERG radio-labelled dofetilide displacement experiments and QT interval in conscious dogs. Data were analysed in parallel to identify potential correlations between pharmacological activity in vitro and in vivo.

KEY RESULTS

An Emax model could not be used due to large variability in the functional patch clamp assay. Dofetilide displacement revealed that binding curves are unrelated to the in vivo potency estimates for QTc prolongation in dogs and humans. Mean in vitro potency estimates ranged from 99.9 nM for cisapride to 1030 μM for moxifloxacin.

CONCLUSIONS AND IMPLICATIONS

The lack of standardized protocols for in vitro assays leads to significant differences in experimental conditions, making the assessment of in vitro-in vivo correlations unreliable. Identification of an accurate safety window during the screening of candidate molecules requires a quantitative framework that disentangles system- from drug-specific properties under physiological conditions, enabling translation of the results to humans. Similar considerations will be relevant for the comprehensive in vitro pro-arrhythmia assay initiative.

Levofloxacin-Induced QTc Prolongation Depends on the Time of Drug Administration

Understanding the factors influencing a drug's potential to prolong the QTc interval on an electrocardiogram is essential for the correct evaluation of its safety profile. To explore the effect of dosing time on drug‐induced QTc prolongation, a randomized, crossover, clinical trial was conducted in which 12 healthy male subjects received levofloxacin at 02:00, 06:00, 10:00, 14:00, 18:00, and 22:00. Using a pharmacokinetic‐pharmacodynamic (PK‐PD) modeling approach to account for variations in PKs, heart rate, and daily variation in baseline QT, we find that the concentration‐QT relationship shows a 24‐hour sinusoidal rhythm. Simulations show that the extent of levofloxacin‐induced QT prolongation depends on dosing time, with the largest effect at 14:00 (1.73 (95% prediction interval: 1.56–1.90) ms per mg/L) and the smallest effect at 06:00 (−0.04 (−0.19 to 0.12) ms per mg/L). These results suggest that a 24‐hour variation in the concentration‐QT relationship could be a potentially confounding factor in the assessment of drug‐induced QTc prolongation.

The role of concentration-effect relationships in the assessment of QTc interval prolongation

Population pharmacokinetic and pharmacokinetic-pharmacodynamic (PKPD) modelling has been widely used in clinical research. Yet, its application in the evaluation of cardiovascular safety remains limited, particularly in the evaluation of pro-arrhythmic effects. Here we discuss the advantages of disadvantages of population PKPD modelling and simulation, a paradigm built around the knowledge of the concentration-effect relationship as the basis for decision making in drug development and its utility as a guide to drug safety. A wide-ranging review of the literature was performed on the experimental protocols currently used to characterize the potential for QT interval prolongation, both pre-clinically and clinically. Focus was given to the role of modelling and simulation for design optimization and subsequent analysis and interpretation of the data, discriminating drug from system specific properties. Cardiovascular safety remains one of the major sources of attrition in drug development with stringent regulatory requirements. However, despite the myriad of tests, data are not integrated systematically to ensure accurate translation of the observed drug effects in clinically relevant conditions. The thorough QT study addresses a critical regulatory question but does not necessarily reflect knowledge of the underlying pharmacology and has limitations in its ability to address fundamental clinical questions. It is also prone to issues of multiplicity. Population approaches offer a paradigm for the evaluation of drug safety built around the knowledge of the concentration-effect relationship. It enables quantitative assessment of the probability of QTc interval prolongation in patients, providing better guidance to regulatory labelling and understanding of benefit/risk in specific populations.

Integration of PKPD relationships into benefit-risk analysis

AIM

Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit-risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit-risk assessment. In addition, we propose the use of pharmacokinetic-pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents.

METHODS

A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit-risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile.

RESULTS

A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit-risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit-risk balance before extensive evidence is generated in clinical practice.

CONCLUSIONS

Benefit-risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials.

Generating Virtual Patients by Multivariate and Discrete Re-Sampling Techniques

Purpose

Clinical Trial Simulations (CTS) are a valuable tool for decision-making during drug development. However, to obtain realistic simulation scenarios, the patients included in the CTS must be representative of the target population. This is particularly important when covariate effects exist that may affect the outcome of a trial. The objective of our investigation was to evaluate and compare CTS results using re-sampling from a population pool and multivariate distributions to simulate patient covariates.

Methods

COPD was selected as paradigm disease for the purposes of our analysis, FEV1 was used as response measure and the effects of a hypothetical intervention were evaluated in different populations in order to assess the predictive performance of the two methods.

Results

Our results show that the multivariate distribution method produces realistic covariate correlations, comparable to the real population. Moreover, it allows simulation of patient characteristics beyond the limits of inclusion and exclusion criteria in historical protocols.

Conclusion

Both methods, discrete resampling and multivariate distribution generate realistic pools of virtual patients. However the use of a multivariate distribution enable more flexible simulation scenarios since it is not necessarily bound to the existing covariate combinations in the available clinical data sets.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-015-1699-x) contains supplementary material, which is available to authorized users.

The Rotterdam Study: 2014 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.