Quantitatively characterizing drug‐induced arrhythmic contractile motions of human stem cell‐derived cardiomyocytes

Hoang, Plansky; Huebsch, Nathaniel; Bang, Shin Hyuk; Siemons, Brian; Conklin, Bruce R.; Healy, Kevin E.; Ma, Zhen; Jacquir, Sabir

doi:10.1002/bit.26709

Cited by 5 publications

(6 citation statements)

References 33 publications

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“…Our platform showed expected changes in arrhythmia metrics to known toxicants and revealed alterations in response to the endocrine disrupting chemical BPA with high sensitivity that suggest cardiac risk and point toward disrupted ion channels as mechanisms of action that may not have been detected in other platforms with more surrogate metrics. Further, automated image analysis and computational approaches including machine learning that have mainly been applied to 2D systems and focus on different outcome metrics such as Ca transient and contractile motion tracking [94][95][96] . can be applied for AP analyses in our platform to increase its predictive power.…”

Section: Discussionmentioning

confidence: 99%

A predictive in vitro risk assessment platform for pro-arrhythmic toxicity using human 3D cardiac microtissues

Kofron

Kim

Munarin

et al. 2021

Sci Rep

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Cardiotoxicity of pharmaceutical drugs, industrial chemicals, and environmental toxicants can be severe, even life threatening, which necessitates a thorough evaluation of the human response to chemical compounds. Predicting risks for arrhythmia and sudden cardiac death accurately is critical for defining safety profiles. Currently available approaches have limitations including a focus on single select ion channels, the use of non-human species in vitro and in vivo, and limited direct physiological translation. We have advanced the robustness and reproducibility of in vitro platforms for assessing pro-arrhythmic cardiotoxicity using human induced pluripotent stem cell-derived cardiomyocytes and human cardiac fibroblasts in 3-dimensional microtissues. Using automated algorithms and statistical analyses of eight comprehensive evaluation metrics of cardiac action potentials, we demonstrate that tissue-engineered human cardiac microtissues respond appropriately to physiological stimuli and effectively differentiate between high-risk and low-risk compounds exhibiting blockade of the hERG channel (E4031 and ranolazine, respectively). Further, we show that the environmental endocrine disrupting chemical bisphenol-A (BPA) causes acute and sensitive disruption of human action potentials in the nanomolar range. Thus, this novel human 3D in vitro pro-arrhythmic risk assessment platform addresses critical needs in cardiotoxicity testing for both environmental and pharmaceutical compounds and can be leveraged to establish safe human exposure levels.

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Section: Discussionmentioning

confidence: 99%

A predictive in vitro risk assessment platform for pro-arrhythmic toxicity using human 3D cardiac microtissues

Kofron

Kim

Munarin

et al. 2021

Sci Rep

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“…Nonlinear parameters were calculated using an open-source algorithm based on phase space reconstruction (Hoang et al, 2018(Hoang et al, , 2019. Briefly, one-dimensional time-series data can be reconstructed into a multi-dimensional phase space that consists of a set of typical trajectories of the system, in which each point corresponds to one system state.…”

Section: Nonlinear Analysis Based On Phase Space Reconstructionmentioning

confidence: 99%

“…This software was coupled to correlation analysis and ensemble averaging techniques that successfully distinguished between normal field potentials and arrhythmogenic complexes from microelectrode array (MEA) recordings (Pradhapan et al, 2013). Concurrently, nonlinear analytical techniques have been shown to improve the sensitivity of hiPSC-based assays by detecting subtle abnormal aberrations from contractile function readouts in response to drug exposure (Hoang et al, 2018(Hoang et al, , 2019.…”

Section: Introductionmentioning

confidence: 99%

Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell‐based drug cardiotoxicity testing

Kowalczewski

Sakolish

Hoang

et al. 2022

J Tissue Eng Regen Med

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Utilizing recent advances in human induced pluripotent stem cell (hiPSC) technology, nonlinear analysis and machine learning we can create novel tools to evaluate drug-induced cardiotoxicity on human cardiomyocytes. With cardiovascular disease remaining the leading cause of death globally it has become imperative to create effective and modern tools to test the efficacy and toxicity of drugs to combat heart disease. The calcium transient signals recorded from hiPSC-derived cardiomyocytes (hiPSC-CMs) are highly complex and dynamic with great degrees of response characteristics to various drug treatments. However, traditional linear methods often fail to capture the subtle variation in these signals generated by hiPSC-CMs.In this work, we integrated nonlinear analysis, dimensionality reduction techniques and machine learning algorithms for better classifying the contractile signals from hiPSC-CMs in response to different drug exposure. By utilizing extracted parameters from a commercially available high-throughput testing platform, we were able to distinguish the groups with drug treatment from baseline controls, determine the drug exposure relative to IC50 values, and classify the drugs by its unique cardiac responses. By incorporating nonlinear parameters computed by phase space reconstruction, we were able to improve our machine learning algorithm's ability to predict cardiotoxic levels and drug classifications. We also visualized the effects of drug treatment and dosages with dimensionality reduction techniques, t-distributed stochastic neighbor embedding (t-SNE). We have shown that integration of nonlinear analysis and artificial intelligence has proven to be a powerful tool for analyzing cardiotoxicity and classifying toxic compounds through their mechanistic action.

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“…Brightfield videos of spontaneously beating cardiac tissues can be acquired and then be converted to beating profiles by means of different available software packages [ 105 , 107 , 132 , 133 , 134 ], allowing the analysis of different contractibility parameters such as beating frequency, amplitude and time of contraction, and relaxation time. The improvement of the analysis of the contractile profiles generated from the video acquisition system has also been focused upon, envisaging the maximization of the number of possible outcomes/parameters that can be extracted from the video records in an automated way [ 132 , 135 ]. Fluorescence-based methods have been used to collect calcium transient profiles through the use of calcium fluorescent dyes, such as Fura-2 [ 107 ] or Fluo-4 [ 105 , 133 ].…”

Section: In Vitro Applications Of Hpsc-derived 3d Cardiac Microtismentioning

confidence: 99%

From Human Pluripotent Stem Cells to 3D Cardiac Microtissues: Progress, Applications and Challenges

Branco

Diogo

2020

Bioengineering

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The knowledge acquired throughout the years concerning the in vivo regulation of cardiac development has promoted the establishment of directed differentiation protocols to obtain cardiomyocytes (CMs) and other cardiac cells from human pluripotent stem cells (hPSCs), which play a crucial role in the function and homeostasis of the heart. Among other developments in the field, the transition from homogeneous cultures of CMs to more complex multicellular cardiac microtissues (MTs) has increased the potential of these models for studying cardiac disorders in vitro and for clinically relevant applications such as drug screening and cardiotoxicity tests. This review addresses the state of the art of the generation of different cardiac cells from hPSCs and the impact of transitioning CM differentiation from 2D culture to a 3D environment. Additionally, current methods that may be employed to generate 3D cardiac MTs are reviewed and, finally, the adoption of these models for in vitro applications and their adaptation to medium- to high-throughput screening settings are also highlighted.

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Quantitatively characterizing drug‐induced arrhythmic contractile motions of human stem cell‐derived cardiomyocytes

Cited by 5 publications

References 33 publications

A predictive in vitro risk assessment platform for pro-arrhythmic toxicity using human 3D cardiac microtissues

A predictive in vitro risk assessment platform for pro-arrhythmic toxicity using human 3D cardiac microtissues

Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell‐based drug cardiotoxicity testing

From Human Pluripotent Stem Cells to 3D Cardiac Microtissues: Progress, Applications and Challenges

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