Towards Bridging Translational Gap in Cardiotoxicity Prediction: an Application of Progressive Cardiac Risk Assessment Strategy in TdP Risk Assessment of Moxifloxacin

Prediction of drug pro-arrhythmic cardiotoxicity using a semi-physiologically based pharmacokinetic model linked to cardiac ionic currents inhibition

Drug-induced torsades de pointes (TdP) risks are responsible for the withdrawal of many drugs from the market. Nowadays, assessments of drug-induced TdP risks are mainly based on maximum effective free therapeutic plasma concentration (EFTPCmax) and cardiac ionic current inhibitions using the human ventricular myocytes model (Tor-ORd model). Myocytes are targets of drug-induced TdP. The TdP risks may be directly linked to myocyte drug concentrations. We aimed to develop a semi-physiologically based pharmacokinetic (Semi-PBPK) model linked to cardiac ionic current inhibition (pharmacodynamics, PD) (Semi-PBPK-PD) to simultaneously predict myocyte drug concentrations and their TdP risks in humans. Alterations in action potential duration (ΔAPD90) were simulated using the Tor-ORd model and ionic current inhibition parameters based on myocyte or plasma drug concentrations. The predicted ΔAPD90 values were translated into in vivo alterations in QT interval(ΔQTc) induced by moxifloxacin, dofetilide, or sotalol. Myocyte drug concentrations of moxifloxacin, dofetilide, and sotalol gave better predictions of ΔQTc than plasma. Following validating the developed semi-PBPK-PD model, TdP risks of 37 drugs were assessed using ΔAPD90 and early afterdepolarization occurrence, which were estimated based on 10 × EFTPCmax and 10 × EFTMCmax (maximum effective free therapeutic myocyte concentration). 10 × EFTMCmax gave more sensitive and accurate predictions of pro-arrhythmic cardiotoxicity and the predicted TdP risks were also closer to clinic practice than 10 × EFTPCmax. In conclusion, pharmacokinetics and TdP risks of 37 drugs were successfully predicted using the semi-PBPK-PD model. Myocyte drug concentrations gave better predictions of ΔQTc and TdP risks than plasma.

Micro-electrode channel guide (µECG) technology: an online method for continuous electrical recording in a human beating heart-on-chip

Cardiac toxicity still represents a common adverse outcome causing drug attrition and post-marketing withdrawal. The development of relevant in vitro models resembling the human heart recently opened the path towards a more accurate detection of drug-induced human cardiac toxicity early in the drug development process. Organs-on-chip (OoC) have been proposed as promising tools to recapitulate in vitro the key aspects of the in vivo cardiac physiology and to provide a means to directly analyze functional readouts. In this scenario, a new device capable of continuous monitoring of electrophysiological signals from functional in vitro human hearts-on-chip is here presented. The development of cardiac microtissues was achieved through a recently published method to control the mechanical environment, while the introduction of a technology consisting in micro-electrode coaxial guides (µECG) allowed to conduct direct and non-destructive electrophysiology studies. The generated human cardiac microtissues exhibited synchronous spontaneous beating, as demonstrated by multi-point and continuous acquisition of cardiac field potential, and expression of relevant genes encoding for cardiac ion-channels. A proof-of-concept pharmacological validation on 3 drugs proved the proposed model to potentially be a powerful tool to evaluate functional cardiac toxicity.

Multiparametric Mechanistic Profiling of Inotropic Drugs in Adult Human Primary Cardiomyocytes

Effects of non-cardiac drugs on cardiac contractility can lead to serious adverse events. Furthermore, programs aimed at treating heart failure have had limited success and this therapeutic area remains a major unmet medical need. The challenges in assessing drug effect on cardiac contractility point to the fundamental translational value of the current preclinical models. Therefore, we sought to develop an adult human primary cardiomyocyte contractility model that has the potential to provide a predictive preclinical approach for simultaneously predicting drug-induced inotropic effect (sarcomere shortening) and generating multi-parameter data to profile different mechanisms of action based on cluster analysis of a set of 12 contractility parameters. We report that 17 positive and 9 negative inotropes covering diverse mechanisms of action exerted concentration-dependent increases and decreases in sarcomere shortening, respectively. Interestingly, the multiparametric readout allowed for the differentiation of inotropes operating via distinct mechanisms. Hierarchical clustering of contractility transient parameters, coupled with principal component analysis, enabled the classification of subsets of both positive as well as negative inotropes, in a mechanism-related mode. Thus, human cardiomyocyte contractility model could accurately facilitate informed mechanistic-based decision making, risk management and discovery of molecules with the most desirable pharmacological profile for the correction of heart failure.

CardiacPBPK: A tool for the prediction and visualization of time-concentration profiles of drugs in heart tissue

BACKGROUND AND OBJECTIVE

Prediction of drug concentration in heart tissue is important in terms of drug safety and efficacy. This work presents the Open-Source CardiacPBPK platform for the prediction of the time-concentration profile of drugs, which could potentially reduce the risk of drug development failure due to cardiotoxicity. The objective of the CardiacPBPK development is to accelerate and simplify the in-silico toxicological assessment of new drugs, and to provide supportive material for the research community to use.

METHODS

The CardiacPBPK software provides a modular implementation of the PBPK model of heart tissue. It can be easily accessed via the Internet or installed locally. The graphical user interface and tabular design are easy to configure and use.

RESULTS

CardiacPBPK is a tool designed to predict and visualize the time-concentration profiles of a parent compound, and one metabolite, in venous plasma and heart tissue after oral or intravenous drug administration. CardiacPBPK is built on the R-environment framework and supports shiny application features such as interactive visualization of the results, and web applications interface by default. A shiny application refers to a computer program created with the use of shiny package in R. The application is freely available at https://github.com/jszlek/CardiacPBPK and https://sourceforge.net/projects/cardiacpbpk/. This open-source application runs on all platforms supporting R-environment (Linux, Windows, Mac OS X, Solaris).

CONCLUSIONS

We demonstrate the application of CardiacPBPK by simulating the study of amitriptyline intoxication in the case of CYP2D6 genetic polymorphism.

An overview of new antitubercular drugs, drug candidates, and their targets

The causative agent of tuberculosis (TB), Mycobacterium tuberculosis and more recently totally drug-resistant strains of M. tuberculosis, display unique mechanisms to survive in the host. A four-drug treatment regimen was introduced 40 years ago but the emergence of multidrug-resistance and more recently TDR necessitates the identification of new targets and drugs for the cure of M. tuberculosis infection. The current efforts in the drug development process are insufficient to completely eradicate the TB epidemic. For almost five decades the TB drug development process remained stagnant. The last 10 years have made sudden progress giving some new and highly promising drugs including bedaquiline, delamanid, and pretomanid. Many of the candidates are repurposed compounds, which were developed to treat other infections but later, exhibited anti-TB properties also. Each class of drug has a specific target and a definite mode of action. These targets are either involved in cell wall biosynthesis, protein synthesis, DNA/RNA synthesis, or metabolism. This review discusses recent progress in the discovery of newly developed and Food and Drug Administration approved drugs as well as repurposed drugs, their targets, mode of action, drug-target interactions, and their structure-activity relationship.

Better prediction of the local concentration-effect relationship: the role of physiologically based pharmacokinetics and quantitative systems pharmacology and toxicology in the evolution of model-informed drug discovery and development

Model-informed drug discovery and development (MID3) is an umbrella term under which sit several computational approaches: quantitative systems pharmacology (QSP), quantitative systems toxicology (QST) and physiologically based pharmacokinetics (PBPK). QSP models are built using mechanistic knowledge of the pharmacological pathway focusing on the putative mechanism of drug efficacy; whereas QST models focus on safety and toxicity issues and the molecular pathways and networks that drive these adverse effects. These can be mediated through exaggerated on-target or off-target pharmacology, immunogenicity or the physiochemical nature of the compound. PBPK models provide a mechanistic description of individual organs and tissues to allow the prediction of the intra- and extra-cellular concentration of the parent drug and metabolites under different conditions. Information on biophase concentration enables the prediction of a drug effect in different organs and assessment of the potential for drug-drug interactions. Together, these modelling approaches can inform the exposure-response relationship and hence support hypothesis generation and testing, compound selection, hazard identification and risk assessment through to clinical proof of concept (POC) and beyond to the market.

[Pharmacokinetic and pharmacodynamic modelling in paediatric drug development with a focus on physiology-based pharmacokinetic simulations]

Pharmacokinetic and pharmacodynamic models are mandatory for dosing and the safe use of drugs in the paediatric population. Different modelling methods allow for the development of dosing regimens for children requiring only a small number of blood samples or none at all. The medicines regulatory authorities recommend using these methods for paediatric drug development programs. Taking sildenafil as an example, the least invasive method of physiology-based pharmacokinetic simulation for the development of dosing regimens in the paediatric population is presented.

Virtual Thorough QT (TQT) Trial-Extrapolation of In Vitro Cardiac Safety Data to In Vivo Situation Using Multi-Scale Physiologically Based Ventricular Cell-wall Model Exemplified with Tolterodine and Fesoterodine

QT interval prolongation typically assessed with dedicated clinical trials called thorough QT/QTc (TQT) studies is used as surrogate to identify the proarrhythmic risk of drugs albeit with criticism in terms of cost-effectiveness in establishing the actual risk of torsade de pointes (TdP). Quantitative systems toxicology and safety (QSTS) models have potential to quantitatively translate the in vitro cardiac safety data to clinical level including simulation of TQT trials. Virtual TQT simulations have been exemplified with use of two related drugs tolterodine and fesoterodine. The impact of bio-relevant concentration in plasma versus estimated heart tissue exposure on predictions was also assessed. Tolterodine and its therapeutically equipotent metabolite formed via CYP2D6 pathway, 5-HMT, inhibit multiple cardiac ion currents (I_Kr, I_Na, I_CaL). The QSTS model was able to accurately simulate the QT prolongation at therapeutic and supra-therapeutic dose levels of tolterodine well within 95% confidence interval limits of observed data. The model was able to predict the QT prolongation difference between CYP2D6 extensive and poor metaboliser subject groups at both dose levels thus confirming the ability of the model to account for electrophysiologically active metabolite. The QSTS model was able to simulate the negligible QT prolongation observed with fesoterodine establishing that the 5-HMT does not prolong QT interval even though it is a blocker of hERG channel. With examples of TOL and FESO, we demonstrated the utility of the QSTS approaches to simulate virtual TQT trials, which in turn could complement and reduce the clinical studies or help optimise clinical trial designs.