Computational approaches identify a transcriptomic fingerprint of drug-induced structural cardiotoxicity.

Structural cardiotoxicity (SCT) presents a high-impact risk that is poorly tolerated in drug discovery unless significant benefit is anticipated. Therefore, we aimed to improve the mechanistic understanding of SCT. First, we combined machine learning methods with a modified calcium transient assay in human-induced pluripotent stem cell-derived cardiomyocytes to identify nine parameters that could predict SCT. Next, we applied transcriptomic profiling to human cardiac microtissues exposed to structural and non-structural cardiotoxins. Fifty-two genes expressed across the three main cell types in the heart (cardiomyocytes, endothelial cells, and fibroblasts) were prioritised in differential expression and network clustering analyses and could be linked to known mechanisms of SCT. This transcriptomic fingerprint may prove useful for generating strategies to mitigate SCT risk in early drug discovery.

Application of microphysiological systems for nonclinical evaluation of cell therapies

Microphysiological systems (MPS) are gaining broader application in the pharmaceutical industry but have primarily been leveraged in early discovery toxicology and pharmacology studies with small molecules. The adoption of MPS offers a promising avenue to reduce animal use, improve in-vitro-to-in-vivo translation of pharmacokinetics/pharmacodynamics and toxicity correlation, and provide mechanistic understanding of model species suitability. While MPS have demonstrated utility in these areas with small molecules and biologics, MPS models in cell therapy development have not been fully explored, let alone validated. Distinguishing features of MPS, including long-term viability and physiologically relevant expression of functional enzymes, receptors, and pharmacological targets make them attractive tools for nonclinical characterization. However, there is currently limited published evidence of MPS being utilized to study the disposition, metabolism, pharmacology, and toxicity profiles of cell therapies. This review provides an industry perspective on the nonclinical application of MPS on cell therapies, first with a focus on oncology applications followed by examples in regenerative medicine.

Microphysiological systems (MPS) are advanced cell models, applied in the pharmaceutical industry to characterize novel therapies. While their application in studies of small molecule ther­apies has been very successful, the use of these models to study cell therapies has been limited. Cell therapies consist of cells and are living drugs, often with complex biological mechanisms of action, which can be very challenging to study. However, MPS have several features that make them attractive for studying cell therapies, including possibilities for longer-term studies and the ability to mimic physiologically relevant biological functions. MPS can mimic complex biological systems and processes, as such, the adoption of MPS offers a promising avenue to reduce the use of animals in the characterization of novel therapies. This review provides an industry perspective on current chal­lenges and highlights opportunities for using MPS in the development of cell therapies.

Strengthening cardiac therapy pipelines using human pluripotent stem cell-derived cardiomyocytes.

Advances in hiPSC isolation and reprogramming and hPSC-CM differentiation have prompted their therapeutic application and utilization for evaluating potential cardiovascular safety liabilities. In this perspective, we showcase key efforts toward the large-scale production of hiPSC-CMs, implementation of hiPSC-CMs in industry settings, and recent clinical applications of this technology. The key observations are a need for traceable gender and ethnically diverse hiPSC lines, approaches to reduce cost of scale-up, accessible clinical trial datasets, and transparent guidelines surrounding the safety and efficacy of hiPSC-based therapies.

Simultaneously discovering the fate and biochemical effects of pharmaceuticals through untargeted metabolomics.

Untargeted metabolomics is an established approach in toxicology for characterising endogenous metabolic responses to xenobiotic exposure. Detecting the xenobiotic and its biotransformation products as part of the metabolomics analysis provides an opportunity to simultaneously gain deep insights into its fate and metabolism, and to associate the internal relative dose directly with endogenous metabolic responses. This integration of untargeted exposure and response measurements into a single assay has yet to be fully demonstrated. Here we assemble a workflow to discover and analyse pharmaceutical-related measurements from routine untargeted UHPLC-MS metabolomics datasets, derived from in vivo (rat plasma and cardiac tissue, and human plasma) and in vitro (human cardiomyocytes) studies that were principally designed to investigate endogenous metabolic responses to drug exposure. Our findings clearly demonstrate how untargeted metabolomics can discover extensive biotransformation maps, temporally-changing relative systemic exposure, and direct associations of endogenous biochemical responses to the internal dose.

Prediction of inotropic effect based on calcium transients in human iPSC-derived cardiomyocytes and machine learning.

Functional changes to cardiomyocytes are undesirable during drug discovery and identifying the inotropic effects of compounds is hence necessary to decrease the risk of cardiovascular adverse effects in the clinic. Recently, approaches leveraging calcium transients in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been developed to detect contractility changes, induced by a variety of mechanisms early during drug discovery projects. Although these approaches have been able to provide some predictive ability, we hypothesised that using additional waveform parameters could offer improved insights, as well as predictivity. In this study, we derived 25 parameters from each calcium transient waveform and developed a modified Random Forest method to predict the inotropic effects of the compounds. In total annotated data for 48 compounds were available for modelling, out of which 31 were inotropes. The results show that the Random Forest model with a modified purity criterion performed slightly better than an unmodified algorithm in terms of the Area Under the Curve, giving values of 0.84 vs 0.81 in a cross-validation, and outperformed the ToxCast Pipeline model, for which the highest value was 0.76 when using the best-performing parameter, PW10. Our study hence demonstrates that more advanced parameters derived from waveforms, in combination with additional machine learning methods, provide improved predictivity of cardiovascular risk associated with inotropic effects.

Deriving waveform parameters from calcium transients in human iPSC-derived cardiomyocytes to predict cardiac activity with machine learning.

Human induced pluripotent stem cell-derived cardiomyocytes have been established to detect dynamic calcium transients by fast kinetic fluorescence assays that provide insights into specific aspects of clinical cardiac activity. However, the precise derivation and use of waveform parameters to predict cardiac activity merit deeper investigation. In this study, we derived, evaluated, and applied 38 waveform parameters in a novel Python framework, including (among others) peak frequency, peak amplitude, peak widths, and a novel parameter, shoulder-tail ratio. We then trained a random forest model to predict cardiac activity based on the 25 parameters selected by correlation analysis. The area under the curve (AUC) obtained for leave-one-compound-out cross-validation was 0.86, thereby replicating the predictions of conventional methods and outperforming fingerprint-based methods by a large margin. This work demonstrates that machine learning is able to automate the assessment of cardiovascular liability from waveform data, reducing any risk of user-to-user variability and bias.

An Extensive Metabolomics Workflow to Discover Cardiotoxin-Induced Molecular Perturbations in Microtissues.

Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed of ca. 500 cells. While untargeted metabolomics is capable of generating hypotheses on toxicological modes of action and discovering metabolic biomarkers, applying this technology to low-biomass microtissues in suspension is experimentally challenging. Thus, we first evaluated a filtration-based approach for harvesting microtissues and assessed the sensitivity and reproducibility of nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) measurements of intracellular extracts, revealing samples consisting of 28 pooled microtissues, harvested by filtration, are suitable for profiling the intracellular metabolome and lipidome. Subsequently, an extensive workflow combining nESI-DIMS untargeted metabolomics and lipidomics of intracellular extracts with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analysis of spent culture medium, to profile the metabolic footprint and quantify drug exposure concentrations, was implemented. Using the synthetic drug and model cardiotoxin sunitinib, time-resolved metabolic and lipid perturbations in cardiac microtissues were investigated, providing valuable data for generating hypotheses on toxicological modes of action and identifying putative biomarkers such as disruption of purine metabolism and perturbation of polyunsaturated fatty acid levels.

Intra- and intercellular signaling pathways associated with drug-induced cardiac pathophysiology.

Cardiac physiology and homeostasis are maintained by the interaction of multiple cell types, via both intra- and intercellular signaling pathways. Perturbations in these signaling pathways induced by oncology therapies can reduce cardiac function, ultimately leading to heart failure. As cancer survival increases, related cardiovascular complications are becoming increasingly prevalent, thus identifying the perturbations and cell signaling drivers of cardiotoxicity is increasingly important. Here, we discuss the homotypic and heterotypic cellular interactions that form the basis of intra- and intercellular cardiac signaling pathways, and how oncological agents disrupt these pathways, leading to heart failure. We also highlight the emerging systems biology techniques that can be applied, enabling a deeper understanding of the intra- and intercellular signaling pathways across multiple cell types associated with cardiovascular toxicity.

Cardiovascular microphysiological systems (CVMPS) for safety studies - a pharma perspective.

The integrative responses of the cardiovascular (CV) system are essential for maintaining blood flow to provide oxygenation, nutrients, and waste removal for the entire body. Progress has been made in independently developing simple in vitro models of two primary components of the CV system, namely the heart (using induced pluripotent stem-cell derived cardiomyocytes) and the vasculature (using endothelial cells and smooth muscle cells). These two in vitro biomimics are often described as immature and simplistic, and typically lack the structural complexity of native tissues. Despite these limitations, they have proven useful for specific "fit for purpose" applications, including early safety screening. More complex in vitro models offer the tantalizing prospect of greater refinement in risk assessments. To this end, efforts to physically link cardiac and vascular components to mimic a true CV microphysiological system (CVMPS) are ongoing, with the goal of providing a more holistic and integrated CV response model. The challenges of building and implementing CVMPS in future pharmacological safety studies are many, and include a) the need for more complex (and hence mature) cell types and tissues, b) the need for more realistic vasculature (within and across co-modeled tissues), and c) the need to meaningfully couple these two components to allow for integrated CV responses. Initial success will likely come with simple, bioengineered tissue models coupled with fluidics intended to mirror a vascular component. While the development of more complex integrated CVMPS models that are capable of differentiating safe compounds and providing mechanistic evaluations of CV liabilities may be feasible, adoption by pharma will ultimately hinge on model efficiency, experimental reproducibility, and added value above current strategies.

Time for a Fully Integrated Nonclinical-Clinical Risk Assessment to Streamline QT Prolongation Liability Determinations: A Pharma Industry Perspective.

Defining an appropriate and efficient assessment of drug-induced corrected QT interval (QTc) prolongation (a surrogate marker of torsades de pointes arrhythmia) remains a concern of drug developers and regulators worldwide. In use for over 15 years, the nonclinical International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) S7B and clinical ICH E14 guidances describe three core assays (S7B: in vitro hERG current & in vivo QTc studies; E14: thorough QT study) that are used to assess the potential of drugs to cause delayed ventricular repolarization. Incorporating these assays during nonclinical or human testing of novel compounds has led to a low prevalence of QTc-prolonging drugs in clinical trials and no new drugs having been removed from the marketplace due to unexpected QTc prolongation. Despite this success, nonclinical evaluations of delayed repolarization still minimally influence ICH E14-based strategies for assessing clinical QTc prolongation and defining proarrhythmic risk. In particular, the value of ICH S7B-based "double-negative" nonclinical findings (low risk for hERG block and in vivo QTc prolongation at relevant clinical exposures) is underappreciated. These nonclinical data have additional value in assessing the risk of clinical QTc prolongation when clinical evaluations are limited by heart rate changes, low drug exposures, or high-dose safety considerations. The time has come to meaningfully merge nonclinical and clinical data to enable a more comprehensive, but flexible, clinical risk assessment strategy for QTc monitoring discussed in updated ICH E14 Questions and Answers. Implementing a fully integrated nonclinical/clinical risk assessment for compounds with double-negative nonclinical findings in the context of a low prevalence of clinical QTc prolongation would relieve the burden of unnecessary clinical QTc studies and streamline drug development.

In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities.

The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

Current and future approaches to nonclinical cardiovascular safety assessment.

Our goal is to accurately predict all types of cardiovascular events in patients utilising nonclinical cardiovascular safety data. In the past two decades, cardiovascular safety science has primarily focused on events associated with the electrocardiogram. Broadening out to other cardiovascular parameters, we share real-life case studies that highlight our progress towards improved and better-informed project progression based upon use of disease models, mechanism-based translation and structure-function relationships. To fulfil this goal, further advances in patient-relevant humanised models will be required to enable cardiovascular safety science to keep pace with the ever-changing landscape of novel therapeutic paradigms.

Drug-induced myocardial dysfunction - recommendations for assessment in clinical and pre-clinical studies.

Introduction: Drug-induced myocardial dysfunction is an important safety concern during drug development. Oncology compounds can cause myocardial dysfunction, leading to decreased left ventricular ejection fraction and heart failure via several mechanisms. Cardiovascular imaging has a major role in the early detection and monitoring of cardiotoxicity. Echocardiography is the method of choice because of its widespread availability, low cost, and absence of radiation exposure. Cardiac magnetic resonance imaging can provide better reliability, reproducibility, and accuracy in the detection of drug-induced myocardial dysfunction. In addition, it enables assessment of myocardial edema, fibrosis, and necrosis. Cardiac serologic biomarkers such as troponins and B-type natriuretic peptides are used in combination with imaging during drug development. This article provides a general overview of each imaging modality and practical guidance for early detection and monitoring of cardiotoxicity.Areas covered: Cardiovascular imaging modalities and cardiac biomarkers for monitoring of cardiac function and early detection of drug-induced myocardial dysfunction in drug development.Expert opinion: Some new drugs especially in the oncology field, can cause myocardial dysfunction. Depending on the strength of pre-clinical or clinical data, CV imaging modalities and cardiac biomarkers play an important role in the early detection and mitigation plans for such drugs during their development.

A pharmacological characterization of electrocardiogram PR and QRS intervals in conscious telemetered rats.

INTRODUCTION: The conscious telemetered rat is widely used as an early in vivo screening model for assessing the cardiovascular safety of novel pharmacological agents. The current study aimed to identify its utility in assessing electrocardiogram (ECG) PR and QRS interval changes. METHOD: Male Han-Wistar rats (~250 g) were implanted with radio-telemetry devices for the recording of ECG and haemodynamic parameters. Animals (n = 4-8) were treated with single doses of calcium (nifedipine, diltiazem or verapamil; CCBs) or sodium channel blockers (quinidine or flecainide; SCBs) or their corresponding vehicles in an ascending dose design. Data was recorded continuously up to 24 h post-dose. Pharmacokinetic analysis of blood samples was performed to allow comparison of effects to published data in other species. RESULTS: Of the CCBs, only diltiazem (300 mg/kg) prolonged the PR interval (49 ± 2 versus vehicle: 43 ± 1 ms), although this was not statistically significant (p = .11). QA interval decreased with nifedipine (30 ± 1 versus 24 ± 0 ms) and diltiazem (34 ± 1 versus 27 ± 1 ms) but increased with verapamil (30 ± 0 versus 37 ± 1 ms) demonstrating pharmacological activity of each agent. Both SCBs, caused statistically significant (p < .05) increases in both intervals - quinidine (100 mg/kg; PR: 50 ± 2 versus 43 ± 1 ms; QRS: 22 ± 2 versus 18 ± 1 ms) and flecainide (9 mg/kg; PR: 56 ± 1 versus 46 ± 1 ms; QRS: 27 ± 1 versus 21 ± 1 ms). Drug plasma exposure was confirmed in all animals. DISCUSSION: At similar plasma concentrations to other species, the conscious telemetered rat demonstrates limited utility in assessing PR interval prolongation by CCBs, despite significant contractility effects being observed. However, results with SCBs demonstrate a potential application for evaluating drug-induced QRS prolongation.

On the potential of in vitro organ-chip models to define temporal pharmacokinetic-pharmacodynamic relationships.

Functional human-on-a-chip systems hold great promise to enable quantitative translation to in vivo outcomes. Here, we explored this concept using a pumpless heart only and heart:liver system to evaluate the temporal pharmacokinetic/pharmacodynamic (PKPD) relationship for terfenadine. There was a time dependent drug-induced increase in field potential duration in the cardiac compartment in response to terfenadine and that response was modulated using a metabolically competent liver module that converted terfenadine to fexofenadine. Using this data, a mathematical model was developed to predict the effect of terfenadine in preclinical species. Developing confidence that microphysiological models could have a transformative effect on drug discovery, we also tested a previously discovered proprietary AstraZeneca small molecule and correctly determined the cardiotoxic response to its metabolite in the heart:liver system. Overall our findings serve as a guiding principle to future investigations of temporal concentration response relationships in these innovative in vitro models, especially, if validated across multiple time frames, with additional pharmacological mechanisms and molecules representing a broad chemical diversity.

Exosomal delivery of doxorubicin enables rapid cell entry and enhanced in vitro potency.

Doxorubicin is a chemotherapeutic agent that is commonly used to treat a broad range of cancers. However, significant cardiotoxicity, associated with prolonged exposure to doxorubicin, limits its continued therapeutic use. One strategy to prevent the uptake of doxorubicin into cardiac cells is the encapsulation of the drug to prevent non-specific uptake and also to improve the drugs' pharmacokinetic properties. Although encapsulated forms of doxorubicin limit the cardiotoxicity observed, they are not without their own liabilities as an increased amount of drug is deposited in the skin where liposomal doxorubicin can cause palmar-plantar erythrodysesthesia. Exosomes are small endogenous extracellular vesicles, that transfer bioactive material from one cell to another, and are considered attractive drug delivery vehicles due to their natural origin. In this study, we generated doxorubicin-loaded exosomes and demonstrate their rapid cellular uptake and re-distribution of doxorubicin from endosomes to the cytoplasm and nucleus resulting in enhanced potency in a number of cultured and primary cell lines when compared to free doxorubicin and liposomal formulations of doxorubicin. In contrast to other delivery methods for doxorubicin, exosomes do not accumulate in the heart, thereby providing potential for limiting the cardiac side effects and improved therapeutic index.

Information-Derived Mechanistic Hypotheses for Structural Cardiotoxicity.

Adverse events resulting from drug therapy can be a cause of drug withdrawal, reduced and or restricted clinical use, as well as a major economic burden for society. To increase the safety of new drugs, there is a need to better understand the mechanisms causing the adverse events. One way to derive new mechanistic hypotheses is by linking data on drug adverse events with the drugs' biological targets. In this study, we have used data mining techniques and mutual information statistical approaches to find associations between reported adverse events collected from the FDA Adverse Event Reporting System and assay outcomes from ToxCast, with the aim to generate mechanistic hypotheses related to structural cardiotoxicity (morphological damage to cardiomyocytes and/or loss of viability). Our workflow identified 22 adverse event-assay outcome associations. From these associations, 10 implicated targets could be substantiated with evidence from previous studies reported in the literature. For two of the identified targets, we also describe a more detailed mechanism, forming putative adverse outcome pathways associated with structural cardiotoxicity. Our study also highlights the difficulties deriving these type of associations from the very limited amount of data available.

Characterization and Validation of a Human 3D Cardiac Microtissue for the Assessment of Changes in Cardiac Pathology.

Pharmaceutical agents despite their efficacy to treat disease can cause additional unwanted cardiovascular side effects. Cardiotoxicity is characterized by changes in either the function and/or structure of the myocardium. Over recent years, functional cardiotoxicity has received much attention, however morphological damage to the myocardium and/or loss of viability still requires improved detection and mechanistic insights. A human 3D cardiac microtissue containing human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs), cardiac endothelial cells and cardiac fibroblasts was used to assess their suitability to detect drug induced changes in cardiac structure. Histology and clinical pathology confirmed these cardiac microtissues were morphologically intact, lacked a necrotic/apoptotic core and contained all relevant cell constituents. High-throughput methods to assess mitochondrial membrane potential, endoplasmic reticulum integrity and cellular viability were developed and 15 FDA approved structural cardiotoxins and 14 FDA approved non-structural cardiotoxins were evaluated. We report that cardiac microtissues provide a high-throughput experimental model that is both able to detect changes in cardiac structure at clinically relevant concentrations and provide insights into the phenotypic mechanisms of this liability.

Cytochrome P450 2J2: Potential Role in Drug Metabolism and Cardiotoxicity.

Drug-induced cardiotoxicity may be modulated by endogenous arachidonic acid (AA)-derived metabolites known as epoxyeicosatrienoic acids (EETs) synthesized by cytochrome P450 2J2 (CYP2J2). The biologic effects of EETs, including their protective effects on inflammation and vasodilation, are diverse because, in part, of their ability to act on a variety of cell types. In addition, CYP2J2 metabolizes both exogenous and endogenous substrates and is involved in phase 1 metabolism of a variety of structurally diverse compounds, including some antihistamines, anticancer agents, and immunosuppressants. This review addresses current understanding of the role of CYP2J2 in the metabolism of xenobiotics and endogenous AA, focusing on the effects on the cardiovascular system. In particular, we have promoted here the hypothesis that CYP2J2 influences drug-induced cardiotoxicity through potentially conflicting effects on the production of protective EETs and the metabolism of drugs.