Anna Glinka

Virtual population generator for human cardiomyocytes parameters: in silico drug cardiotoxicity assessment

Background: The anatomical and histological parameters of the human ventricle depend on many factors including age and sex. Myocyte volume and electric capacitance are significant physiological parameters of left ventricle cardiomyocyte mathematical models. They allow the assessment of inter-individual variability during in vitro–in vivo extrapolation of the drug cardiotoxic effect. Objective: The current research was carried out to analyze the relationship between age, human left ventricle cardiomyocyte volume, and electric capacitance in a healthy population. Methods: In order to collect data describing cardiomyocyte volume and membrane area, literature searches were performed. It was assumed that the cardiomyocyte volume (VOL) and area (AREA) distribution have non-negative support and are skewed to the right. A log-linear model with constant variance was used. A simulation study was run to assess the influence of physiological parameters on action potential duration. Results: The coefficient of determination for the proposed model R2 = 0.95, that is, 95% of the variability observed in log cardiomyocyte volume can be explained by the estimated regression equation. To allow simple calculation and model performance validation, a simple Excel file was developed (Supplementary material). Conclusions: To the best of our knowledge, there is no other model available, combining age, cardiomyocyte volume, and area. The main limitations of the proposed models result from the assumptions made at the data analysis stage. The limited amount of information available in the literature and the lack of differentiation between sexes results in one common equation. The developed model is a part of the computational system for drug cardiotoxicity assessment.

The effects of six antipsychotic agents on QTc-An attempt to mimic clinical trial through simulation including variability in the population

BACKGROUND Many drugs (belonging to different chemical groups) have the potential for QT interval prolongation associated with ionic channel blockade in the cardiomyocyte membrane. Due to the fact that this phenomenon is linked to a higher risk of TdP, the ability to predict its scale is one of the most important outcomes of cardiotoxicity assessment of new agents. METHODS With use of the Cardiac Safety Simulator (CSS), the effect of six antipsychotic drugs was predicted in silico. Separate simulations were carried out for each studied population taking the drug. The aim of this study was to predict both the mean values of delta QTc and the results range. To be able to observe individual variability after drug administration, each patient was randomly assigned to the individual drug concentration. Also, appropriate diversity in heart rate, plasma electrolytes concentrations, morphometric parameters of ventricular myocytes, and one common hERG polymorphism frequency in population were added. RESULTS Analyzing the results of simulation with Students t-test, in five of six cases, there were no statistically significant differences between observed and predicted mean values. The diversity of results in all populations studied, however, was not fully reconstructed. DISCUSSION The model was able to accurately reproduce the average effect of the drug on the length when the phenomenon is associated purely with blocking of ionic channels. Nevertheless, the problem of variability in the population and its effect on the QT interval requires further study.

In vitro–in vivo extrapolation of drug-induced proarrhythmia predictions at the population level

Drug cardiotoxicity is a serious issue for patients, regulators, pharmaceutical companies and health service payers because they are all affected by its consequences. Despite the wide range of data they generate, existing approaches for cardiac safety testing might not be adequate and sufficiently cost-effective, probably as a result of the complexity of the problem. For this reason, translational tools (based on biophysically detailed, mathematical models) allowing for in vitro-in vivo extrapolation are gaining increasing interest. This current review describes approaches that can be used for cardiac safety assessment at the population level, by accounting for various sources of variability including kinetics of the compound of interest.

QTc modification after risperidone administration--insight into the mechanism of action with use of the modeling and simulation at the population level approach.

Abstract Context: Ensuring the safety of therapy is both expensive and time-consuming process, which may be supported by modeling and simulation. Objective: The objective of this study was to gain insight into the effect of risperidone administration on QT interval by in silico evaluation of the effect in the individuals with different metabolic status of CYP2D6. Materials and methods: Evaluation was performed through the combination of empirical and mechanistic modeling with the use of the Cardiac Safety Simulator platform allowing for simulation of electrophysiological consequences of drug administration at the population level. The performance of the proposed approach was evaluated by in silico mimicking of the clinical trial conducted by Novalbos. Results: The simulation results depict differences in ΔQT correlated with change in metabolic activity, but not as significant as observed clinically. For poor metabolizers (PMs), ΔQTc was 8.0 and 5.1 ms, for Fridericia’s and Bezett’s correction, respectively, in comparison to 13.9 in Novalbos’s study. For intermediate metabolizers (IMs), there was 9.3 and 7.3 ms versus 4 ms observed clinically, for ultrarapid metabolizers (UMs) −4.0 and 1 ms versus 0.60 ms, for EMs −5.9 and 7.7 ms versus 6.1 ms. Discussion and conclusion: Simulated results underestimate changes observed in the PMs and overestimate the results for the IMs and UMs groups. EM individuals were properly predicted. The results of various QTc studies vary considerably and it is not clear which factors have a decisive influence. Nevertheless, presented differences are still more consistent with clinical results than results obtained clinically by other researchers.

Slow delayed rectifying potassium current (IKs ) - analysis of the in vitro inhibition data and predictive model development.

The excitable cell membranes contain ion channels that allow the ions passage through the specific pores via a passive process. Assessment of the inhibition of the IKr (hERG) current is considered to be the main target during the drug development process, although there are other ionic currents for which drug‐triggered modification can either potentiate or mask hERG channel blockade. Information describing the results of in vitro studies investigating the chemical–IKs current interactions has been developed in the current study. Based on the publicly available data sources, 145 records were collected. The final list of publications consists of 64 positions and refers to 106 different molecules connected with IKs current inhibition, with at least one IC50 value measured. Ultimately, 98 of the IC50 values expressed as absolute values were gathered. For 36 records the IC50 was expressed as a relative value. For the 11 remaining records, the inhibition was not clearly expressed. Based on the collected data the predictive models for the IC50 estimation were developed with the use of various algorithms. The extended Quantitative Structure‐Activity Relationships (QSAR) methodology was applied and the in vitro research settings were included as independent variables, apart from the physico‐chemical descriptors calculated with the use of the Marvin Calculator Plugins. The root mean squared error and normalized root mean squared error values for the best model (an expert system based on two independent artificial neural networks) were 0.86 and 14.04%, respectively. The model was further built into the ToxComp system, the ToxIVIVE tool specialized for cardiotoxicity assessment of drugs. Copyright

Tox-Database.net: a curated resource for data describing chemical triggered in vitro cardiac ion channels inhibition

BackgroundDrugs safety issues are now recognized as being factors generating the most reasons for drug withdrawals at various levels of development and at the post-approval stage. Among them cardiotoxicity remains the main reason, despite the substantial effort put into in vitro and in vivo testing, with the main focus put on hERG channel inhibition as the hypothesized surrogate of drug proarrhythmic potency. The large interest in the IKr current has resulted in the development of predictive tools and informative databases describing a drugs susceptibility to interactions with the hERG channel, although there are no similar, publicly available sets of data describing other ionic currents driven by the human cardiomyocyte ionic channels, which are recognized as an overlooked drug safety target.DiscussionThe aim of this database development and publication was to provide a scientifically useful, easily usable and clearly verifiable set of information describing not only IKr (hERG), but also other human cardiomyocyte specific ionic channels inhibition data (IKs, INa, ICa).SummaryThe broad range of data (chemical space and in vitro settings) and the easy to use user interface makes tox-database.net a useful tool for interested scientists.Database URLhttp://tox-database.net.

The open-access dataset for insilico cardiotoxicity prediction system.

Drug cardiotoxicity is one of the main reasons of fatal drug related problem events and the subsequent withdrawals. Therefore, its early assessment is a crucial element of the drug development process. For the drug driven hERG inhibition assessment, which is assumed to be the main reason for toxicity, in vitro techniques are used. Gold standards are based on the Patch Clamp method with the use of various cell models but due to its low throughput, insilico models have become more appreciated. To develop a reliable empirical QSAR model, wide dataset containing a variety of cases has to be available. In this article, a freely available for download, set of data is described. It is based on literature peer-reviewed reports and contains hERG inhibition information expressed as IC50 value for 263 molecules described in 642 records. All studies were done with the use of three cell models (XO, CHO, HEK) and other elements describe the electrophysiological settings of the in vitro study. The above mentioned set was used for the successful development of the predictive models.

An analysis of cardiomyocytes’ electrophysiology in the presence of the hERG gene mutations

Abstract Mutations in the human ether-à-go-go-related gene are linked with cardiomyocyte repolarization impairment, which, in combination with other factors, can lead to life-threatening arrhythmias. The aim of the study was to demonstrate the effect of selected mutations associated with protein trafficking problems on the action potential of the ventricular cell. To perform the simulations, the O’Hara-Rudy dynamic model was used. The modification of membrane permeability to rapid delayed rectifier current was based on data obtained from in vitro studies with the human embryonic kidney (HEK293) cell line transfected with human genes: wild type and one of the seven mutations (F805C, G601S, D456Y, I31S, R823W, F640V, and A561V). Simulations were carried out for each mutation on epicardial, endocardial, and M-cells with RR interval values of 500, 750, 1000, and 1500 ms. A positive correlation between the APD90 length and the percentage of current reduction and between APD90 and RR interval lengths was observed.

Wild type and K897T polymorphisms of the hERG gene: modeling the APD in Caucasians.

The presented study aims to assess the possibility of simulating changes in cardiac cell electrophysiology due to K897T polymorphism in the Caucasian population. In the first part of the experiment, the parameters of the equations describing channel gating were fitted to the experimental data. Then, the action potentials of midmyocardial cells of 100 individuals were simulated in the in vitro - in vivo extrapolation system - ToxComp. Mean APD90 for the entire simulated population is 352.05 ms (SD = 21.69 ms). Mean APD90 for the 80 individuals with the WT version of the hERG gene and for the 20 K897T homo- and heterozygotes is respectively 349.08 ms (SD = 21.09 ms) and 363.95ms (SD = 20.41 ms). The ToxComp system can be useful in predicting the impact of genetic variability on drug triggered cardiac cell electrophysiology interference.