Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification

Lee, Eugene K.; Tran, David; Keung, Wendy; Chan, Phyllis; Wong, G.C.; Chan, Chun Man; Costa, Kevin D.; Tse, Gary; Khine, Michelle

doi:10.1016/j.stemcr.2017.09.008

Cited by 53 publications

(46 citation statements)

References 36 publications

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“…Animal studies for drug testing often mislead drug development processes due to genotypic and physiological differences between species . As a substitute for the current in vitro and in vivo models, several studies have suggested using 3D cardiac organoids as a new model system to check cardiac responses to drugs by demonstrating that the organoids enable evaluation of well‐known drugs, such as verapamil, isoproterenol, and metoprolol . For example, Agarwal et al.…”

Section: Current Progress In Organoid Technologiesmentioning

confidence: 99%

Organoids for Advanced Therapeutics and Disease Models

Kim

Cho

Min

et al. 2018

Advanced Therapeutics

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Organoid culture is a fast-emerging technology in the biological and biomedical research fields, garnering interest due to its unique features of self-organization from diverse types of stem cells and close resemblance to organs in the human body. This innovative in vitro model system presents the possibility of significant advances in the understanding of human development and disease mechanisms as well as in the discovery of novel diagnostics and therapeutics. Here, the authors review several types of tissue-specific organoids and discuss the most recent studies on the biomedical application of organoids. Finally, the challenges and prospects of organoids as an in vitro model system are laid out.

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Section: Current Progress In Organoid Technologiesmentioning

confidence: 99%

Organoids for Advanced Therapeutics and Disease Models

Kim

Cho

Min

et al. 2018

Advanced Therapeutics

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“…To overcome those limitations, small size EHT platforms have been described in the literature, including the Heart-Dyno platform [ 98 , 102 ], the Cardiac MicroRings (CaMiRi) [ 87 ] and the µTUG arrays [ 95 ]. Some platforms are now commercially available, such as in the case of the Biowire TM II platform (TARA Biosystems) [ 94 , 117 ] and the cardiac tissue strip model (Novoheart TM ) [ 127 , 128 ] (see Table 2 ).…”

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

confidence: 99%

“…The selected parameters should reflect relevant changes related to the pharmacological effects and preferentially allow the discrimination of different levels of toxicity severity and different types of toxic effects [ 138 , 139 ]. In addition to the development and selection of the best methodologies to capture and quantify the effects of cardioactive compounds on hPSC-CMs, the development of strategies that help in the identification and interpretation of the readouts in order to define which type of cardiotoxicity is associated with a specific compound and elucidate the mechanism of action is also a relevant topic that should be taken into consideration [ 128 ].…”

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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“…Approaches that incorporate the randomization of in silico parameters, non-linear modelling and chaos theory [63] together with the application of machine learning tools [64] and self-correcting parameterization [33] may lead to a better representation of 'real world' scenarios. Drug development will also benefit from input data acquired from a broader palette of studies performed in humans e.g.…”

Section: Defining the Physiological Gamut And Systems Limitsmentioning

confidence: 99%

Introduction to biological complexity as a missing link in drug discovery

Gintant

George

2018

Expert Opinion on Drug Discovery

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Despite a burgeoning knowledge of the intricacies and mechanisms responsible for human disease, technological advances in medicinal chemistry, and more efficient assays used for drug screening, it remains difficult to discover novel and effective pharmacologic therapies. Areas covered: By reference to the primary literature and concepts emerging from academic and industrial drug screening landscapes, the authors propose that this disconnect arises from the inability to scale and integrate responses from simpler model systems to outcomes from more complex and human-based biological systems. Expert opinion: Further collaborative efforts combining target-based and phenotypic-based screening along with systems-based pharmacology and informatics will be necessary to harness the technological breakthroughs of today to derive the novel drug candidates of tomorrow. New questions must be asked of enabling technologies-while recognizing inherent limitations-in a way that moves drug development forward. Attempts to integrate mechanistic and observational information acquired across multiple scales frequently expose the gap between our knowledge and our understanding as the level of complexity increases. We hope that the thoughts and actionable items highlighted will help to inform the directed evolution of the drug discovery process.

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Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification

Cited by 53 publications

References 36 publications

Organoids for Advanced Therapeutics and Disease Models

Organoids for Advanced Therapeutics and Disease Models

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

Introduction to biological complexity as a missing link in drug discovery

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