How can we improve our understanding of cardiovascular safety liabilities to develop safer medicines?

Collaborative science in action: A 20 year perspective from the Health and Environmental Sciences Institute (HESI) cardiac safety committee

The Health and Environmental Sciences Institute (HESI) is a nonprofit organization dedicated to resolving global health challenges through collaborative scientific efforts across academia, regulatory authorities and the private sector. Collaborative science across non-clinical disciplines offers an important keystone to accelerate the development of safer and more effective medicines. HESI works to address complex challenges by leveraging diverse subject-matter expertise across sectors offering access to resources, data and shared knowledge. In 2008, the HESI Cardiac Safety Technical Committee (CSTC) was established to improve public health by reducing unanticipated cardiovascular (CV)-related adverse effects from pharmaceuticals or chemicals. The committee continues to significantly impact the field of CV safety by bringing together experts from across sectors to address challenges of detecting and predicting adverse cardiac outcomes. Committee members have collaborated on the organization, management and publication of prospective studies, retrospective analyses, workshops, and symposia resulting in 38 peer reviewed manuscripts. Without this collaboration these manuscripts would not have been published. Through their work, the CSTC is actively addressing challenges and opportunities in detecting potential cardiac failure modes using in vivo, in vitro and in silico models, with the aim of facilitating drug development and improving study design. By examining past successes and future prospects of the CSTC, this manuscript sheds light on how the consortium's multifaceted approach not only addresses current challenges in detecting potential cardiac failure modes but also paves the way for enhanced drug development and study design methodologies. Further, exploring future opportunities and challenges will focus on improving the translational predictability of nonclinical evaluations and reducing reliance on animal research in CV safety assessments.

Electrophysiological Changes in the Rabbit Ventricular Wedge and Human-Induced Pluripotent Stem-Cell Derived (IPSC) Cardiomyocytes Translate to Severe Arrhythmia Observed in a Canine Toxicology Study, Not Predicted by Standard In Vitro Ion Channel Assays

During drug discovery, small molecules are typically assayed in vitro for secondary pharmacology effects, which include ion channels relevant to cardiac electrophysiology. Compound A was an irreversible inhibitor of myeloperoxidase investigated for the treatment of peripheral artery disease. Oral doses in dogs at ≥5 mg/kg resulted in cardiac arrhythmias in a dose-dependent manner (at Cmax, free ≥1.53 μM) that progressed in severity with time. Nevertheless, a panel of 13 different cardiac ion channel (K, Na, and Ca) assays, including hERG, failed to identify pharmacologic risks of the molecule. Compound A and a related Compound B were evaluated for electrophysiological effects in the isolated rabbit ventricular wedge assay. Compounds A and B prolonged QT and Tp-e intervals at ≥1 and ≥.3 μM, respectively, and both prolonged QRS at ≥5 μM. Compound A produced early after depolarizations and premature ventricular complexes at ≥5 μM. These data indicate both compounds may be modulating hERG (Ikr) and Nav1.5 ion channels. In human IPSC cardiomyocytes, Compounds A and B prolonged field potential duration at ≥3 μM and induced cellular dysrhythmia at ≥10 and ≥3 μM, respectively. In a rat toxicology study, heart tissue: plasma concentration ratios for Compound A were ≥19X at 24 hours post-dose, indicating significant tissue distribution. In conclusion, in vitro ion channel assays may not always identify cardiovascular electrophysiological risks observed in vivo, which can be affected by tissue drug distribution. Risk for arrhythmia may increase with a "trappable" ion channel inhibitor, particularly if cardiac tissue drug levels achieve a critical threshold for pharmacologic effects.

Challenging the status quo: a framework for mechanistic and human-relevant cardiovascular safety screening

Traditional approaches to preclinical drug safety assessment have generally protected human patients from unintended adverse effects. However, these assessments typically occur too late to make changes in the formulation or in phase 1 and beyond, are highly dependent on animal studies and have the potential to lead to the termination of useful drugs due to liabilities in animals that are not applicable in patients. Collectively, these elements come at great detriment to both patients and the drug development sector. This phenomenon is particularly problematic in the area of cardiovascular safety assessment where preclinical attrition is high. We believe that a more efficient and translational approach can be defined. A multi-tiered assessment that leverages our understanding of human cardiovascular biology, applies human cell-based in vitro characterizations of cardiovascular responses to insult, and incorporates computational models of pharmacokinetic relationships would enable earlier and more translational identification of human-relevant liabilities. While this will take time to develop, the ultimate goal would be to implement such assays both in the lead selection phase as well as through regulatory phases.

Graphene-integrated mesh electronics with converged multifunctionality for tracking multimodal excitation-contraction dynamics in cardiac microtissues

Cardiac microtissues provide a promising platform for disease modeling and developmental studies, which require the close monitoring of the multimodal excitation-contraction dynamics. However, no existing assessing tool can track these multimodal dynamics across the live tissue. We develop a tissue-like mesh bioelectronic system to track these multimodal dynamics. The mesh system has tissue-level softness and cell-level dimensions to enable stable embedment in the tissue. It is integrated with an array of graphene sensors, which uniquely converges both bioelectrical and biomechanical sensing functionalities in one device. The system achieves stable tracking of the excitation-contraction dynamics across the tissue and throughout the developmental process, offering comprehensive assessments for tissue maturation, drug effects, and disease modeling. It holds the promise to provide more accurate quantification of the functional, developmental, and pathophysiological states in cardiac tissues, creating an instrumental tool for improving tissue engineering and studies.

Pharmacokinetics, biodistribution, and in vivo toxicity of 7-nitroindazole loaded in pegylated and non-pegylated nanoemulsions in rats

Sepsis is a life-threatening condition caused by a dysregulated host response to infection. The development of sepsis is associated with excessive nitric oxide (NO) production, which plays an important role in controlling vascular homeostasis. 7-nitroindazole (7-NI) is a selective inhibitor of neuronal nitric oxide synthase (NOS-1) with potential application for treating NO imbalance conditions. However, 7-NI exhibits a low aqueous solubility and a short plasma half-life. To circumvent these biopharmaceutical limitations, pegylated (NEPEG7NI) and non-pegylated nanoemulsions (NENPEG7NI) containing 7-NI were developed. This study evaluates the pharmacokinetic profiles and toxicological properties of 7-NI loaded into the nanoemulsions. After a single intravenous administration of the free drug and the nanoemulsions at a dose of 10 mg.kg-1 in Wistar rats, 7-NI was widely distributed in the organs. The pharmacokinetic parameters of Cmax, t1/2, and AUC0-t were significantly increased after administration of the NEPEG7NI, compared to both free 7-NI and NENPEG7NI (p < 0.05). No observable adverse effects were observed after administering the free 7-NI, NEPEG7NI, or NENPEG7NI in the animals after a single dose of up to 3.0 mg.kg-1. The results indicated that 7-NI-loaded nanoemulsions are safe, constituting a promising approach to treating sepsis.

Heart-on-a-chip systems: disease modeling and drug screening applications

Cardiovascular disease (CVD) is the leading cause of death worldwide, casting a substantial economic footprint and burdening the global healthcare system. Historically, pre-clinical CVD modeling and therapeutic screening have been performed using animal models. Unfortunately, animal models oftentimes fail to adequately mimic human physiology, leading to a poor translation of therapeutics from pre-clinical trials to consumers. Even those that make it to market can be removed due to unforeseen side effects. As such, there exists a clinical, technological, and economical need for systems that faithfully capture human (patho)physiology for modeling CVD, assessing cardiotoxicity, and evaluating drug efficacy. Heart-on-a-chip (HoC) systems are a part of the broader organ-on-a-chip paradigm that leverages microfluidics, tissue engineering, microfabrication, electronics, and gene editing to create human-relevant models for studying disease, drug-induced side effects, and therapeutic efficacy. These compact systems can be capable of real-time measurements and on-demand characterization of tissue behavior and could revolutionize the drug development process. In this review, we highlight the key components that comprise a HoC system followed by a review of contemporary reports of their use in disease modeling, drug toxicity and efficacy assessment, and as part of multi-organ-on-a-chip platforms. We also discuss future perspectives and challenges facing the field, including a discussion on the role that standardization is expected to play in accelerating the widespread adoption of these platforms.

Cellular Senescence, Mitochondrial Dysfunction, and Their Link to Cardiovascular Disease

Cardiovascular diseases (CVDs), a group of disorders affecting the heart or blood vessels, are the primary cause of death worldwide, with an immense impact on patient quality of life and disability. According to the World Health Organization, CVD takes an estimated 17.9 million lives each year, where more than four out of five CVD deaths are due to heart attacks and strokes. In the decades to come, an increased prevalence of age-related CVD, such as atherosclerosis, coronary artery stenosis, myocardial infarction (MI), valvular heart disease, and heart failure (HF) will contribute to an even greater health and economic burden as the global average life expectancy increases and consequently the world's population continues to age. Considering this, it is important to focus our research efforts on understanding the fundamental mechanisms underlying CVD. In this review, we focus on cellular senescence and mitochondrial dysfunction, which have long been established to contribute to CVD. We also assess the recent advances in targeting mitochondrial dysfunction including energy starvation and oxidative stress, mitochondria dynamics imbalance, cell apoptosis, mitophagy, and senescence with a focus on therapies that influence both and therefore perhaps represent strategies with the most clinical potential, range, and utility.

Characterizing induced pluripotent stem cells and derived cardiomyocytes: insights from nano scale mass measurements and mechanical properties

Our study reveals that the nano-mechanical measures of elasticity and cell mass change significantly through induced pluripotent stem cell (iPSC) differentiation to cardiomyocytes, providing a reliable method to evaluate such processes. The findings support the importance of identifying these properties, and highlight the potential of AFM for comprehensive characterization of iPSC at the nanoscale.

A comprehensive review on 3D tissue models: Biofabrication technologies and preclinical applications

The limitations of traditional two-dimensional (2D) cultures and animal testing, when it comes to precisely foreseeing the toxicity and clinical effectiveness of potential drug candidates, have resulted in a notable increase in the rate of failure during the process of drug discovery and development. Three-dimensional (3D) in-vitro models have arisen as substitute platforms with the capacity to accurately depict in-vivo conditions and increasing the predictivity of clinical effects and toxicity of drug candidates. It has been found that 3D models can accurately represent complex tissue structure of human body and can be used for a wide range of disease modeling purposes. Recently, substantial progress in biomedicine, materials and engineering have been made to fabricate various 3D in-vitro models, which have been exhibited better disease progression predictivity and drug effects than convention models, suggesting a promising direction in pharmaceutics. This comprehensive review highlights the recent developments in 3D in-vitro tissue models for preclinical applications including drug screening and disease modeling targeting multiple organs and tissues, like liver, bone, gastrointestinal tract, kidney, heart, brain, and cartilage. We discuss current strategies for fabricating 3D models for specific organs with their strengths and pitfalls. We expand future considerations for establishing a physiologically-relevant microenvironment for growing 3D models and also provide readers with a perspective on intellectual property, industry, and regulatory landscape.

Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity

BACKGROUND AND OBJECTIVE

In silico methods are gaining attention for predicting drug-induced Torsade de Pointes (TdP) in different stages of drug development. However, many computational models tended not to account for inter-individual response variability due to demographic covariates, such as sex, or physiologic covariates, such as renal function, which may be crucial when predicting TdP. This study aims to compare the effects of drugs in male and female populations with normal and impaired renal function using in silico methods.

METHODS

Pharmacokinetic models considering sex and renal function as covariates were implemented from data published in pharmacokinetic studies. Drug effects were simulated using an electrophysiologically calibrated population of cellular models of 300 males and 300 females. The population of models was built by modifying the endocardial action potential model published by O'Hara et al. (2011) according to the experimentally measured gene expression levels of 12 ion channels.

RESULTS

Fifteen pharmacokinetic models for CiPA drugs were implemented and validated in this study. Eight pharmacokinetic models included the effect of renal function and four the effect of sex. The mean difference in action potential duration (APD) between male and female populations was 24.9 ms (p<0.05). Our simulations indicated that women with impaired renal function were particularly susceptible to drug-induced arrhythmias, whereas healthy men were less prone to TdP. Differences between patient groups were more pronounced for high TdP-risk drugs. The proposed in silico tool also revealed that individuals with impaired renal function, electrophysiologically simulated with hyperkalemia (extracellular potassium concentration [K+]o = 7 mM) exhibited less pronounced APD prolongation than individuals with normal potassium levels. The pharmacokinetic/electrophysiological framework was used to determine the maximum safe dose of dofetilide in different patient groups. As a proof of concept, 3D simulations were also run for dofetilide obtaining QT prolongation in accordance with previously reported clinical values.

CONCLUSIONS

This study presents a novel methodology that combines pharmacokinetic and electrophysiological models to incorporate the effects of sex and renal function into in silico drug simulations and highlights their impact on TdP-risk assessment. Furthermore, it may also help inform maximum dose regimens that ensure TdP-related safety in a specific sub-population of patients.

In-depth mechanistic analysis including high-throughput RNA sequencing in the prediction of functional and structural cardiotoxicants using hiPSC cardiomyocytes

BACKGROUND

Cardiotoxicity remains one of the most reported adverse drug reactions that lead to drug attrition during pre-clinical and clinical drug development. Drug-induced cardiotoxicity may develop as a functional change in cardiac electrophysiology (acute alteration of the mechanical function of the myocardium) and/or as a structural change, resulting in loss of viability and morphological damage to cardiac tissue.

RESEARCH DESIGN AND METHODS

Non-clinical models with better predictive value need to be established to improve cardiac safety pharmacology. To this end, high-throughput RNA sequencing (ScreenSeq) was combined with high-content imaging (HCI) and Ca2+ transience (CaT) to analyze compound-treated human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).

RESULTS

Analysis of hiPSC-CMs treated with 33 cardiotoxicants and 9 non-cardiotoxicants of mixed therapeutic indications facilitated compound clustering by mechanism of action, scoring of pathway activities related to cardiomyocyte contractility, mitochondrial integrity, metabolic state, diverse stress responses and the prediction of cardiotoxicity risk. The combination of ScreenSeq, HCI and CaT provided a high cardiotoxicity prediction performance with 89% specificity, 91% sensitivity and 90% accuracy.

CONCLUSIONS

Overall, this study introduces mechanism-driven risk assessment approach combining structural, functional and molecular high-throughput methods for pre-clinical risk assessment of novel compounds.

A generalized canine transfer function accurately reconstructs central aortic pressure waveforms to enable enhanced pulse wave analysis

Routine preclinical blood pressure evaluation is an important risk assessment tool. Although proximal aortic pressure is most relevant for key target organs, abdominal aortic pressures are more commonly recorded. Pulse pressure amplification and waveform distortion in abdominal waveforms make it inappropriate for central hemodynamic analytical methods without the use of a mathematical transfer function. Clinical transfer functions have been developed to estimate ascending aortic waveforms from brachial or radial artery waveforms in humans, but no preclinical analogues exist. The aim of this study was to develop a canine-specific transfer function to reconstruct thoracic aortic pressure waveforms from abdominal aortic data to enable the application of central hemodynamic analytical methods. Simultaneous abdominal and thoracic blood pressures were recorded from seven conscious, male beagle dogs administered 3 well-characterized pharmacologic standards and animals were appointed to a training (n = 3) or validation (n = 4) group at baseline and during dosing. A generalized transfer function was developed from the training group data and evaluated for its ability to synthesize thoracic pressure waves in the training and validation groups. Select hemodynamic parameters were evaluated in measured and synthesized thoracic data. There was a high degree of correlation between measured and synthesized thoracic parameters (r2 = 0.74-0.99). There was no difference between indices computed from synthesized or actual thoracic waveforms at baseline or after administration of pharmacologic standards. This work demonstrates that a generalized preclinical transfer function can reproduce thoracic pressure waves across a range of hemodynamic responses thus enabling the application of central hemodynamic analytical methods.

Advances in biomaterial-based cardiac organoids

Cardiovascular disease (CVD) is one of the important causes of death worldwide. The incidence and mortality rates are increasing annually with the intensification of social aging. The efficacy of drug therapy is limited in individuals suffering from severe heart failure due to the inability of myocardial cells to undergo regeneration and the challenging nature of cardiac tissue repair following injury. Consequently, surgical transplantation stands as the most efficient approach for treatment. Nevertheless, the shortage of donors and the considerable number of heart failure patients worldwide, estimated at 26 million, results in an alarming treatment deficit, with only around 5000 heart transplants feasible annually. The existing major alternatives, such as mechanical or xenogeneic hearts, have significant flaws, such as high cost and rejection, and are challenging to implement for large-scale, long-term use. An organoid is a three-dimensional (3D) cell tissue that mimics the characteristics of an organ. The critical application has been rated in annual biotechnology by authoritative journals, such as Science and Cell. Related industries have achieved rapid growth in recent years. Based on this technology, cardiac organoids are expected to pave the way for viable heart repair and treatment and play an essential role in pathological research, drug screening, and other areas. This review centers on the examination of biomaterials employed in cardiac repair, strategies employed for the reconstruction of cardiac structure and function, clinical investigations pertaining to cardiac repair, and the prospective applications of cardiac organoids. From basic research to clinical practice, the current status, latest progress, challenges, and prospects of biomaterial-based cardiac repair are summarized and discussed, providing a reference for future exploration and development of cardiac regeneration strategies.

Single-Cell Analysis of Contractile Forces in iPSC-Derived Cardiomyocytes: Paving the Way for Precision Medicine in Cardiovascular Disease

Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) hold enormous potential in cardiac disease modeling, drug screening, and regenerative medicine. Furthermore, patient-specific iPSC-CMS can be tested for personalized medicine. To provide a deeper understanding of the contractile force dynamics of iPSC-CMs, we employed Atomic Force Microscopy (AFM) as an advanced detection tool to distinguish the characteristics of force dynamics at a single cell level. We measured normal (vertical) and lateral (axial) force at different pacing frequencies. We found a significant correlation between normal and lateral force. We also observed a significant force-frequency relationship for both types of forces. This work represents the first demonstration of the correlation of normal and lateral force from individual iPSC-CMs. The identification of this correlation is relevant because it validates the comparison across systems and models that can only account for either normal or lateral force. These findings enhance our understanding of iPSC-CM properties, thereby paving the way for the development of therapeutic strategies in cardiovascular medicine.

CardioMotion: identification of functional and structural cardiotoxic liabilities in small molecules through brightfield kinetic imaging

Cardiovascular toxicity is an important cause of drug failures in the later stages of drug development, early clinical safety assessment, and even postmarket withdrawals. Early-stage in vitro assessment of potential cardiovascular liabilities in the pharmaceutical industry involves assessment of interactions with cardiac ion channels, as well as induced pluripotent stem cell-derived cardiomyocyte-based functional assays, such as calcium flux and multielectrode-array assays. These methods are appropriate for the identification of acute functional cardiotoxicity but structural cardiotoxicity, which manifests effects after chronic exposure, is often only captured in vivo. CardioMotion is a novel, label-free, high throughput, in vitro assay and analysis pipeline which records and assesses the spontaneous beating of cardiomyocytes and identifies compounds which impact beating. This is achieved through the acquisition of brightfield images at a high framerate, combined with an optical flow-based python analysis pipeline which transforms the images into waveform data which are then parameterized. Validation of this assay with a large dataset showed that cardioactive compounds with diverse known direct functional and structural mechanisms-of-action on cardiomyocytes are identified (sensitivity = 72.9%), importantly, known structural cardiotoxins also disrupt cardiomyocyte beating (sensitivity = 86%) in this method. Furthermore, the CardioMotion method presents a high specificity of 82.5%.

Directed graph mapping shows rotors maintain non-terminating and focal sources maintain self-terminating Torsade de Pointes in canine model

Torsade de Pointes is a polymorphic ventricular tachycardia which is as yet incompletely understood. While the onset of a TdP episode is generally accepted to be caused by triggered activity, the mechanisms for the perpetuation is still under debate. In this study, we analysed data from 54 TdP episodes divided over 5 dogs (4 female, 1 male) with chronic atrioventricular block. Previous research on this dataset showed both reentry and triggered activity to perpetuate the arrhythmia. 13 of those TdP episodes showed reentry as part of the driving mechanism of perpetuating the episode. The remaining 41 episodes were purely ectopic. Reentry was the main mechanism in long-lasting episodes (>14 beats), while focal sources were responsible for maintaining shorter episodes. Building on these results, we re-analysed the data using directed graph mapping This program uses principles from network theory and a combination of positional data and local activation times to identify reentry loops and focal sources within the data. The results of this study are twofold. First, concerning reentry loops, we found that on average non-terminating (NT) episodes (≥10 s) show significantly more simultaneous reentry loops than self-terminating (ST) TdP (<10 s). Non-terminating episodes have on average 2.72 ± 1.48 simultaneous loops, compared to an average of 1.33 ± 0.66 for self-terminating episodes. In addition, each NT episode showed a presence of (bi-)ventricular loops between 10.10% and 69.62% of their total reentry duration. Compared to the ST episodes, only 1 in 4 episodes (25%) showed (bi-)ventricular reentry, lasting only 7.12% of its total reentry duration. This suggests that while focal beats trigger TdP, macro-reentry and multiple simultaneous localized reentries are the major drivers of long-lasting episodes. Second, using heatmaps, we found focal sources to occur in preferred locations, instead of being distributed randomly. This may have implications on treatment if such focal origins can be disabled reliably.

Evaluation of chronic drug-induced electrophysiological and cytotoxic effects using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs)

Introduction: Cardiotoxicity is one of the leading causes of compound attrition during drug development. Most in vitro screening platforms aim at detecting acute cardio-electrophysiological changes and drug-induced chronic functional alterations are often not studied in the early stage of drug development. Therefore, we developed an assay using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) that evaluates both drug-induced acute and delayed electrophysiological and cytotoxic effects of reference compounds with clinically known cardiac outcomes. Methods: hiPSC-CMs were seeded in 48-well multielectrode array (MEA) plates and were treated with four doses of reference compounds (covering and exceeding clinical free plasma peak concentrations -fC_max values) and MEA recordings were conducted for 4 days. Functional-electrophysiological (field-potentials) and viability (impedance) parameters were recorded with a MEA machine. Results: To assess this platform, we tested tyrosine-kinase inhibitors with high-cardiac risk profile (sunitinib, vandetanib and nilotinib) and low-cardiac risk (erlotinib), as well as known classic cardiac toxic drugs (doxorubicin and BMS-986094), ion-channel trafficking inhibitors (pentamidine, probucol and arsenic trioxide) and compounds without known clinical cardiotoxicity (amoxicillin, cetirizine, captopril and aspirin). By evaluating the effects of these compounds on MEA parameters, the assay was mostly able to recapitulate different drug-induced cardiotoxicities, represented by a prolongation of the field potential, changes in beating rate and presence of arrhythmic events in acute (<2 h) or delayed phase ≥24 h, and/or reduction of impedance during the delayed phase (≥24 h). Furthermore, a few reference compounds were tested in hiPSC-CMs using fluorescence- and luminescence-based plate reader assays, confirming the presence or absence of cytotoxic effects, linked to changes of the impedance parameters measured in the MEA assay. Of note, some cardiotoxic effects could not be identified at acute time points (<2 h) but were clearly detected after 24 h, reinforcing the importance of chronic drug evaluation. Discussion: In conclusion, the evaluation of chronic drug-induced cardiotoxicity using a hiPSC-CMs in vitro assay can contribute to the early de-risking of compounds and help optimize the drug development process.

Index of cardiac-electrophysiological balance in relapsing-remitting multiple sclerosis patients treated with fingolimod

BACKGROUND

Fingolimod is indicated for the treatment of relapsing-remitting multiple sclerosis (RRMS) and also targets cardiovascular system due to receptors on cardiomyocytes. Results of previous studies are controversial for the effect of fingolimod in terms of ventricular arrhythmias. Index of cardio-electrophysiological balance (iCEB) is a risk marker for predicting malignant ventricular arrhythmia. There is no evidence on the effect of fingolimod on iCEB in patients with relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to evaluate iCEB in patients with RRMS treated with fingolimod .

METHODS

A total of 86 patients with RRMS treated with fingolimod were included in the study. All patients underwent a standard 12-lead surface electrocardiogram at initiation of treatment and 6 h after treatment. Heart rate, RR interval, QRS duration, QT, QTc (heart rate corrected QT), T wave peak-to-end (Tp-e) interval, Tp-e/QT, Tp-e/QTc, iCEB (QT/QRS) and iCEBc (QTc/QRS) ratios were calculated from the electrocardiogram. QT correction for heart rate was performed using both the Bazett and Fridericia formulas. Pre-treatment and post-treatment values were compared.

RESULTS

Heart rate was significantly lower after fingolimod treatment (p< 0.001). While the post-treatment values of RR and QT intervals were significantly longer (p< 0.001) and post-treatment iCEB was higher (median [Q1-Q3], 4.23 [3.95-4.50] vs 4.53 [4.18-5.14]; p< 0.001), it was found that there was no statistically significant change in iCEB and other study parameters derived using QT after correcting for heart rate using both of two formulas.

CONCLUSIONS

In this study, it was found that fingolimod did not statistically significantly change any of the heart rate-corrected ventricular repolarization parameters, including iCEBc, and it is safe in terms of ventricular arrhythmia.

Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking

Graph neural networks (GNNs) have been widely used in molecular property prediction, but explaining their black-box predictions is still a challenge. Most existing explanation methods for GNNs in chemistry focus on attributing model predictions to individual nodes, edges or fragments that are not necessarily derived from a chemically meaningful segmentation of molecules. To address this challenge, we propose a method named substructure mask explanation (SME). SME is based on well-established molecular segmentation methods and provides an interpretation that aligns with the understanding of chemists. We apply SME to elucidate how GNNs learn to predict aqueous solubility, genotoxicity, cardiotoxicity and blood-brain barrier permeation for small molecules. SME provides interpretation that is consistent with the understanding of chemists, alerts them to unreliable performance, and guides them in structural optimization for target properties. Hence, we believe that SME empowers chemists to confidently mine structure-activity relationship (SAR) from reliable GNNs through a transparent inspection on how GNNs pick up useful signals when learning from data.

Evaluation of a Cardiovascular Systems Model for Design and Analysis of Hemodynamic Safety Studies

Early prediction, quantification and translation of cardiovascular hemodynamic drug effects is essential in pre-clinical drug development. In this study, a novel hemodynamic cardiovascular systems (CVS) model was developed to support these goals. The model consisted of distinct system- and drug-specific parameter, and uses data for heart rate (HR), cardiac output (CO), and mean atrial pressure (MAP) to infer drug mode-of-action (MoA). To support further application of this model in drug development, we conducted a systematic analysis of the estimation performance of the CVS model to infer drug- and system-specific parameters. Specifically, we focused on the impact on model estimation performance when considering differences in available readouts and the impact of study design choices. To this end, a practical identifiability analysis was performed, evaluating model estimation performance for different combinations of hemodynamic endpoints, drug effect sizes, and study design characteristics. The practical identifiability analysis showed that MoA of drug effect could be identified for different drug effect magnitudes and both system- and drug-specific parameters can be estimated precisely with minimal bias. Study designs which exclude measurement of CO or use a reduced measurement duration still allow the identification and quantification of MoA with acceptable performance. In conclusion, the CVS model can be used to support the design and inference of MoA in pre-clinical CVS experiments, with a future potential for applying the uniquely identifiable systems parameters to support inter-species scaling.

Modeling Heart Diseases on a Chip: Advantages and Future Opportunities

Heart disease is a significant burden on global health care systems and is a leading cause of death each year. To improve our understanding of heart disease, high quality disease models are needed. These will facilitate the discovery and development of new treatments for heart disease. Traditionally, researchers have relied on 2D monolayer systems or animal models of heart disease to elucidate pathophysiology and drug responses. Heart-on-a-chip (HOC) technology is an emerging field where cardiomyocytes among other cell types in the heart can be used to generate functional, beating cardiac microtissues that recapitulate many features of the human heart. HOC models are showing great promise as disease modeling platforms and are poised to serve as important tools in the drug development pipeline. By leveraging advances in human pluripotent stem cell-derived cardiomyocyte biology and microfabrication technology, diseased HOCs are highly tuneable and can be generated via different approaches such as: using cells with defined genetic backgrounds (patient-derived cells), adding small molecules, modifying the cells' environment, altering cell ratio/composition of microtissues, among others. HOCs have been used to faithfully model aspects of arrhythmia, fibrosis, infection, cardiomyopathies, and ischemia, to name a few. In this review, we highlight recent advances in disease modeling using HOC systems, describing instances where these models outperformed other models in terms of reproducing disease phenotypes and/or led to drug development.

A deep learning platform to assess drug proarrhythmia risk

Drug safety initiatives have endorsed human iPSC-derived cardiomyocytes (hiPSC-CMs) as an in vitro model for predicting drug-induced cardiac arrhythmia. However, the extent to which human-defined features of in vitro arrhythmia predict actual clinical risk has been much debated. Here, we trained a convolutional neural network classifier (CNN) to learn features of in vitro action potential recordings of hiPSC-CMs that are associated with lethal Torsade de Pointes arrhythmia. The CNN classifier accurately predicted the risk of drug-induced arrhythmia in people. The risk profile of the test drugs was similar across hiPSC-CMs derived from different healthy donors. In contrast, pathogenic mutations that cause arrhythmogenic cardiomyopathies in patients significantly increased the proarrhythmic propensity to certain intermediate and high-risk drugs in the hiPSC-CMs. Thus, deep learning can identify in vitro arrhythmic features that correlate with clinical arrhythmia and discern the influence of patient genetics on the risk of drug-induced arrhythmia.

Organ Chips and Visualization of Biological Systems

Organ-on-a-chip (OOC) is an emerging frontier cross-cutting science and technology developed in the past 10 years. It was first proposed by the Wyss Institute for Biologically Inspired Engineering of Harvard Medical School. It consists of a transparent flexible polymer the size of a computer memory stick, with hollow microfluidic channels lined with living human cells. Researchers used bionics methods to simulate the microenvironment of human cells on microfluidic chips, so as to realize the basic physiological functions of corresponding tissues and organs in vitro. Transparent chip materials can perform real-time visualization and high-resolution analysis of various human life processes in a way that is impossible in animal models, so as to better reproduce the microenvironment of human tissue and simulate biological systems in vitro to observe drug metabolism and other life processes. It provides innovative research systems and system solutions for in vitro bionics of biological systems. It also has gradually become a new tool for disease mechanism research and new drug development. In this chapter, we will take the current research mature single-organ-on-a-chip and multi-organ human-on-a-chip as examples; give an overview of the research background and underlying technologies in this field, especially the application of in vitro bionic models in visualized medicine; and look forward to the foreseeable future development prospects after the integration of organ-on-chip and organoid technology.

Toward Quantitative Models in Safety Assessment: A Case Study to Show Impact of Dose-Response Inference on hERG Inhibition Models

Due to challenges with historical data and the diversity of assay formats, in silico models for safety-related endpoints are often based on discretized data instead of the data on a natural continuous scale. Models for discretized endpoints have limitations in usage and interpretation that can impact compound design. Here, we present a consistent data inference approach, exemplified on two data sets of Ether-à-go-go-Related Gene (hERG) K+ inhibition data, for dose-response and screening experiments that are generally applicable for in vitro assays. hERG inhibition has been associated with severe cardiac effects and is one of the more prominent safety targets assessed in drug development, using a wide array of in vitro and in silico screening methods. In this study, the IC₅₀ for hERG inhibition is estimated from diverse historical proprietary data. The IC₅₀ derived from a two-point proprietary screening data set demonstrated high correlation (R = 0.98, MAE = 0.08) with IC_50s derived from six-point dose-response curves. Similar IC₅₀ estimation accuracy was obtained on a public thallium flux assay data set (R = 0.90, MAE = 0.2). The IC₅₀ data were used to develop a robust quantitative model. The model's MAE (0.47) and R² (0.46) were on par with literature statistics and approached assay reproducibility. Using a continuous model has high value for pharmaceutical projects, as it enables rank ordering of compounds and evaluation of compounds against project-specific inhibition thresholds. This data inference approach can be widely applicable to assays with quantitative readouts and has the potential to impact experimental design and improve model performance, interpretation, and acceptance across many standard safety endpoints.

Contraction pressure analysis using optical imaging in normal and MYBPC3-mutated hiPSC-derived cardiomyocytes grown on matrices with tunable stiffness

Current in vivo disease models and analysis methods for cardiac drug development have been insufficient in providing accurate and reliable predictions of drug efficacy and safety. Here, we propose a custom optical flow-based analysis method to quantitatively measure recordings of contracting cardiomyocytes on polydimethylsiloxane (PDMS), compatible with medium-throughput systems. Movement of the PDMS was examined by covalently bound fluorescent beads on the PDMS surface, differences caused by increased substrate stiffness were compared, and cells were stimulated with β-agonist. We further validated the system using cardiomyocytes treated with endothelin-1 and compared their contractions against control and cells incubated with receptor antagonist bosentan. After validation we examined two MYBPC3-mutant patient-derived cell lines. Recordings showed that higher substrate stiffness resulted in higher contractile pressure, while beating frequency remained similar to control. β-agonist stimulation resulted in both higher beating frequency as well as higher pressure values during contraction and relaxation. Cells treated with endothelin-1 showed an increased beating frequency, but a lower contraction pressure. Cells treated with both endothelin-1 and bosentan remained at control level of beating frequency and pressure. Lastly, both MYBPC3-mutant lines showed a higher beating frequency and lower contraction pressure. Our validated method is capable of automatically quantifying contraction of hiPSC-derived cardiomyocytes on a PDMS substrate of known shear modulus, returning an absolute value. Our method could have major benefits in a medium-throughput setting.

To Clot or Not to Clot: Deepening Our Understanding of Alterations in the Hemostatic System

The session on the hemostatic system focused on new developments in coagulation and platelet biology as well as how therapeutic agents may affect hemostasis. The classic cascade model of coagulation was compared with the more recent models of cell-based and vascular-based coagulation, which may provide better insight on how the coagulation cascade works in vivo. A review of platelet biology highlighted that, as platelets age, desialylated platelets form and are recognized by Ashwell-Morell receptor (AMR), leading to hepatic uptake and subsequent increase in thrombopoietin (TPO) production. Administration of therapeutics that induce thrombocytopenia was also discussed, including Mylotarg, which is an antibody-drug conjugate that was shown to decrease human megakaryocyte development but had no effect on platelet aggregation. An acetyl co-A carboxylase inhibitor was shown to cause thrombocytopenia by inhibiting de novo lipogenesis, which is critical for the formation of the megakaryocyte demarcation membrane system responsible for platelet production. It was also illustrated how preclinical translation models have been very helpful in the development of adeno-associated virus (AAV) hemophilia B gene therapy and what old and new preclinical tools we have that can predict the risk of a prothrombotic state in people.

Fabrication of human myocardium using multidimensional modelling of engineered tissues

Biofabrication of human tissues has seen a meteoric growth triggered by recent technical advancements such as human induced pluripotent stem cells (hiPSCs) and additive manufacturing. However, generation of cardiac tissue is still hampered by lack of addequate mechanical properties and crucially by the often unpredictable post-fabrication evolution of biological components. In this study we employ melt electrowriting (MEW) and hiPSC-derived cardiac cells to generate fibre-reinforced human cardiac minitissues. These are thoroughly characterized in order to build computational models and simulations able to predict their post-fabrication evolution. Our results show that MEW-based human minitissues display advanced maturation 28 post-generation, with a significant increase in the expression of cardiac genes such as MYL2, GJA5, SCN5A and the MYH7/MYH6 and MYL2/MYL7 ratios. Human iPSC-cardiomyocytes are significantly more aligned within the MEW-based 3D tissues, as compared to conventional 2D controls, and also display greater expression of CX43. These are also correlated with a more mature functionality in the form of faster conduction velocity. We used these data to develop simulations capable of accurately reproducing the experimental performance. In-depth gauging of the structural disposition (cellular alignment) and intercellular connectivity (CX43) allowed us to develop an improved computational model able to predict the relationship between cardiac cell alignment and functional performance. This study lays down the path for advancing in the development of in silico tools to predict cardiac biofabricated tissue evolution after generation, and maps the route towards more accurate and biomimetic tissue manufacture.

Drug-Induced QT Prolongation and Torsade de Pointes in Spontaneous Adverse Event Reporting: A Retrospective Analysis Using the Japanese Adverse Drug Event Report Database (2004-2021)

BACKGROUND

Drugs with new mechanisms of action are continually being developed, but it is difficult to capture whether a drug induces QT prolongation/torsade de pointes (TdP) in preclinical and preapproval clinical trials.

OBJECTIVE

To evaluate drugs associated with drug-induced QT prolongation/TdP using a real-world database in Japan.

PATIENTS AND METHODS

A search was performed in the Japanese Adverse Drug Event Report (JADER) database for QT prolongation and TdP. The reporting odds ratio (ROR) was calculated to identify potential drug-induced QT prolongation/TdP association.

RESULTS

Among the reported 4,326,484 data entries, 3410 patients exhibited QT prolongation/TdP (2707 with QT prolongation, 703 with TdP) with the suspected drugs. Of these patients, 53.9% were females. The highest occurrence was in the 70- to 79-year-old age group (24.7%). The most common types of drugs involved were cardiovascular drugs, central nervous system (CNS) drugs, anticancer drugs, and anti-infective drugs; the rate of overdose was reportedly very low at 1.6%. The highest adjusted RORs were observed for nifekalant (351.41, 95% confidence interval (CI) 235.85-523.59), followed by vandetanib (182.55, 95% CI 108.11-308.24), evocalcet (181.59, 95% CI 132.96-248.01), bepridil (160.37, 95% CI 138.17-186.13), diarsenic trioxide (79.43, 95% CI 63.98-98.62), and guanfacine (78.29, 95% CI 58.51-104.74). Among the drugs launched in Japan during the last decade, vandetanib had the highest adjusted RORs.

CONCLUSIONS

This study using the JADER database showed that antiarrhythmic drugs, calcium-sensing receptor agonists, small-molecule targeted anticancer drugs, and CNS drugs are associated with QT prolongation/TdP. Further pharmacoepidemiological studies, such as cohort studies using large databases, are needed to prove these causal relationships.

Strategies and Tools for Supporting the Appropriateness of Drug Use in Older People

Through this structured review of the published literature, we aimed to provide an up-to-date description of strategies (human-related) and tools (mainly from the digital field) facilitating the appropriateness of drug use in older adults. The evidence of each strategy and tool’s effectiveness and sustainability largely derives from local and heterogeneous experiences, with contrasting results. As a general framework, three main steps should be considered in implementing measures to improve appropriateness: prescription, acceptance by the patient, and continuous monitoring of adherence and risk-benefit profile. Each step needs efforts from specific actors (physicians, patients, caregivers, healthcare professionals) and dedicated supporting tools. Moreover, how to support the appropriateness also strictly depends on the particular setting of care (hospital, ambulatory or primary care, nursing home, long-term care) and available economic resources. Therefore, it is urgent assigning to each approach proposed in the literature the following characteristics: level of effectiveness, strength of evidence, setting of implementation, needed resources, and issues for its sustainability.

Functional isolation, culture and cryopreservation of adult human primary cardiomyocytes

Cardiovascular diseases are the most common cause of death globally. Accurately modeling cardiac homeostasis, dysfunction, and drug response lies at the heart of cardiac research. Adult human primary cardiomyocytes (hPCMs) are a promising cellular model, but unstable isolation efficiency and quality, rapid cell death in culture, and unknown response to cryopreservation prevent them from becoming a reliable and flexible in vitro cardiac model. Combing the use of a reversible inhibitor of myosin II ATPase, (-)-blebbistatin (Bleb), and multiple optimization steps of the isolation procedure, we achieved a 2.74-fold increase in cell viability over traditional methods, accompanied by better cellular morphology, minimally perturbed gene expression, intact electrophysiology, and normal neurohormonal signaling. Further optimization of culture conditions established a method that was capable of maintaining optimal cell viability, morphology, and mitochondrial respiration for at least 7 days. Most importantly, we successfully cryopreserved hPCMs, which were structurally, molecularly, and functionally intact after undergoing the freeze-thaw cycle. hPCMs demonstrated greater sensitivity towards a set of cardiotoxic drugs, compared to human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Further dissection of cardiomyocyte drug response at both the population and single-cell transcriptomic level revealed that hPCM responses were more pronouncedly enriched in cardiac function, whereas hiPSC-CMs responses reflected cardiac development. Together, we established a full set of methodologies for the efficient isolation and prolonged maintenance of functional primary adult human cardiomyocytes in vitro, unlocking their potential as a cellular model for cardiovascular research, drug discovery, and safety pharmacology.

The utility of hERG channel inhibition data in the derivation of occupational exposure limits

Inhibition of the human ether-à-go-go (hERG) channel may lead to QT prolongation and fatal arrhythmia. While pharmaceutical drug candidates that exhibit potent hERG channel inhibition often fail early in development, many drugs with both cardiac and non-cardiac indications proceed to market. In this study, the relationship between in vitro hERG channel inhibition and published occupational exposure limit (OEL) was evaluated. A total of 23 cardiac drugs and 44 drugs with non-cardiac indications with published hERG channel IC₅₀ and published OELs were identified. There was an apparent relationship between hERG IC₅₀ potency and the OEL for cardiac and non-cardiac drugs. Twenty cardiac and non-cardiac drugs were identified that had a potent hERG IC₅₀ (≤25 μM) and a contrastingly large OEL value (≥100 μg/m³). OELs or hazard banding corresponding to ≤100 μg/m³ should be sufficiently protective of effects following occupational exposure to the majority of APIs with hERG IC₅₀ values ≤ 100 μM. It is important to consider hERG IC₅₀ values and possible cardiac effects when deriving OEL values for drugs, regardless of indication. These considerations may be particularly important early in the drug development process for establishing exposure control bands for drugs that do not yet have full clinical safety data.

Venetoclax Induces Cardiotoxicity through Modulation of Oxidative-Stress-Mediated Cardiac Inflammation and Apoptosis via NF-κB and BCL-2 Pathway

Cardiovascular damage induced by anticancer therapy has become the main health problem after tumor elimination. Venetoclax (VTX) is a promising novel agent that has been proven to have a high efficacy in multiple hematological diseases, especially acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL). Considering its mechanism of action, the possibility that VTX may cause cardiotoxicity cannot be ruled out. Therefore, this study was designed to investigate the toxic effect of VTX on the heart. Male Sprague-Dawley rats were randomly divided into three groups: control, low-dose VTX (50 mg/kg via oral gavage), and high-dose VTX (100 mg/kg via oral gavage). After 21 days, blood and tissue samples were collected for histopathological, biochemical, gene, and protein analyses. We demonstrated that VTX treatment resulted in cardiac damages as evidenced by major changes in histopathology and markedly elevated cardiac enzymes and hypertrophic genes markers. Moreover, we observed a drastic increase in oxidative stress, as well as inflammatory and apoptotic markers, with a remarkable decline in the levels of Bcl-2. To the best of our knowledge, this study is the first to report the cardiotoxic effect of VTX. Further experiments and future studies are strongly needed to comprehensively understand the cardiotoxic effect of VTX.

A Change of Heart: Human Cardiac Tissue Engineering as a Platform for Drug Development

PURPOSE OF REVIEW

Human cardiac tissue engineering holds great promise for early detection of drug-related cardiac toxicity and arrhythmogenicity during drug discovery and development. We describe shortcomings of the current drug development pathway, recent advances in the development of cardiac tissue constructs as drug testing platforms, and the challenges remaining in their widespread adoption.

RECENT FINDINGS

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have been used to develop a variety of constructs including cardiac spheroids, microtissues, strips, rings, and chambers. Several ambitious studies have used these constructs to test a significant number of drugs, and while most have shown proper negative inotropic and arrhythmogenic responses, few have been able to demonstrate positive inotropy, indicative of relative hPSC-CM immaturity. Several engineered human cardiac tissue platforms have demonstrated native cardiac physiology and proper drug responses. Future studies addressing hPSC-CM immaturity and inclusion of patient-specific cell lines will further advance the utility of such models for in vitro drug development.

microRNAs signatures as potential biomarkers of structural cardiotoxicity in human-induced pluripotent stem-cell derived cardiomyocytes

Identification of early biomarkers of heart injury and drug-induced cardiotoxicity is important to eliminate harmful drug candidates early in preclinical development and to prevent severe drug effects. The main objective of this study was to investigate the expression of microRNAs (miRNAs) in human-induced pluripotent stem cell cardiomyocytes (hiPSC-CM) in response to a broad range of cardiotoxic drugs. Next generation sequencing was applied to hiPSC-CM treated for 72 h with 40 drugs falling into the categories of functional (i.e., ion channel blockers), structural (changes in cardiomyocytes structure), and general (causing both functional and structural) cardiotoxicants as well as non-cardiotoxic drugs. The largest changes in miRNAs expression were observed after treatments with structural or general cardiotoxicants. The number of deregulated miRNAs was the highest for idarubicin, mitoxantrone, and bortezomib treatments. RT-qPCR validation confirmed upregulation of several miRNAs across multiple treatments at therapeutically relevant concentrations: hsa-miR-187-3p, hsa-miR-146b-5p, hsa-miR-182-5p (anthracyclines); hsa-miR-365a-5p, hsa-miR-185-3p, hsa-miR-184, hsa-miR-182-5p (kinase inhibitors); hsa-miR-182-5p, hsa-miR-126-3p and hsa-miR-96-5p (common some anthracyclines, kinase inhibitors and bortezomib). Further investigations showed that an upregulation of hsa-miR-187-3p and hsa-miR-182-5p could serve as a potential biomarker of structural cardiotoxicity and/or an additional endpoint to characterize cardiac injury in vitro.

Human Engineered Heart Tissue Models for Disease Modeling and Drug Discovery

The emergence of human induced pluripotent stem cells (hiPSCs) and efficient differentiation of hiPSC-derived cardiomyocytes (hiPSC-CMs) induced from diseased donors have the potential to recapitulate the molecular and functional features of the human heart. Although the immaturity of hiPSC-CMs, including the structure, gene expression, conduct, ion channel density, and Ca²⁺ kinetics, is a major challenge, various attempts to promote maturation have been effective. Three-dimensional cardiac models using hiPSC-CMs have achieved these functional and morphological maturations, and disease models using patient-specific hiPSC-CMs have furthered our understanding of the underlying mechanisms and effective therapies for diseases. Aside from the mechanisms of diseases and drug responses, hiPSC-CMs also have the potential to evaluate the safety and efficacy of drugs in a human context before a candidate drug enters the market and many phases of clinical trials. In fact, novel drug testing paradigms have suggested that these cells can be used to better predict the proarrhythmic risk of candidate drugs. In this review, we overview the current strategies of human engineered heart tissue models with a focus on major cardiac diseases and discuss perspectives and future directions for the real application of hiPSC-CMs and human engineered heart tissue for disease modeling, drug development, clinical trials, and cardiotoxicity tests.

Rapid Detection of Direct Compound Toxicity and Trailing Detection of Indirect Cell Metabolite Toxicity in a 96-Well Fluidic Culture Device for Cell-Based Screening Environments: Tactics in Six Sigma Quality Control Charts

Microfluidic screening tools, in vitro, evolve amid varied scientific disciplines. One emergent technique, simultaneously assessing cell toxicity from a primary compound and ensuing cell-generated metabolites (dual-toxicity screening), entails in-line systems having sequentially aligned culture chambers. To explore dual-tox screens, we probe the dissemination of nutrients involving 1-way transport with upstream compound dosing, midstream cascading flows, and downstream cessation. Distribution of flow gives rise to broad concentration ranges of dosing compound (0→ICcompound100) and wide-ranging concentration ranges of generated cell metabolites (0→ICmetabolites100). Innately, single-pass unidirectional flow retains 1st pass informative traits across the network, composed of nine interconnected culture wells, preserving both compound and cell-secreted byproducts as data indicators in each adjacent culture chamber. Thereafter, to assess effective compound hepatotoxicity (0→ECcompound100) and simultaneously classify for cell-metabolite toxicity (0→ECmetabolite100), we reveal utility by analyzing culture viability against ramping exposures of acetaminophen (APAP) and nefazodone (NEF), compounds of hepatic significance. We then discern metabolite generation with an emphasis on amplification across µchannel multiwell sites. Lastly, using conventional cell functions as indicator tools to assess dual toxicity, we investigate a non-drug induced liver injury (non-DILI) compound and DILI compound. The technology is for predictive evaluations of new compound formulations, new chemical entities (NCE), or drugs that have previously failed testing for unresolved reasons.

Kinase inhibitor-induced cardiotoxicity assessed in vitro with human pluripotent stem cell derived cardiomyocytes

Many small molecule kinase inhibitors (SMKIs), used predominately in cancer therapy, have been implicated in serious clinical cardiac adverse events, which means that traditional preclinical drug development assays were not sufficient for identifying these cardiac liabilities. To improve clinical cardiac safety predictions, the effects of SMKIs targeting many different signaling pathways were studied using human pluripotent stem cell derived cardiomyocytes (hPSC-CMs) in combined assays designed for the detection of both electrophysiological (proarrhythmic) and non-electrophysiological (non-proarrhythmic) drug-induced cardiotoxicity. Several microplate-based assays were used to quantitate cell death, apoptosis, mitochondrial damage, energy depletion, and oxidative stress as mechanism-based non-electrophysiological cardiomyocyte toxicities. Microelectrode arrays (MEA) were used to quantitate vitro arrhythmic events (iAEs), field potential duration (FPD) prolongation, and spike amplitude suppression (SAS) as electrophysiological effects. To enhance the clinical relevance, SMKIs induced cardiotoxicities were compared by converting dug concentrations into multiples of reported clinical maximum therapeutic plasma concentration, "FoldC_max", for each assay. The results support the conclusion that the combination of the hPSC-CMs based electrophysiological and non-electrophysiological assays have significantly more predictive value than either assay alone, and significantly more than the current FDA-recommended hERG assay. In addition, the combination of these assays provided mechanistic information relevant to cardiomyocyte toxicities, thus providing valuable information on potential drug-induced cardiotoxicities early in drug development prior to animal and clinical testing. We believe that this early information will be helpful to guide the development of safer and more cost-effective drugs.

Open-access database of literature derived drug-related Torsade de Pointes cases

Since an introduction of an ICH guidance in 2005, no new drugs were withdrawn from the market because of the causation of Torsade de Pointes (TdP). However, the risk of TdP is still a concern for marketed drugs. TdP is a type of polymorphic ventricular tachycardia which may lead to sudden cardiac death. QT/QTc interval prolongation is considered a sensitive, but not specific biomarker. To improve the effectiveness of studies’ workflow related to TdP risk prediction we created an extensive, structured, open-access database of drug-related TdP cases. PubMed, Google Scholar bibliographic databases, and the Internet, via the Google search engine, were searched to identify eligible reports. A total of 424 papers with a description of 634 case reports and observational studies were included. Each paper was manually examined and listed with up to 53 variables related to patient/population characteristics, general health parameters, used drugs, laboratory measurements, ECG results, clinical management, and its outcomes, as well as suspected drug’s properties and its FDA adverse reaction reports. The presented database may be considered as an extension of the recently developed and published database of drug cardiac safety-related information, part of the tox-portal project providing resources for cardiac toxicity assessment.

A tiered approach to population-based in vitro testing for cardiotoxicity: Balancing estimates of potency and variability

Population-wide in vitro studies for characterization of cardiotoxicity hazard, risk, and population variability show that human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) are a powerful and high-throughput testing platform for drugs and environmental chemicals alike. However, studies in multiple donor-derived hiPSC-CMs, across large libraries of chemicals tested in concentration-response are technically complex, and study design optimization is needed to determine sufficient and fit-for-purpose population size considerations. Therefore, we tested a hypothesis that a computational down-sampling analysis based on the data from hiPSC-CM screening of 136 diverse compounds in a population of 43 non-diseased donors, including multiple replicates of the "standard" donor hiPSC-CMs, will inform optimal study designs depending on the decision context (hazard, risk and/or inter-individual variability in cardiotoxicity). Through 50 independent random subsamples of 5, 10, or 20 donors, we estimated accuracy and precision for quantifying potency, inter-individual variability, and QT prolongation risk; the results were compared to the full 43-donor cohort. We found that for potency and clinical risk of QT prolongation, a cohort of 5 randomly-selected unique donors provides accurate and precise estimates. Larger cohort sizes afforded marginal improvements, and 5 replicates of a single donor performed worse. For estimating inter-individual variability, cohorts of at least 20 donors are needed, with smaller populations on average showing bias towards underestimation in population variance. Collectively, this study shows that a variable-size hiPSC-CM-based population-wide in vitro model can be used in a number of decision scenarios for identifying cardiotoxic hazards of drugs and environmental chemicals in the population context.

Monitoring haemodynamic changes in rodent models to better inform safety pharmacology: Novel insights from

Animal models are essential for assessing cardiovascular responses to novel therapeutics. Cardiovascular safety liabilities represent a leading cause of drug attrition and better preclinical measurements are essential to predict drug-related toxicities. Presently, radiotelemetric approaches recording blood pressure are routinely used in preclinical in vivo haemodynamic assessments, providing valuable information on therapy-associated cardiovascular effects. Nonetheless, this technique is chiefly limited to the monitoring of blood pressure and heart rate alone. Alongside these measurements, Doppler flowmetry can provide additional information on the vasculature by simultaneously measuring changes in blood flow in multiple different regional vascular beds. However, due to the time-consuming and expensive nature of this approach, it is not widely used in the industry. Currently, analysis of waveform data obtained from telemetry and Doppler flowmetry typically examines averages or peak values of waveforms. Subtle changes in the morphology and variability of physiological waveforms have previously been shown to be early markers of toxicity and pathology. Therefore, a detailed analysis of pressure and flowmetry waveforms could enhance the understanding of toxicological mechanisms and the ability to translate these preclinical observations to clinical outcomes. In this review, we give an overview of the different approaches to monitor the effects of drugs on cardiovascular parameters (particularly regional blood flow, heart rate and blood pressure) and suggest that further development of waveform analysis could enhance our understanding of safety pharmacology, providing valuable information without increasing the number of in vivo studies needed.

Non-cancer to anti-cancer: investigation of human ether-a-go-go-related gene potassium channel inhibitors as potential therapeutics

BACKGROUND

The expression of hERG K⁺ channels is observed in various cancer cells including epithelial, neuronal, leukemic, and connective tissue. The role of hERG potassium channels in regulating the growth and death of cancer cells include cell proliferation, survival, secretion of proangiogenic factors, invasiveness, and metastasis.

METHODS

In the reported study, an attempt has been made to investigate some non-cancer hERG blockers as potential cancer therapeutics using a computational drug repurposing strategy. Preliminary investigation for hERG blockers/non-blockers has identified 26 potential clinically approved compounds for further studies using molecular modeling.

RESULTS

The interactions at the binding pockets have been investigated along with the prioritization based on the binding score. Some of the identified potential hERG inhibitors, i.e., Bromocriptine, Darglitazone, and Troglitazone, have been investigated to derive the mechanism of cancer inhibition.

CONCLUSIONS

The proposed mechanism for anti-cancer properties via hERG blocking for some of the potential compounds is required to be explored using other experimental methodologies. The drug repurposing approach applied to investigate anti-cancer therapeutics may direct to provide a therapeutic solution to late-stage cancer and benefit a significant population of patients.

Artificial Intelligence in Drug Safety and Metabolism

The use of artificial intelligence methods in drug safety began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been endlessly expanding ever since and the models have become more complex. These approaches are now integrated into molecule risk assessment processes along with in vitro and in vivo methods. Today, artificial intelligence can be used in every phase of drug discovery and development, from profiling chemical libraries in early discovery, to predicting off-target effects in the mid-discovery phase, to assessing potential mutagenic impurities in development and degradants as part of life cycle management. This chapter provides an overview of artificial intelligence in drug safety and describes its application throughout the entire discovery and development process.

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.