Cover Page. The handle holds various files of this Leiden University dissertation

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1 Cover Page The handle holds various files of this Leiden University dissertation Author: Dubois, Vincent F.S. Title: Reverse engineering of drug induced QT(c) interval prolongation : towards a systems pharmacology approach Issue Date:

2 Chapter 2: Reverse engineering of drug-induced QT interval prolongation. Scope and intent of investigations Reverse engineering of drug-induced QT(c) interval prolongation. Scope and intent of investigations. 49

3 The evidence of arrhythmogenic properties of new chemical entities (NCEs) remains an important cause of attrition in drug discovery and development. However, the current paradigm for the evaluation of non-clinical cardiovascular safety of candidate molecules still reflects the understanding of the field more than a decade ago [1,2]. Whilst efforts are in place to ensure that the pro-arrhythmic properties of a NCE are investigated throughout drug development, from the early in vitro screening phase all the way to clinical trials, each and every single experiment remains an isolated, independent unit. Experimental evidence is not generated with the objective of characterising concentration-effect relationships or aimed at integrating and translating the results from preceding stages as the basis for prediction or extrapolation of findings. This situation contrasts with the advancements in the evaluation of efficacy where model-based approaches have been applied as a tool to assess pharmacokineticpharmacodynamic (PKPD) relationships [3 5]. Clearly, a shift in the current paradigm for the evaluation of pro-arrhythmic risk is required, which ensures more efficient screening and selection of compounds. We envisage the need to re-engineer the approach currently used to assess drug-induced QT prolongation, taking the evidence of dromotropic drug effects in humans as starting point for the implementation and analysis of non-clinical data. The objective of the investigations described in this thesis was therefore to develop and evaluate the feasibility of a mechanism-based PKPD modelling approach for the prediction, in a strictly quantitative manner, of drug-induced changes in the QT interval from preclinical in vitro and in vivo test systems to healthy subjects and ultimately to the real life patient population. Emphasis is given to the use of concentration-effect relationships as the basis for the translation of drug effects at therapeutic levels in humans [6 8]. A general PKPD model structure is proposed in which a distinction can be made between parameters describing drug-specific properties versus the system-specific properties. Recently, the advantages of such an approach have been shown for drugs with known QT prolonging effect [9 11]. The model yields a summary of the risk associated with increasing exposures in a way that compounds can be easily compared, thereby facilitating decision making. In addition, the use of Bayesian statistical concepts readily allows for the incorporation of prior knowledge, which can exist for the system-related parameters. Briefly, the Bayesian adaptation of this model comprises three components, which are estimated simultaneously 50

4 during the fitting procedures as presented in Equation 1: an individual correction factor for RRinterval, an oscillatory function describing the circadian variation of the baseline QTc values, and a linear function to capture the concentration-effect relationship. α 2π QT = QTC 0 RR + A cos ( t φ) + slope C 24 Equation 1 where QTc0 [ms] is the individually corrected baseline QTc, RR [sec] is the interval between successive R waves, α is the individual heart rate correction factor, A [ms] is the amplitude of circadian rhythm, t is the clock time, φ is the phase, slope [ms/concentration unit] is the linear concentration-effect relationship, and C is the concentration of drug at the time of QT measurements. This type of parameterisation allows one to distinguish between system- and drug-specific properties. Consequently, these system parameters can be used to compare drug properties across species without the need for further correction factors. Five central questions form the basis for the work to be presented in this thesis: 1. Are there intrinsic differences in the sensitivity to the dromotropic (QT-prolonging) effects of compounds known to block the human ether-a-go-go related gene (herg) ion channel in preclinical species and in humans? 2. If intrinsic differences exist between species can a model-based approach disentangle drugspecific properties from (system-specific) physiological or biological characteristics? 3. Assuming that intrinsic differences between species can be described by systems-specific parameters, can correlations be identified that enable scaling of the effects from animals to humans? 4. Can the magnitude of QT prolonging effects at therapeutic concentrations in humans be predicted in a strictly quantitative manner from findings in preclinical species? 5. Are in vitro-in vivo correlations specific and sensitive enough to allow prediction of the QT prolonging effects at therapeutic concentrations in humans? The research is presented in a way that both conceptual and experimental issues are addressed concurrently. Three important components form the framework proposed throughout this thesis, namely, a) data integration, b) incorporation of pharmacokinetic modelling as the first 51

5 step towards the characterisation of PKPD relationships and c) the parameterisation of drugspecific and system-specific parameters describing QT interval prolongation. Ultimately, our endeavour is to demonstrate the advantages of the approach for prospective drug screening purposes, i.e., as a tool in pharmaceutical R&D. Even though increasing emphasis is given to evaluation of drug effects on ion currents, our approach uses QTc interval as a biomarker of the pharmacological effects on cardiac conductivity. We make use of the wealth of data currently available for different compounds to us through a collaborative data-sharing initiative [ These compounds have been tested pre-clinically and in humans, but the data have not been previously integrated or aggregated with the objective of predicting QT prolongation in humans. It can be anticipated that the principles described throughout this thesis are also applicable to other biomarkers. As such our work can be considered as an important addition to the comprehensive in vitro proarrhythmic assay (CiPA) initiative. PKPD modelling does not only provide the basis for translation and prediction across species, it also represents an important tool for evaluating the interactions between the signalling pathways through effects at multiple ion channels and their implication for drug effects in vivo. Section I: General introduction In Chapter 1, we describe the most commonly used experimental protocols for the characterisation of drug effects during the screening phase. These protocols can be categorised into three groups: a) ion or herg channel specific assays in which inhibition of binding or ion fluxes are assessed in vitro; b) functional measures of drug effect on action potential or tissue conductivity in vitro and c) QTc prolongation in non-clinical species in vivo. From a methodological point of view, this chapter highlights the limitations of current used criteria for drug development as well as the fragmentation in the way data are collected and analysed. Our review shows a mismatch between non-clinical and clinical experimental protocols, which creates uncertainties about the potential QT-prolonging effect of candidate molecules in humans. Many of the non-clinical protocols appear to neglect the role of concentration-effect relationships and how such relationships may translate across species. Here quantitative pharmacology concepts are proposed as the basis for an integrated evaluation 52

6 of the data, in which PKPD modelling and simulation are used to disentangle drug-specific from species specific properties. Ultimately, an approach is envisaged in which PKPD relationships are used as the basis for the scaling between preclinical and clinical data and the risk of QT prolongation in humans is derived as early as possible during drug development. The scope and intent of the investigations described in this chapter (Chapter 2) provides an overview of the framework for a model-based approach in which a common parameterisation is used throughout the different phases of drug development. The ultimate goal of the proposed approach is to facilitate the integration of the data and subsequently the translation and interpretation of findings, taking into account differences between preclinical species and humans. The choice of model parameterisation is central to the work presented in later chapters. In addition, focus is given to the shortcomings in the design of preclinical experiments, which contribute to inaccuracies in the assessment of the risk of QT interval prolongation in humans. Section II: Characterising interspecies differences in PKPD relationships Population pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PKPD) modelling is a powerful technique to, not only characterise concentration-effect relationships, but also to identify the factors explaining variability [12]. A limitation of most population models, however, is that they are descriptive and data-driven, rather than mechanistic. As a result they are not suitable for extrapolation and prediction beyond the compound for which the model has been developed and the experimental conditions that have been studied [13,14]. By contrast, mechanism-based PKPD models can provide the basis to connect information from the pertinent investigations in the different phases of drug development i.e. the translation from preclinical experiments to clinical studies in humans. From a methodological perspective, in Chapter 3 we address the first of the five questions, by exploring potential interspecies differences in the sensitivity to the dromotropic (QT-prolonging) effects of compounds known to block the herg ion channel in humans. Choosing a suitable animal species is a critical step for the characterisation of the concentration-effect relationship and the subsequent prediction of the drug effects in humans. Given the relevance of non-human primates for the evaluation of the safety profile of biologicals, the aim of the current 53

7 investigation was to assess the QTc prolonging effects of moxifloxacin in cynomolgus monkeys, dogs and humans. This comparison is also important because it has been suggested that monkeys might be the preferred species in preclinical investigations due to similarities to humans in terms of the magnitude of drug-induced QT effects [15,16]. In chapter 3 it is shown that the concentration-effect relation of moxifloxacin in humans is distinctly different from the concentration-effect relation in cynomolgus monkeys, indicating that a translation function will be needed when predicting QT interval prolongation in humans on the basis of information from non-clinical species. Data from a new candidate molecule is presented to illustrate how this concept can be implemented prospectively during the screening phase. This work also offers further insight on the relevance of interspecies differences in pharmacokinetics [17 19]. Whereas awareness exists about the potential impact of differences in protein binding, less attention has been given to the requirements for the assessment of drug disposition properties. In the chapter 4 and chapter 5 we address the second of the five questions, the question on the use of a model-based approach to disentangle drug-specific properties from (system-specific) physiological or biological characteristics. In chapter 4 the utility of the model parameterisation based on a distinction between drug- and system-specific properties is explored for paradigm drugs with well-established dromotropic effects: d,l-sotalol, cisapride, and moxifloxacin. The primary objective of the investigation is therefore to establish the predictive value of PKPD relationships in dogs as the basis for the prediction of drug-induced QT interval prolongation in humans. This is important since the use of the same structural model with similar parameterisation in animals and humans will facilitate the translation of data from preclinical to clinical conditions. From a drug development perspective, this feature is essential for the use of the approach for the prospective screening of compounds in R&D. The concept is illustrated by analysing data generated preclinically in dogs and clinically in healthy subjects with the same hierarchical model and using similar effect threshold criteria. Although there is no consensus on what may represent a clinically relevant increase in QT interval in preclinical species, the same threshold of 10 ms was used as reference value for comparing drug effects in dogs and humans [20]. The model is successfully applied to the data enabling the distinction between drug- and system-specific properties. Between the three compounds drug-specific differences in the slope of the linear concentration-effect were observed. It is shown that there is a systematic difference in the slope of the linear concentration-effect relation for these compounds in dogs 54

8 and humans. These results indicate that the slope in dogs may be used as the basis for prediction of drug-induced QTc interval prolongation in humans. The same approach is followed in Chapter 5 to assess the effects of investigational compounds NCE01, NCE02 and NCE03, for which experimental data are available in dogs and healthy subjects. The comparison of these three compounds is of interest, because unlike the compounds tested in Chapter 4, these compounds differ not only in potency (the concentration range in which they act) but also in intrinsic efficacy (the maximum effect that may be reached). Specifically, the analysis reveals the flexibility of the modelling approach which can be used to describe very diverse pharmacological profiles, in that while NCE01 has similar properties as moxifloxacin (i.e. has a clear QT-prolonging effect), NCE02 is a compound with borderline effect on QTc and NCE03 appears to cause a shortening of the QTc interval rather than a prolongation. Our investigation also shows that some knowledge about the expected therapeutic concentration range of the drug is required to ensure an accurate interpretation of preclinical findings. Based on this initial assessment, it will be of interest to analyse a larger data-set of multiple compounds with varying dromotropic properties (including compounds with varying affinity, potency and selectivity for different ion channels), to confirm whether there is indeed a systematic difference in the PKPD relationships between dogs and humans. Evidence of a systematic difference would enable one to use a scaling factor to predict drug effects in humans based on experimental data in dogs. Such a correlation is relevant even if baseline QT interval, heart rate and receptor densities may vary across species [21,22]. In addition, it is important to highlight that the understanding of the disposition properties of the compounds turns out to be essential for the accurate assessment of PKPD relationships. In fact, the evaluation of the different compounds in Chapter 4 and 5 shows that the characterisation of pharmacokinetics is a sine qua non condition to disentangle drug-specific properties from (system-specific) physiological or biological characteristics. 55

9 Section III: Scaling and extrapolation of QT interval prolongation in humans In this section we aimed to explore the possibility of establishing a correlation between drugspecific parameters in preclinical species and in humans and subsequently predict the magnitude of drug effects in humans before the QT interval is evaluated in a clinical trial. Initially, in Chapter 6, we address the third of the five questions, i.e., the identification of a single transduction function for the scaling of dromotropic effects of drugs across species. Here we assess whether drug-specific parameters obtained by PKPD modelling of the effects of nine compounds with no or varying QT-prolonging effect in dogs are predictive of the magnitude of the QT interval prolongation in humans, after correction for systems-specific differences in pharmacodynamics (i.e. the slope of the linear concentration-effect relationship). In the context of this thesis, it should be highlighted that 10 ms is used as a common threshold across species, under the assumption that fractional (%) increase from baseline would be less representative, especially in smaller species in which QT interval is significantly different from humans. Another argument supporting this choice is the known differences in heart rate, herg and other ion channel densities across species [22,23]. Evidence of a correlation between species suggests the possibility of using a single unique translation function to scale drug-specific parameters from animals to humans. Conceptually, this could represent a shift in the current paradigm for safety pharmacology, enabling the use of model-based approaches prospectively not as a data analysis tool, but rather as a screening tool. In view of that, in Chapter 7 we attempt to answer the fourth central question of this thesis, namely, to predict the magnitude of QT-prolonging effects at therapeutic concentrations in humans in a strictly quantitative manner from findings in preclinical species. A critical aspect for the success of the approach is data integration. An outline of the requirements and opportunities for effective data integration and prompt implementation of modelling and simulation is depicted in Figure

10 Figure 2.1. Evidence of a correlation between drug-specific parameters in dogs and humans may allow preclinical data to be used as the basis for translating drug effects to humans. The diagram depicts opportunities (indicated with stars) where data can be integrated to support the characterisation of PKPD relationships and subsequently the prediction of the drug effects on QT interval in humans before candidate molecules are progressed to the clinic. (Adapted from Pollard et al. [24]). In a nutshell, in Chapter 7 we illustrate how PKPD modelling of preclinical data can be used in conjunction with clinical trial simulations to predict the probability of QT interval prolongation 10 ms. The investigation is aimed at mimicking the prospective evaluation of a candidate molecule in development, which has been selected to progress into first-time-in-humans. Data from a compound tested in a blinded manner was generated in dogs according to a cardiovascular safety pharmacology protocol, similar to the experiments described in previous chapters. Data is then analysed using PKPD modelling to obtain the parameter of interest in dogs, i.e., slope parameter. The slope estimates are then extrapolated using the translation function obtained in chapter 6 to obtain values of the slope in humans. Using the PKPD model and clinical trial simulation concepts, simulated pharmacokinetic data from a hypothetical phase I dose-escalation study in healthy subjects are used together with the predicted slope in humans as input for the prediction of drug effects in humans. In addition to its translational relevance, this analysis provides further insight into the implications of interspecies differences in drug disposition (i.e. the formation of active metabolites) for the extrapolation and prediction of QT- 57

11 prolonging effects in humans. In brief, it is shown that the proposed approach may enable one to establish the clinical relevance of QT prolongation before testing the drug in healthy subjects or patients. Within the context of reverse engineering, the next step is to evaluate how to best use in vitro data to support the screening of candidate molecules. Therefore, after having characterised the correlation between slope parameters in dogs and humans, an attempt is made in Chapter 8 to integrate herg binding data into the proposed framework as a drug-specific parameter. Similar concepts to those developed for the assessment of PKPD relationships in conscious dogs in vivo can be applied to in vitro experiments, allowing us to address the last of the five questions, whether in vitro-in vivo correlations can be specific and sensitive enough to predict the QTprolonging effects at therapeutic concentrations in humans. In this context, in Chapter 8 we explore how data from herg assays, which currently represent a primary screening filter before QT/QTc interval prolongation is evaluated in vivo, can be integrated and parameterised into PKPD models. The [ 3 H]-dofetilide equilibrium binding assay for the herg K+ channel and whole cell patch clamp experiments with over expressed herg HEK293 cells are used to assess binding and functional herg inhibition for three reference compounds with known clinical effects, namely cisapride, sotalol and moxifloxacin. These experimental protocols were selected because they might provide insight into drug-specific properties, such as affinity. Extrapolations could then be performed based on in vitro-in vivo correlations in a similar manner to what has been demonstrated for the slope of the PKPD relationship in dogs and humans. These parameters could also be incorporated into PKPD models to explore the liability for QT interval prolongation in humans directly from in vitro experiments. Our investigation shows however that no systematic in vitro in vivo correlation can be identified for any of the reference compounds. Section IV: Conclusions and future perspectives. The final section of this thesis summarises the main findings and conclusions from the investigations presented throughout the various chapters. In Chapter 9, we continue to advocate the need for data integration and evidence synthesis based on PKPD relationships. In 58

12 addition to reviewing the requirements for extrapolation and translation of drug effects, we also provide recommendations for the evaluation of probability of QT interval prolongation before transition of compounds to humans. Attention is given to the experimental protocol design aspects, which are required to ensure the accurate characterisation of pharmacokinetic and pharmacodynamic properties. Clearly, a new paradigm for the evaluation of cardiovascular safety must emerge in which novel biomarkers, are identified which reflect the underlying drug effects on ion currents and signalling pathways that determine the cardiac action potentials [25]. An overview is provided of newer techniques that allow one to assess herg currents in a more direct way, but it is likely that a stricter quantitative framework will be required for the translation of in vitro findings. Despite these advancements, it can be anticipated that the lack of good quality pharmacokinetic data will continue to represent an important hurdle for assessing the liability for QT interval prolongation. In addition, efforts are needed to assess the impact of differences in drug metabolism between preclinical species and humans. Lastly, it is concluded that the ability to discriminate between drug- and system-specific parameters will remain critical for the screening and selection of suitable candidate molecules. Prediction of QT interval prolongation and pro-arrhythmic activity in humans will demand further integration of pharmacokinetic and pharmacodynamic data based on experimental protocols that enable the characterisation of the concentration-effect relationship at therapeutically relevant levels. 59

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