CiPA Assay – A Comprehensive In Vitro Proarrhythmia Assay

doctor looking at wavelength on a computer

An international group of regulatory, industry and academic scientists are developing a comprehensive in vitro proarrhythmia assay (CiPA Assay) to replace the current hERG ion channel and QT prolongation approach. CiPA includes a combination of in vitro, in silico and in-vivo assays that assess the proarrhythmic risk of compounds.

In this study, we used a human ventricular model of Purkinje fibres to evaluate the predictivity of three CiPA in vitro assays and a novel biomarker-based approach. Our results show that LEV does not induce any relevant changes in electrophysiological parameters and arrhythmias.

doctors looking at a smart phone screen

Evaluation of hERG channel activity
A considerable challenge in drug development is the proarrhythmic risk posed by long QT syndrome (LQTS). This is due to the inhibition of a voltage-gated potassium channel, IKr, encoded by the Human Ether-a-go-go related gene (hERG), which causes prolonged ventricular repolarization and prolongs the QT interval. This hERG channel block and QT prolongation has been identified as an essential determinant of proarrhythmic risk by the International Conference on Harmonisation (ICH) of Standards for Pharmaceuticals and Medicinal Products for Human Use (S7B) and E14, and is a limiting factor in the approval of new low-risk drugs with otherwise positive safety profiles.

To address this issue, the Comprehensive in vitro proarrhythmia assay (CiPA assay) was developed to evaluate drugs’ effects on a wide variety of torsadogenic channels and mechanisms, including hERG, Nav1.5, CaV1.2, Kir2.1 and KV7.1/mink, with a focus on IC50 parameters. In addition to hERG, CiPA incorporates a ‘late’ sodium current assay, as inhibitors of persistent inward current can also affect repolarisation and mitigate proarrhythmic risk (e.g. ranolazine).

Up to now, only manual patch clamp recordings have been used to reliably measure hERG channel binding kinetics and drug trapping. These assays are unable to capture the complex and dynamic behaviour of hERG inhibition, and thus do not provide a sufficient level of data for high throughput screening. Moreover, as a result of interferences from the parental cells, these assays are associated with higher false-positive and false-negative rates.

Simulation of human ventricular electrophysiology
The development of a computational model of human ventricular electrophysiology is necessary to evaluate drug effects on a variety of cardiac ion channel properties. These include the refractory period, conduction velocity, and wavelength of healthy and ischaemic ventricular tissue, as well as the impact of drug changes on body surface ECGs and QT intervals.

However, the choice of a mathematical model depends on many factors. It must be computationally efficient and compatible with ionic currents, and it should preserve key properties of human ventricular tissue such as AP morphology and restitution, and change of AP shape under the influence of ionic currents.

In addition, it should be able to simulate drug actions that are associated with changes in the tissue’s electrical conduction properties and metabolic imbalances. This should be achieved by combining the electric potential, electrograms (EGMs), and activation maps that represent the solutions of the mathematical model at a given point in time.

To perform a simulation, a heart geometry reconstruction, either by automatic or manual tools, must be performed and a fine partition of the heart volume should be generated. A computational mesh would then be generated by using tetrahedral or hexahedral cells with arbitrary edge length (Figure 2, bottom).

Numerical solution is then approximated on each vertex of the computational mesh using discretization techniques. This process requires a lot of computing power. This is especially true for a nonlinear model, in which the initial conditions and boundary conditions are significant sources of uncertainty.

Validation of in silico conclusions
In silico methods are emerging as a valuable tool to replace some of the classical in vivo tests. However, they cannot be used to predict all toxicity endpoints and must be validated with experimental data (Hartung and Hoffmann, 2009; Merlot, 2010).

In recent years, the use of in silico models has achieved advancements in numerous pharmacological areas including: the clarification of absorption, distribution, metabolism, excretion and toxicity properties, discovery and optimization of novel molecules, and physicochemical characterization. Ideally, in silico results are valid and reliable and can be used as stand-alone evidence for regulatory purposes when they are considered relevant, adequate and documented properly.

The Comprehensive in vitro Proarrhythmia Assay (CiPA assay) initiative developed a model that allows quantitative evaluation of a drug’s proarrhythmic risk using a physiologic and pharmacodynamic approach. Instead of being confined to the traditional IC50 prediction model based on hERG/IKr ion channel blockade assessment, CiPA uses in vitro data of seven major ionic currents to evaluate the relative risk of tachyarrhythmia.

The CiPAORdv1.0 model developed under the CiPA initiative combines a cardiac action potential (AP) modelling approach and a mechanism-based metric that assesses tachyarrhythmic risk of 28 candidate drugs. The model was then tested for its validity using a computationally reconstructed human ventricular cardiomyocyte action potential.