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Wang T, Du Z, Zhuo L, Fu X, Zou Q, Yao X. MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning. Int J Biol Macromol 2024; 276:133825. [PMID: 39002900 DOI: 10.1016/j.ijbiomac.2024.133825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Revised: 07/09/2024] [Accepted: 07/10/2024] [Indexed: 07/15/2024]
Abstract
Predicting compound-induced inhibition of cardiac ion channels is crucial and challenging, significantly impacting cardiac drug efficacy and safety assessments. Despite the development of various computational methods for compound-induced inhibition prediction in cardiac ion channels, their performance remains limited. Most methods struggle to fuse multi-source data, relying solely on specific dataset training, leading to poor accuracy and generalization. We introduce MultiCBlo, a model that fuses multimodal information through a progressive learning approach, designed to predict compound-induced inhibition of cardiac ion channels with high accuracy. MultiCBlo employs progressive multimodal information fusion technology to integrate the compound's SMILES sequence, graph structure, and fingerprint, enhancing its representation. This is the first application of progressive multimodal learning for predicting compound-induced inhibition of cardiac ion channels, to our knowledge. The objective of this study was to predict the compound-induced inhibition of three major cardiac ion channels: hERG, Cav1.2, and Nav1.5. The results indicate that MultiCBlo significantly outperforms current models in predicting compound-induced inhibition of cardiac ion channels. We hope that MultiCBlo will facilitate cardiac drug development and reduce compound toxicity risks. Code and data are accessible at: https://github.com/taowang11/MultiCBlo. The online prediction platform is freely accessible at: https://huggingface.co/spaces/wtttt/PCICB.
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Affiliation(s)
- Tao Wang
- School of Data Science and Artificial Intelligence, Wenzhou University of Technology, 325027 Wenzhou, China
| | - Zhenya Du
- Guangzhou Xinhua University, 510520 Guangzhou, China
| | - Linlin Zhuo
- School of Data Science and Artificial Intelligence, Wenzhou University of Technology, 325027 Wenzhou, China.
| | - Xiangzheng Fu
- College of Computer Science and Electronic Engineering, Hunan University, 410012 Changsha, China.
| | - Quan Zou
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 611730 Chengdu, China
| | - Xiaojun Yao
- Faculty of Applied Sciences, Macao Polytechnic University, 999078 Macao, China.
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2
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Brennan S, Chen S, Makwana S, Esposito S, McGuinness LR, Alnaimi AIM, Sims MW, Patel M, Aziz Q, Ojake L, Roberts JA, Sharma P, Lodwick D, Tinker A, Barrett-Jolley R, Dart C, Rainbow RD. Identification and characterisation of functional K ir6.1-containing ATP-sensitive potassium channels in the cardiac ventricular sarcolemmal membrane. Br J Pharmacol 2024; 181:3380-3400. [PMID: 38763521 DOI: 10.1111/bph.16390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/21/2024] [Accepted: 03/18/2024] [Indexed: 05/21/2024] Open
Abstract
BACKGROUND AND PURPOSE The canonical Kir6.2/SUR2A ventricular KATP channel is highly ATP-sensitive and remains closed under normal physiological conditions. These channels activate only when prolonged metabolic compromise causes significant ATP depletion and then shortens the action potential to reduce contractile activity. Pharmacological activation of KATP channels is cardioprotective, but physiologically, it is difficult to understand how these channels protect the heart if they only open under extreme metabolic stress. The presence of a second KATP channel population could help explain this. Here, we characterise the biophysical and pharmacological behaviours of a constitutively active Kir6.1-containing KATP channel in ventricular cardiomyocytes. EXPERIMENTAL APPROACH Patch-clamp recordings from rat ventricular myocytes in combination with well-defined pharmacological modulators was used to characterise these newly identified K+ channels. Action potential recording, calcium (Fluo-4) fluorescence measurements and video edge detection of contractile function were used to assess functional consequences of channel modulation. KEY RESULTS Our data show a ventricular K+ conductance whose biophysical characteristics and response to pharmacological modulation were consistent with Kir6.1-containing channels. These Kir6.1-containing channels lack the ATP-sensitivity of the canonical channels and are constitutively active. CONCLUSION AND IMPLICATIONS We conclude there are two functionally distinct populations of ventricular KATP channels: constitutively active Kir6.1-containing channels that play an important role in fine-tuning the action potential and Kir6.2/SUR2A channels that activate with prolonged ischaemia to impart late-stage protection against catastrophic ATP depletion. Further research is required to determine whether Kir6.1 is an overlooked target in Comprehensive in vitro Proarrhythmia Assay (CiPA) cardiac safety screens.
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Affiliation(s)
- Sean Brennan
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
| | - Shen Chen
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Samir Makwana
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Simona Esposito
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Lauren R McGuinness
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
| | - Abrar I M Alnaimi
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
- Department of Cardiac Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Mark W Sims
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Manish Patel
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Qadeer Aziz
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Leona Ojake
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - James A Roberts
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
| | - Parveen Sharma
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
| | - David Lodwick
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Andrew Tinker
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Richard Barrett-Jolley
- Department of Musculoskeletal and Ageing Science, University of Liverpool, Liverpool, UK
| | - Caroline Dart
- Department of Biochemistry, Cell and Systems Biology, University of Liverpool, Liverpool, UK
| | - Richard D Rainbow
- Department of Cardiovascular and Metabolic Medicine and Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool, UK
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Escobar F, Friis S, Adly N, Brinkwirth N, Gomis-Tena J, Saiz J, Klaerke DA, Stoelzle-Feix S, Romero L. Experimentally validated modeling of dynamic drug-hERG channel interactions reproducing the binding mechanisms and its importance in action potential duration. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 254:108293. [PMID: 38936153 DOI: 10.1016/j.cmpb.2024.108293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 06/09/2024] [Accepted: 06/16/2024] [Indexed: 06/29/2024]
Abstract
BACKGROUND AND OBJECTIVE Assessment of drug cardiotoxicity is critical in the development of new compounds and modeling of drug-binding dynamics to hERG can improve early cardiotoxicity assessment. We previously developed a methodology to generate Markovian models reproducing preferential state-dependent binding properties, trapping dynamics and the onset of IKr block using simple voltage clamp protocols. Here, we test this methodology with real IKr blockers and investigate the impact of drug dynamics on action potential prolongation. METHODS Experiments were performed on HEK cells stably transfected with hERG and using the Nanion SyncroPatch 384i. Three protocols, P-80, P0 and P 40, were applied to obtain the experimental data from the drugs and the Markovian models were generated using our pipeline. The corresponding static models were also generated and a modified version of the O´Hara-Rudy action potential model was used to simulate the action potential duration. RESULTS The experimental Hill plots and the onset of IKr block of ten compounds were obtained using our voltage clamp protocols and the models generated successfully mimicked these experimental data, unlike the CiPA dynamic models. Marked differences in APD prolongation were observed when drug effects were simulated using the dynamic models and the static models. CONCLUSIONS These new dynamic models of ten well-known IKr blockers constitute a validation of our methodology to model dynamic drug-hERG channel interactions and highlight the importance of state-dependent binding, trapping dynamics and the time-course of IKr block to assess drug effects even at the steady-state.
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Affiliation(s)
- Fernando Escobar
- Centro de Innovación e Investigación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | | | | | | | - Julio Gomis-Tena
- Centro de Innovación e Investigación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Javier Saiz
- Centro de Innovación e Investigación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain
| | - Dan A Klaerke
- Department of Pathobiology, University of Copenhagen, Copenhagen, Denmark
| | | | - Lucia Romero
- Centro de Innovación e Investigación en Bioingeniería, Universitat Politècnica de València, Valencia, Spain.
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Naumenko N, Koivumäki JT, Lunko O, Tuomainen T, Leigh R, Rabiee M, Laurila J, Oksanen M, Lehtonen S, Koistinaho J, Tavi P. Presenilin-1 ΔE9 mutation associated sarcoplasmic reticulum leak alters [Ca 2+] i distribution in human iPSC-derived cardiomyocytes. J Mol Cell Cardiol 2024; 193:78-87. [PMID: 38851626 DOI: 10.1016/j.yjmcc.2024.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 05/28/2024] [Accepted: 06/04/2024] [Indexed: 06/10/2024]
Abstract
Mutations in ubiquitously expressed presenilin genes (PSENs) lead to early-onset familial Alzheimer's disease (FAD), but patients carrying the mutation also suffer from heart diseases. To elucidate the cardiac myocyte specific effects of PSEN ΔE9, we studied cardiomyocytes derived from induced pluripotent stem cells (iPSC-CMs) from patients carrying AD-causing PSEN1 exon 9 deletion (PSEN1 ΔE9). When compared with their isogenic controls, PSEN1 ΔE9 cardiomyocytes showed increased sarcoplasmic reticulum (SR) Ca2+ leak that was resistant to blockage of ryanodine receptors (RyRs) by tetracaine or inositol-3-reseceptors (IP3Rs) by 2-ABP. The SR Ca2+ leak did not affect electrophysiological properties of the hiPSC-CMs, but according to experiments and in silico simulations the leak induces a diastolic buildup of [Ca2+] near the perinuclear SR and reduces the releasable Ca2+ during systole. This demonstrates that PSEN1 ΔE9 induced SR Ca2+ leak has specific effects in iPSC-CMs, reflecting their unique structural and calcium signaling features. The results shed light on the physiological and pathological mechanisms of PSEN1 in cardiac myocytes and explain the intricacies of comorbidity associated with AD-causing mutations in PSEN1.
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Affiliation(s)
- Nikolay Naumenko
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jussi T Koivumäki
- BioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olesia Lunko
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Tomi Tuomainen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Robert Leigh
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mina Rabiee
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jalmari Laurila
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Minna Oksanen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Sarka Lehtonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Jari Koistinaho
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Pasi Tavi
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
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5
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Trayanova NA, Lyon A, Shade J, Heijman J. Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation. Physiol Rev 2024; 104:1265-1333. [PMID: 38153307 DOI: 10.1152/physrev.00017.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 12/29/2023] Open
Abstract
The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.
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Affiliation(s)
- Natalia A Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Aurore Lyon
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of Heart and Lungs, Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Julie Shade
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Jordi Heijman
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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6
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Boulay E, Troncy E, Jacquemet V, Huang H, Pugsley MK, Downey AM, Venegas Baca R, Authier S. In Silico Human Cardiomyocyte Action Potential Modeling: Exploring Ion Channel Input Combinations. Int J Toxicol 2024; 43:357-367. [PMID: 38477622 DOI: 10.1177/10915818241237988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024]
Abstract
In silico modeling offers an opportunity to supplement and accelerate cardiac safety testing. With in silico modeling, computational simulation methods are used to predict electrophysiological interactions and pharmacological effects of novel drugs on critical physiological processes. The O'Hara-Rudy's model was developed to predict the response to different ion channel inhibition levels on cardiac action potential duration (APD) which is known to directly correlate with the QT interval. APD data at 30% 60% and 90% inhibition were derived from the model to delineate possible ventricular arrhythmia scenarios and the marginal contribution of each ion channel to the model. Action potential values were calculated for epicardial, myocardial, and endocardial cells, with action potential curve modeling. This study assessed cardiac ion channel inhibition data combinations to consider when undertaking in silico modeling of proarrhythmic effects as stipulated in the Comprehensive in Vitro Proarrhythmia Assay (CiPA). As expected, our data highlight the importance of the delayed rectifier potassium channel (IKr) as the most impactful channel for APD prolongation. The impact of the transient outward potassium channel (Ito) inhibition on APD was minimal while the inward rectifier (IK1) and slow component of the delayed rectifier potassium channel (IKs) also had limited APD effects. In contrast, the contribution of fast sodium channel (INa) and/or L-type calcium channel (ICa) inhibition resulted in substantial APD alterations supporting the pharmacological relevance of in silico modeling using input from a limited number of cardiac ion channels including IKr, INa, and ICa, at least at an early stage of drug development.
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Affiliation(s)
- Emmanuel Boulay
- GREPAQ (Groupe de Recherche en Pharmacologie Animale du Québec), Université de Montréal, Saint-Hyacinthe, QC, Canada
- Charles River Laboratories, Laval, QC, Canada
| | - Eric Troncy
- GREPAQ (Groupe de Recherche en Pharmacologie Animale du Québec), Université de Montréal, Saint-Hyacinthe, QC, Canada
| | - Vincent Jacquemet
- Département de Pharmacologie et Physiologie, Université de Montréal, Faculté de Médecine, Montréal, QC, Canada
- Centre de Recherche, Hôpital du Sacré-Cœur, Montréal, QC, Canada
- Institut de Génie Biomédical, Université de Montréal, Montréal, QC, Canada
| | - Hai Huang
- Charles River Laboratories, Laval, QC, Canada
| | - Michael K Pugsley
- Toxicology & Safety Pharmacology, Cytokinetics, San Francisco, CA, USA
| | | | | | - Simon Authier
- GREPAQ (Groupe de Recherche en Pharmacologie Animale du Québec), Université de Montréal, Saint-Hyacinthe, QC, Canada
- Charles River Laboratories, Laval, QC, Canada
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7
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Zhang Y, Toyoda F, Himeno Y, Noma A, Amano A. Cell-specific models of hiPSC-CMs developed by the gradient-based parameter optimization method fitting two different action potential waveforms. Sci Rep 2024; 14:13086. [PMID: 38849433 PMCID: PMC11161598 DOI: 10.1038/s41598-024-63413-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 05/28/2024] [Indexed: 06/09/2024] Open
Abstract
Parameter optimization (PO) methods to determine the ionic current composition of experimental cardiac action potential (AP) waveform have been developed using a computer model of cardiac membrane excitation. However, it was suggested that fitting a single AP record in the PO method was not always successful in providing a unique answer because of a shortage of information. We found that the PO method worked perfectly if the PO method was applied to a pair of a control AP and a model output AP in which a single ionic current out of six current species, such as IKr, ICaL, INa, IKs, IKur or IbNSC was partially blocked in silico. When the target was replaced by a pair of experimental control and IKr-blocked records of APs generated spontaneously in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), the simultaneous fitting of the two waveforms by the PO method was hampered to some extent by the irregular slow fluctuations in the Vm recording and/or sporadic alteration in AP configurations in the hiPSC-CMs. This technical problem was largely removed by selecting stable segments of the records for the PO method. Moreover, the PO method was made fail-proof by running iteratively in identifying the optimized parameter set to reconstruct both the control and the IKr-blocked AP waveforms. In the lead potential analysis, the quantitative ionic mechanisms deduced from the optimized parameter set were totally consistent with the qualitative view of ionic mechanisms of AP so far described in physiological literature.
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Affiliation(s)
- Yixin Zhang
- Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Futoshi Toyoda
- Department of Physiology, Shiga University of Medical Science, Otsu, Japan
- Central Research Laboratory, Shiga University of Medical Science, Otsu, Japan
| | - Yukiko Himeno
- Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan.
- Department of Physiology, Shiga University of Medical Science, Otsu, Japan.
| | - Akinori Noma
- Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Akira Amano
- Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
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8
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Qauli AI, Danadibrata RZ, Marcellinus A, Lim KM. Development of in-silico drug cardiac toxicity evaluation system with consideration of inter-individual variability. Transl Clin Pharmacol 2024; 32:83-97. [PMID: 38974343 PMCID: PMC11224897 DOI: 10.12793/tcp.2024.32.e7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 04/30/2024] [Accepted: 05/26/2024] [Indexed: 07/09/2024] Open
Abstract
Safety pharmacology examines the potential for new drugs to have unusual, rare side effects such as torsade de pointes (TdP). Recently, as a part of the Comprehensive in vitro Proarrhythmia Assay (CiPA) project, techniques for predicting the development of drug-induced TdP through computer simulations have been proposed and verified. However, CiPA assessment generally does not consider the effect of cardiac cell inter-individual variability, especially related to metabolic status. The study aimed to explore whether rare proarrhythmic effects may be linked to the inter-individual variability of cardiac cells and whether incorporating this variability into computational models could alter the prediction of drugs' TdP risks. This study evaluated the contribution of two biological characteristics to the proarrhythmic effects. The first was spermine concentration, which varies with metabolic status; the second was L-type calcium permeability that could occur due to mutations. Twenty-eight drugs were examined throughout this study, and qNet was analyzed as an essential feature. Even though there were some discrepancies of TdP risk predictions from the baseline model, we found that considering the inter-individual variability might change the TdP risk of drugs. Several drugs in the high-risk drugs group were predicted to affect as intermediate and low-risk drugs in some individuals and vice versa. Also, most intermediate-risk drugs were expected to act as low-risk drugs. When compared, the effects of inter-individual variability of L-type calcium were more significant than spermine in altering the TdP risk of compounds. These results emphasize the importance of considering inter-individual variability to assess drugs.
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Affiliation(s)
- Ali Ikhsanul Qauli
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
- Department of Engineering, Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya 60115, Indonesia
| | | | - Aroli Marcellinus
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
| | - Ki Moo Lim
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
- Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea
- Meta Heart Inc., Gumi 39177, Korea
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9
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Grandits T, Augustin CM, Haase G, Jost N, Mirams GR, Niederer SA, Plank G, Varró A, Virág L, Jung A. Neural network emulation of the human ventricular cardiomyocyte action potential for more efficient computations in pharmacological studies. eLife 2024; 12:RP91911. [PMID: 38598284 PMCID: PMC11006416 DOI: 10.7554/elife.91911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024] Open
Abstract
Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.
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Affiliation(s)
- Thomas Grandits
- Department of Mathematics and Scientific Computing, University of GrazGrazAustria
- NAWI Graz, University of GrazGrazAustria
| | - Christoph M Augustin
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Medical Physics and Biophysics, Medical University of GrazGrazAustria
- BioTechMed-GrazGrazAustria
| | - Gundolf Haase
- Department of Mathematics and Scientific Computing, University of GrazGrazAustria
| | - Norbert Jost
- Department of Pharmacology and Pharmacotherapy, University of SzegedSzegedHungary
- HUN-REN-TKI, Research Group of PharmacologyBudapestHungary
| | - Gary R Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of NottinghamNottinghamUnited Kingdom
| | - Steven A Niederer
- Division of Imaging Sciences & Biomedical Engineering, King’s College LondonLondonUnited Kingdom
| | - Gernot Plank
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Medical Physics and Biophysics, Medical University of GrazGrazAustria
- BioTechMed-GrazGrazAustria
| | - András Varró
- Department of Pharmacology and Pharmacotherapy, University of SzegedSzegedHungary
- HUN-REN-TKI, Research Group of PharmacologyBudapestHungary
| | - László Virág
- Department of Pharmacology and Pharmacotherapy, University of SzegedSzegedHungary
| | - Alexander Jung
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Medical Physics and Biophysics, Medical University of GrazGrazAustria
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10
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Mahardika T NQ, Qauli AI, Marcellinus A, Lim KM. Evaluation of cardiac pro-arrhythmic risks using the artificial neural network with ToR-ORd in silico model output. Front Physiol 2024; 15:1374355. [PMID: 38638275 PMCID: PMC11024991 DOI: 10.3389/fphys.2024.1374355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/04/2024] [Indexed: 04/20/2024] Open
Abstract
Torsades de pointes (TdP) is a type of ventricular arrhythmia that can lead to sudden cardiac death. Drug-induced TdP has been an important concern for researchers and international regulatory boards. The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative was proposed that integrates in vitro testing and computational models of cardiac ion channels and human cardiomyocyte cells to evaluate the proarrhythmic risk of drugs. The TdP risk classification performance using only a single TdP metric may require some improvements because of information limitations and the instability of generalizing results. This study evaluates the performance of TdP metrics from the in silico simulations of the Tomek-O'Hara Rudy (ToR-ORd) ventricular cell model for classifying the TdP risk of drugs. We utilized these metrics as an input to an artificial neural network (ANN)-based classifier. The ANN model was optimized through hyperparameter tuning using the grid search (GS) method to find the optimal model. The study outcomes show an area under the curve (AUC) value of 0.979 for the high-risk category, 0.791 for the intermediate-risk category, and 0.937 for the low-risk category. Therefore, this study successfully demonstrates the capability of the ToR-ORd ventricular cell model in classifying the TdP risk into three risk categories, providing new insights into TdP risk prediction methods.
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Affiliation(s)
- Nurul Qashri Mahardika T
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
| | - Ali Ikhsanul Qauli
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- Department of Engineering, Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya, Jawa Timur, Indonesia
| | - Aroli Marcellinus
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
| | - Ki Moo Lim
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- Computational Medicine Lab, Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- Meta Heart Co Ltd., Gumi, Republic of Korea
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11
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Lei CL, Whittaker DG, Mirams GR. The impact of uncertainty in hERG binding mechanism on in silico predictions of drug-induced proarrhythmic risk. Br J Pharmacol 2024; 181:987-1004. [PMID: 37740435 DOI: 10.1111/bph.16250] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/23/2023] [Accepted: 08/28/2023] [Indexed: 09/24/2023] Open
Abstract
BACKGROUND AND PURPOSE Drug-induced reduction of the rapid delayed rectifier potassium current carried by the human Ether-à-go-go-Related Gene (hERG) channel is associated with increased risk of arrhythmias. Recent updates to drug safety regulatory guidelines attempt to capture each drug's hERG binding mechanism by combining in vitro assays with in silico simulations. In this study, we investigate the impact on in silico proarrhythmic risk predictions due to uncertainty in the hERG binding mechanism and physiological hERG current model. EXPERIMENTAL APPROACH Possible pharmacological binding models were designed for the hERG channel to account for known and postulated small molecule binding mechanisms. After selecting a subset of plausible binding models for each compound through calibration to available voltage-clamp electrophysiology data, we assessed their effects, and the effects of different physiological models, on proarrhythmic risk predictions. KEY RESULTS For some compounds, multiple binding mechanisms can explain the same data produced under the safety testing guidelines, which results in different inferred binding rates. This can result in substantial uncertainty in the predicted torsade risk, which often spans more than one risk category. By comparison, we found that the effect of a different hERG physiological current model on risk classification was subtle. CONCLUSION AND IMPLICATIONS The approach developed in this study assesses the impact of uncertainty in hERG binding mechanisms on predictions of drug-induced proarrhythmic risk. For some compounds, these results imply the need for additional binding data to decrease uncertainty in safety-critical applications.
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Affiliation(s)
- Chon Lok Lei
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
- Department of Biomedical Sciences, Faculty of Health Sciences, University of Macau, Macau, China
| | - Dominic G Whittaker
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, UK
| | - Gary R Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, UK
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12
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Aguado-Sierra J, Dominguez-Gomez P, Amar A, Butakoff C, Leitner M, Schaper S, Kriegl JM, Darpo B, Vazquez M, Rast G. Virtual clinical QT exposure-response studies - A translational computational approach. J Pharmacol Toxicol Methods 2024; 126:107498. [PMID: 38432528 DOI: 10.1016/j.vascn.2024.107498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 12/13/2023] [Accepted: 02/29/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND AND PURPOSE A recent paradigm shift in proarrhythmic risk assessment suggests that the integration of clinical, non-clinical, and computational evidence can be used to reach a comprehensive understanding of the proarrhythmic potential of drug candidates. While current computational methodologies focus on predicting the incidence of proarrhythmic events after drug administration, the objective of this study is to predict concentration-response relationships of QTc as a clinical endpoint. EXPERIMENTAL APPROACH Full heart computational models reproducing human cardiac populations were created to predict the concentration-response relationship of changes in the QT interval as recommended for clinical trials. The concentration-response relationship of the QT-interval prolongation obtained from the computational cardiac population was compared against the relationship from clinical trial data for a set of well-characterized compounds: moxifloxacin, dofetilide, verapamil, and ondansetron. KEY RESULTS Computationally derived concentration-response relationships of QT interval changes for three of the four drugs had slopes within the confidence interval of clinical trials (dofetilide, moxifloxacin and verapamil) when compared to placebo-corrected concentration-ΔQT and concentration-ΔQT regressions. Moxifloxacin showed a higher intercept, outside the confidence interval of the clinical data, demonstrating that in this example, the standard linear regression does not appropriately capture the concentration-response results at very low concentrations. The concentrations corresponding to a mean QTc prolongation of 10 ms were consistently lower in the computational model than in clinical data. The critical concentration varied within an approximate ratio of 0.5 (moxifloxacin and ondansetron) and 1 times (dofetilide, verapamil) the critical concentration observed in human clinical trials. Notably, no other in silico methodology can approximate the human critical concentration values for a QT interval prolongation of 10 ms. CONCLUSION AND IMPLICATIONS Computational concentration-response modelling of a virtual population of high-resolution, 3-dimensional cardiac models can provide comparable information to clinical data and could be used to complement pre-clinical and clinical safety packages. It provides access to an unlimited exposure range to support trial design and can improve the understanding of pre-clinical-clinical translation.
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Affiliation(s)
- Jazmin Aguado-Sierra
- Elem Biotech, Barcelona, Spain; Barcelona Supercomputing Center, Barcelona, Spain.
| | | | | | | | - Michael Leitner
- Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach, Germany.
| | - Stefan Schaper
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach, Germany.
| | - Jan M Kriegl
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach, Germany.
| | | | - Mariano Vazquez
- Elem Biotech, Barcelona, Spain; Barcelona Supercomputing Center, Barcelona, Spain.
| | - Georg Rast
- Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH and Co. KG, Biberach, Germany.
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13
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Abrasheva VO, Kovalenko SG, Slotvitsky M, Romanova SА, Aitova AA, Frolova S, Tsvelaya V, Syunyaev RA. Human sodium current voltage-dependence at physiological temperature measured by coupling a patch-clamp experiment to a mathematical model. J Physiol 2024; 602:633-661. [PMID: 38345560 DOI: 10.1113/jp285162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 01/02/2024] [Indexed: 02/20/2024] Open
Abstract
Voltage-gated Na+ channels are crucial to action potential propagation in excitable tissues. Because of the high amplitude and rapid activation of the Na+ current, voltage-clamp measurements are very challenging and are usually performed at room temperature. In this study, we measured Na+ current voltage-dependence in stem cell-derived cardiomyocytes at physiological temperature. While the apparent activation and inactivation curves, measured as the dependence of current amplitude on voltage, fall within the range reported in previous studies, we identified a systematic error in our measurements. This error is caused by the deviation of the membrane potential from the command potential of the amplifier. We demonstrate that it is possible to account for this artifact using computer simulation of the patch-clamp experiment. We obtained surprising results through patch-clamp model optimization: a half-activation of -11.5 mV and a half-inactivation of -87 mV. Although the half-activation deviates from previous research, we demonstrate that this estimate reproduces the conduction velocity dependence on extracellular potassium concentration. KEY POINTS: Voltage-gated Na+ currents play a crucial role in excitable tissues including neurons, cardiac and skeletal muscle. Measurement of Na+ current is challenging because of its high amplitude and rapid kinetics, especially at physiological temperature. We have used the patch-clamp technique to measure human Na+ current voltage-dependence in human induced pluripotent stem cell-derived cardiomyocytes. The patch-clamp data were processed by optimization of the model accounting for voltage-clamp experiment artifacts, revealing a large difference between apparent parameters of Na+ current and the results of the optimization. We conclude that actual Na+ current activation is extremely depolarized in comparison to previous studies. The new Na+ current model provides a better understanding of action potential propagation; we demonstrate that it explains propagation in hyperkalaemic conditions.
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Affiliation(s)
| | - Sandaara G Kovalenko
- Moscow Institute of Physics and Technology, Moscow, Russia
- M. F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, Russia
- ITMO University, St Petersburg, Russia
| | - Mihail Slotvitsky
- Moscow Institute of Physics and Technology, Moscow, Russia
- M. F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, Russia
- ITMO University, St Petersburg, Russia
| | - Serafima А Romanova
- Moscow Institute of Physics and Technology, Moscow, Russia
- M. F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, Russia
| | - Aleria A Aitova
- Moscow Institute of Physics and Technology, Moscow, Russia
- M. F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, Russia
- ITMO University, St Petersburg, Russia
| | - Sheida Frolova
- Moscow Institute of Physics and Technology, Moscow, Russia
- M. F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, Russia
| | - Valeria Tsvelaya
- Moscow Institute of Physics and Technology, Moscow, Russia
- M. F. Vladimirsky Moscow Regional Research Clinical Institute, Moscow, Russia
- ITMO University, St Petersburg, Russia
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14
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Heitmann S, Vandenberg JI, Hill AP. Assessing drug safety by identifying the axis of arrhythmia in cardiomyocyte electrophysiology. eLife 2023; 12:RP90027. [PMID: 38079357 PMCID: PMC10712948 DOI: 10.7554/elife.90027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023] Open
Abstract
Many classes of drugs can induce fatal cardiac arrhythmias by disrupting the electrophysiology of cardiomyocytes. Safety guidelines thus require all new drugs to be assessed for pro-arrhythmic risk prior to conducting human trials. The standard safety protocols primarily focus on drug blockade of the delayed-rectifier potassium current (IKr). Yet the risk is better assessed using four key ion currents (IKr, ICaL, INaL, IKs). We simulated 100,000 phenotypically diverse cardiomyocytes to identify the underlying relationship between the blockade of those currents and the emergence of ectopic beats in the action potential. We call that relationship the axis of arrhythmia. It serves as a yardstick for quantifying the arrhythmogenic risk of any drug from its profile of multi-channel block alone. We tested it on 109 drugs and found that it predicted the clinical risk labels with an accuracy of 88.1-90.8%. Pharmacologists can use our method to assess the safety of novel drugs without resorting to animal testing or unwieldy computer simulations.
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Affiliation(s)
| | - Jamie I Vandenberg
- Victor Chang Cardiac Research InstituteDarlinghurstAustralia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South WalesSydneyAustralia
| | - Adam P Hill
- Victor Chang Cardiac Research InstituteDarlinghurstAustralia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South WalesSydneyAustralia
- Victor Chang Cardiac Research Institute Innovation CentreDarlinghurstAustralia
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15
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Fuadah YN, Qauli AI, Marcellinus A, Pramudito MA, Lim KM. Machine learning approach to evaluate TdP risk of drugs using cardiac electrophysiological model including inter-individual variability. Front Physiol 2023; 14:1266084. [PMID: 37860622 PMCID: PMC10584148 DOI: 10.3389/fphys.2023.1266084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/20/2023] [Indexed: 10/21/2023] Open
Abstract
Introduction: Predicting ventricular arrhythmia Torsade de Pointes (TdP) caused by drug-induced cardiotoxicity is essential in drug development. Several studies used single biomarkers such as qNet and Repolarization Abnormality (RA) in a single cardiac cell model to evaluate TdP risk. However, a single biomarker may not encompass the full range of factors contributing to TdP risk, leading to divergent TdP risk prediction outcomes, mainly when evaluated using unseen data. We addressed this issue by utilizing multi-in silico features from a population of human ventricular cell models that could capture a representation of the underlying mechanisms contributing to TdP risk to provide a more reliable assessment of drug-induced cardiotoxicity. Method: We generated a virtual population of human ventricular cell models using a modified O'Hara-Rudy model, allowing inter-individual variation. IC 50 and Hill coefficients from 67 drugs were used as input to simulate drug effects on cardiac cells. Fourteen features (dVm dt repol , dVm dt max , Vm peak , Vm resting , APD tri , APD 90 , APD 50 , Ca peak , Ca diastole , Ca tri , CaD 90 , CaD 50 , qNet, qInward) could be generated from the simulation and used as input to several machine learning models, including k-nearest neighbor (KNN), Random Forest (RF), XGBoost, and Artificial Neural Networks (ANN). Optimization of the machine learning model was performed using a grid search to select the best parameter of the proposed model. We applied five-fold cross-validation while training the model with 42 drugs and evaluated the model's performance with test data from 25 drugs. Result: The proposed ANN model showed the highest performance in predicting the TdP risk of drugs by providing an accuracy of 0.923 (0.908-0.937), sensitivity of 0.926 (0.909-0.942), specificity of 0.921 (0.906-0.935), and AUC score of 0.964 (0.954-0.975). Discussion and conclusion: According to the performance results, combining the electrophysiological model including inter-individual variation and optimization of machine learning showed good generalization ability when evaluated using the unseen dataset and produced a reliable drug-induced TdP risk prediction system.
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Affiliation(s)
- Yunendah Nur Fuadah
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- School of Electrical Engineering, Telkom University, Bandung, Indonesia
| | - Ali Ikhsanul Qauli
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- Department of Engineering, Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya, Jawa Timur, Indonesia
| | - Aroli Marcellinus
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
| | - Muhammad Adnan Pramudito
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
| | - Ki Moo Lim
- Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- Computational Medicine Lab, Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
- Meta Heart Co., Ltd., Gumi, Republic of Korea
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16
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Lei CL, Clerx M, Gavaghan DJ, Mirams GR. Model-driven optimal experimental design for calibrating cardiac electrophysiology models. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 240:107690. [PMID: 37478675 DOI: 10.1016/j.cmpb.2023.107690] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 06/09/2023] [Accepted: 06/22/2023] [Indexed: 07/23/2023]
Abstract
BACKGROUND AND OBJECTIVE Models of the cardiomyocyte action potential have contributed immensely to the understanding of heart function, pathophysiology, and the origin of heart rhythm disturbances. However, action potential models are highly nonlinear, making them difficult to parameterise and limiting to describing 'average cell' dynamics, when cell-specific models would be ideal to uncover inter-cell variability but are too experimentally challenging to be achieved. Here, we focus on automatically designing experimental protocols that allow us to better identify cell-specific maximum conductance values for each major current type. METHODS AND RESULTS We developed an approach that applies optimal experimental designs to patch-clamp experiments, including both voltage-clamp and current-clamp experiments. We assessed the models calibrated to these new optimal designs by comparing them to the models calibrated to some of the commonly used designs in the literature. We showed that optimal designs are not only overall shorter in duration but also able to perform better than many of the existing experiment designs in terms of identifying model parameters and hence model predictive power. CONCLUSIONS For cardiac cellular electrophysiology, this approach will allow researchers to define their hypothesis of the dynamics of the system and automatically design experimental protocols that will result in theoretically optimal designs.
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Affiliation(s)
- Chon Lok Lei
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China; Department of Biomedical Sciences, Faculty of Health Sciences, University of Macau, Macau, China.
| | - Michael Clerx
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - David J Gavaghan
- Department of Computer Science, University of Oxford, Oxford, United Kingdom; Doctoral Training Centre, University of Oxford, Oxford, United Kingdom
| | - Gary R Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom.
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17
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Yoon SH, Lee HL, Jeong DU, Lim KM, Park SJ, Kim KS. Assessment of the proarrhythmic effects of repurposed antimalarials for COVID-19 treatment using a comprehensive in vitro proarrhythmia assay (CiPA). Front Pharmacol 2023; 14:1220796. [PMID: 37649890 PMCID: PMC10464612 DOI: 10.3389/fphar.2023.1220796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 08/07/2023] [Indexed: 09/01/2023] Open
Abstract
Due to the outbreak of the SARS-CoV-2 virus, drug repurposing and Emergency Use Authorization have been proposed to treat the coronavirus disease 2019 (COVID-19) during the pandemic. While the efficiency of the drugs has been discussed, it was identified that certain compounds, such as chloroquine and hydroxychloroquine, cause QT interval prolongation and potential cardiotoxic effects. Drug-induced cardiotoxicity and QT prolongation may lead to life-threatening arrhythmias such as torsades de pointes (TdP), a potentially fatal arrhythmic symptom. Here, we evaluated the risk of repurposed pyronaridine or artesunate-mediated cardiac arrhythmias alone and in combination for COVID-19 treatment through in vitro and in silico investigations using the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative. The potential effects of each drug or in combinations on cardiac action potential (AP) and ion channels were explored using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and Chinese hamster ovary (CHO) cells transiently expressing cardiac ion channels (Nav1.5, Cav1.2, and hERG). We also performed in silico computer simulation using the optimized O'Hara-Rudy human ventricular myocyte model (ORd model) to classify TdP risk. Artesunate and dihydroartemisinin (DHA), the active metabolite of artesunate, are classified as a low risk of inducing TdP based on the torsade metric score (TMS). Moreover, artesunate does not significantly affect the cardiac APs of hiPSC-CMs even at concentrations up to 100 times the maximum serum concentration (Cmax). DHA modestly prolonged at APD90 (10.16%) at 100 times the Cmax. When considering Cmax, pyronaridine, and the combination of both drugs (pyronaridine and artesunate) are classified as having an intermediate risk of inducing TdP. However, when considering the unbound concentration (the free fraction not bound to carrier proteins or other tissues inducing pharmacological activity), both drugs are classified as having a low risk of inducing TdP. In summary, pyronaridine, artesunate, and a combination of both drugs have been confirmed to pose a low proarrhythmogenic risk at therapeutic and supratherapeutic (up to 4 times) free Cmax. Additionally, the CiPA initiative may be suitable for regulatory use and provide novel insights for evaluating drug-induced cardiotoxicity.
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Affiliation(s)
- Seung-Hyun Yoon
- R&D Center for Advanced Pharmaceuticals and Evaluation, Korea Institute of Toxicology, Daejeon, Republic of Korea
- College of Veterinary Medicine, Research Institute of Veterinary Medicine, Chungnam National University, Daejeon, Republic of Korea
| | - Hyun-Lee Lee
- R&D Center for Advanced Pharmaceuticals and Evaluation, Korea Institute of Toxicology, Daejeon, Republic of Korea
| | - Da Un Jeong
- Intelligent Human Twin Research Center, Electronics and Telecommunications Research Institute, Daejeon, Republic of Korea
| | - Ki Moo Lim
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Republic of Korea
| | - Seong-Jun Park
- College of Veterinary Medicine, Research Institute of Veterinary Medicine, Chungnam National University, Daejeon, Republic of Korea
| | - Ki-Suk Kim
- R&D Center for Advanced Pharmaceuticals and Evaluation, Korea Institute of Toxicology, Daejeon, Republic of Korea
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18
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Meier S, Grundland A, Dobrev D, Volders PG, Heijman J. In silico analysis of the dynamic regulation of cardiac electrophysiology by K v 11.1 ion-channel trafficking. J Physiol 2023; 601:2711-2731. [PMID: 36752166 PMCID: PMC10313819 DOI: 10.1113/jp283976] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 01/30/2023] [Indexed: 02/09/2023] Open
Abstract
Cardiac electrophysiology is regulated by continuous trafficking and internalization of ion channels occurring over minutes to hours. Kv 11.1 (also known as hERG) underlies the rapidly activating delayed-rectifier K+ current (IKr ), which plays a major role in cardiac ventricular repolarization. Experimental characterization of the distinct temporal effects of genetic and acquired modulators on channel trafficking and gating is challenging. Computer models are instrumental in elucidating these effects, but no currently available model incorporates ion-channel trafficking. Here, we present a novel computational model that reproduces the experimentally observed production, forward trafficking, internalization, recycling and degradation of Kv 11.1 channels, as well as their modulation by temperature, pentamidine, dofetilide and extracellular K+ . The acute effects of these modulators on channel gating were also incorporated and integrated with the trafficking model in the O'Hara-Rudy human ventricular cardiomyocyte model. Supraphysiological dofetilide concentrations substantially increased Kv 11.1 membrane levels while also producing a significant channel block. However, clinically relevant concentrations did not affect trafficking. Similarly, severe hypokalaemia reduced Kv 11.1 membrane levels based on long-term culture data, but had limited effect based on short-term data. By contrast, clinically relevant elevations in temperature acutely increased IKr due to faster kinetics, while after 24 h, IKr was decreased due to reduced Kv 11.1 membrane levels. The opposite was true for lower temperatures. Taken together, our model reveals a complex temporal regulation of cardiac electrophysiology by temperature, hypokalaemia, and dofetilide through competing effects on channel gating and trafficking, and provides a framework for future studies assessing the role of impaired trafficking in cardiac arrhythmias. KEY POINTS: Kv 11.1 channels underlying the rapidly activating delayed-rectifier K+ current are important for ventricular repolarization and are continuously shuttled from the cytoplasm to the plasma membrane and back over minutes to hours. Kv 11.1 gating and trafficking are modulated by temperature, drugs and extracellular K+ concentration but experimental characterization of their combined effects is challenging. Computer models may facilitate these analyses, but no currently available model incorporates ion-channel trafficking. We introduce a new two-state ion-channel trafficking model able to reproduce a wide range of experimental data, along with the effects of modulators of Kv 11.1 channel functioning and trafficking. The model reveals complex dynamic regulation of ventricular repolarization by temperature, extracellular K+ concentration and dofetilide through opposing acute (millisecond) effects on Kv 11.1 gating and long-term (hours) modulation of Kv 11.1 trafficking. This in silico trafficking framework provides a tool to investigate the roles of acute and long-term processes on arrhythmia promotion and maintenance.
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Affiliation(s)
- Stefan Meier
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Faculty of Health, Medicine, and Life Sciences, Maastricht University and Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Adaïa Grundland
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Faculty of Health, Medicine, and Life Sciences, Maastricht University and Maastricht University Medical Center+, Maastricht, The Netherlands
- Department of Data Science and Knowledge Engineering, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands
| | - Dobromir Dobrev
- Institute of Pharmacology, West German Heart and Vascular Center, University of Duisburg-Essen, Essen, Germany
- Department of Molecular Physiology & Biophysics, Baylor College of Medicine, Houston, Texas, United States of America
- Department of Medicine and Research Center, Montreal Heart Institute and Université de Montréal, Montréal, Quebec, Canada
| | - Paul G.A. Volders
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Faculty of Health, Medicine, and Life Sciences, Maastricht University and Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Jordi Heijman
- Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Faculty of Health, Medicine, and Life Sciences, Maastricht University and Maastricht University Medical Center+, Maastricht, The Netherlands
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19
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Steger-Hartmann T, Kreuchwig A, Wang K, Birzele F, Draganov D, Gaudio S, Rothfuss A. Perspectives of data science in preclinical safety assessment. Drug Discov Today 2023:103642. [PMID: 37244565 DOI: 10.1016/j.drudis.2023.103642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/12/2023] [Accepted: 05/22/2023] [Indexed: 05/29/2023]
Abstract
The data landscape in preclinical safety assessment is fundamentally changing because of not only emerging new data types, such as human systems biology, or real-world data (RWD) from clinical trials, but also technological advancements in data-processing software and analytical tools based on deep learning approaches. The recent developments of data science are illustrated with use cases for the three factors: predictive safety (new in silico tools), insight generation (new data for outstanding questions); and reverse translation (extrapolating from clinical experience to resolve preclinical questions). Further advances in this field can be expected if companies focus on overcoming identified challenges related to a lack of platforms and data silos and assuring appropriate training of data scientists within the preclinical safety teams.
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Affiliation(s)
| | - Annika Kreuchwig
- Investigational Toxicology, Bayer AG, Pharmaceuticals, 13353 Berlin, Germany
| | - Ken Wang
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences F. Hoffmann-La-Roche AG, Basel, Switzerland
| | - Fabian Birzele
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences F. Hoffmann-La-Roche AG, Basel, Switzerland
| | - Dragomir Draganov
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences F. Hoffmann-La-Roche AG, Basel, Switzerland
| | - Stefano Gaudio
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences F. Hoffmann-La-Roche AG, Basel, Switzerland
| | - Andreas Rothfuss
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences F. Hoffmann-La-Roche AG, Basel, Switzerland
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20
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Brennan S, Alnaimi AIM, McGuinness LR, Abdelaziz MIM, McKenzie RA, Draycott S, Whitmore J, Sharma P, Rainbow RD. Slowly activating voltage-gated potassium current potentiation by ML277 is a novel cardioprotective intervention. PNAS NEXUS 2023; 2:pgad156. [PMID: 37234204 PMCID: PMC10208113 DOI: 10.1093/pnasnexus/pgad156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/27/2023] [Accepted: 05/01/2023] [Indexed: 05/27/2023]
Abstract
Cardiovascular disease is thought to account for nearly a third of deaths worldwide, with ischemic heart disease, including acute coronary syndromes such as myocardial infarction, accounting for 1.7 million deaths per year. There is a clear need for interventions to impart cardioprotection against ischemia. Here, we show that the slowly activating voltage-gated potassium current (IKs) potentiator ML277 imparts cardioprotection against ischemia in cellular and whole-heart models by modulating the action potential duration. In three different metabolic inhibition and reperfusion models, an increased contractile recovery and cell survival was observed with ML277, indicative of protection. Finally, ML277 reduced infarct size in an ex vivo Langendorff coronary ligation model, including if only applied on reperfusion. In conclusion, potentiation of the IKs with ML277 imparted a cardioprotection that was equivalent to the protection reported previously by ischemic preconditioning. These data suggest that IKs potentiation may be therapeutically useful in acute coronary syndromes.
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Affiliation(s)
- Sean Brennan
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
| | - Abrar I M Alnaimi
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
| | - Lauren R McGuinness
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
| | - Muhammad I M Abdelaziz
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
| | - Robert A McKenzie
- Department of Cardiovascular Sciences, College of Life Sciences, University of Leicester, LE1 7RH, L7 8TX, UK
| | - Sophie Draycott
- Department of Cardiovascular Sciences, College of Life Sciences, University of Leicester, LE1 7RH, L7 8TX, UK
| | - Jacob Whitmore
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
| | - Parveen Sharma
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
| | - Richard D Rainbow
- Department of Cardiovascular and Metabolic Medicine & Liverpool Centre for Cardiovascular Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, L69 3GE, L7 8TX, UK
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21
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Farm HJ, Clerx M, Cooper F, Polonchuk L, Wang K, Gavaghan DJ, Lei CL. Importance of modelling hERG binding in predicting drug-induced action potential prolongations for drug safety assessment. Front Pharmacol 2023; 14:1110555. [PMID: 37021055 PMCID: PMC10067903 DOI: 10.3389/fphar.2023.1110555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/22/2023] [Indexed: 03/30/2023] Open
Abstract
Reduction of the rapid delayed rectifier potassium current (IKr) via drug binding to the human Ether-à-go-go-Related Gene (hERG) channel is a well recognised mechanism that can contribute to an increased risk of Torsades de Pointes. Mathematical models have been created to replicate the effects of channel blockers, such as reducing the ionic conductance of the channel. Here, we study the impact of including state-dependent drug binding in a mathematical model of hERG when translating hERG inhibition to action potential changes. We show that the difference in action potential predictions when modelling drug binding of hERG using a state-dependent model versus a conductance scaling model depends not only on the properties of the drug and whether the experiment achieves steady state, but also on the experimental protocols. Furthermore, through exploring the model parameter space, we demonstrate that the state-dependent model and the conductance scaling model generally predict different action potential prolongations and are not interchangeable, while at high binding and unbinding rates, the conductance scaling model tends to predict shorter action potential prolongations. Finally, we observe that the difference in simulated action potentials between the models is determined by the binding and unbinding rate, rather than the trapping mechanism. This study demonstrates the importance of modelling drug binding and highlights the need for improved understanding of drug trapping which can have implications for the uses in drug safety assessment.
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Affiliation(s)
- Hui Jia Farm
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Michael Clerx
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Fergus Cooper
- Doctoral Training Centre, University of Oxford, Oxford, United Kingdom
| | - Liudmila Polonchuk
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Ken Wang
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - David J. Gavaghan
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
- Doctoral Training Centre, University of Oxford, Oxford, United Kingdom
- *Correspondence: David J. Gavaghan, ; Chon Lok Lei,
| | - Chon Lok Lei
- Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau, China
- Department of Biomedical Sciences, Faculty of Health Sciences, University of Macau, Macau, China
- *Correspondence: David J. Gavaghan, ; Chon Lok Lei,
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22
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Altomare C, Bartolucci C, Sala L, Balbi C, Burrello J, Pietrogiovanna N, Burrello A, Bolis S, Panella S, Arici M, Krause R, Rocchetti M, Severi S, Barile L. A dynamic clamping approach using in silico IK1 current for discrimination of chamber-specific hiPSC-derived cardiomyocytes. Commun Biol 2023; 6:291. [PMID: 36934210 PMCID: PMC10024709 DOI: 10.1038/s42003-023-04674-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 03/07/2023] [Indexed: 03/20/2023] Open
Abstract
Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CM) constitute a mixed population of ventricular-, atrial-, nodal-like cells, limiting the reliability for studying chamber-specific disease mechanisms. Previous studies characterised CM phenotype based on action potential (AP) morphology, but the classification criteria were still undefined. Our aim was to use in silico models to develop an automated approach for discriminating the electrophysiological differences between hiPSC-CM. We propose the dynamic clamp (DC) technique with the injection of a specific IK1 current as a tool for deriving nine electrical biomarkers and blindly classifying differentiated CM. An unsupervised learning algorithm was applied to discriminate CM phenotypes and principal component analysis was used to visualise cell clustering. Pharmacological validation was performed by specific ion channel blocker and receptor agonist. The proposed approach improves the translational relevance of the hiPSC-CM model for studying mechanisms underlying inherited or acquired atrial arrhythmias in human CM, and for screening anti-arrhythmic agents.
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Affiliation(s)
- Claudia Altomare
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Euler institute, Università Svizzera italiana, Lugano, Switzerland
| | - Chiara Bartolucci
- Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Cesena, Italy
| | - Luca Sala
- Istituto Auxologico Italiano IRCCS, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milan, Italy
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
| | - Carolina Balbi
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Cellular and Molecular Cardiology, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Jacopo Burrello
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Division of Internal Medicine 4 and Hypertension Unit, Department of Medical Sciences, University of Torino, Torino, Italy
| | - Nicole Pietrogiovanna
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Alessio Burrello
- Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna, Italy
| | - Sara Bolis
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Cellular and Molecular Cardiology, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Stefano Panella
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Martina Arici
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
| | - Rolf Krause
- Euler institute, Università Svizzera italiana, Lugano, Switzerland
| | - Marcella Rocchetti
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
| | - Stefano Severi
- Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Cesena, Italy.
| | - Lucio Barile
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland.
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
- Euler institute, Università Svizzera italiana, Lugano, Switzerland.
- Faculty of Biomedical Sciences, Università Svizzera italiana, Lugano, Switzerland.
- Institute of Life Science, Scuola Superiore Sant'Anna, Pisa, Italy.
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23
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In silico assessment on TdP risks of drug combinations under CiPA paradigm. Sci Rep 2023; 13:2924. [PMID: 36807374 PMCID: PMC9940090 DOI: 10.1038/s41598-023-29208-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 01/31/2023] [Indexed: 02/22/2023] Open
Abstract
Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines' TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when limited drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models on several ion channels for various drug pairs. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as biomarker features. The drug combination maps were also used to illustrate combined medicines' TdP risk. We found that the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations.
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24
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Delaunois A, Mathy F, Cornet M, Gryshkova V, Korlowski C, Bonfitto F, Koch J, Schlit A, Hebeisen S, Passini E, Rodriguez B, Valentin J. Testing the nonclinical Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm with an established anti-seizure medication: Levetiracetam case study. Pharmacol Res Perspect 2023; 11:e01059. [PMID: 36748725 PMCID: PMC9903303 DOI: 10.1002/prp2.1059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 01/12/2023] [Accepted: 01/13/2023] [Indexed: 02/08/2023] Open
Abstract
Levetiracetam (LEV), a well-established anti-seizure medication (ASM), was launched before the original ICH S7B nonclinical guidance assessing QT prolongation potential and the introduction of the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm. No information was available on its effects on cardiac channels. The goal of this work was to "pressure test" the CiPA approach with LEV and check the concordance of nonclinical core and follow-up S7B assays with clinical and post-marketing data. The following experiments were conducted with LEV (0.25-7.5 mM): patch clamp assays on hERG (acute or trafficking effects), NaV 1.5, CaV 1.2, Kir 2.1, KV 7.1/mink, KV 1.5, KV 4.3, and HCN4; in silico electrophysiology modeling (Virtual Assay® software) in control, large-variability, and high-risk human ventricular cell populations; electrophysiology measurements in human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes and dog Purkinje fibers; ECG measurements in conscious telemetered dogs after single oral administration (150, 300, and 600 mg/kg). Except a slight inhibition (<10%) of hERG and KV 7.1/mink at 7.5 mM, that is, 30-fold the free therapeutic plasma concentration (FTPC) at 1500 mg, LEV did not affect any other cardiac channels or hERG trafficking. In both virtual and real human cardiomyocytes, and in dog Purkinje fibers, LEV induced no relevant changes in electrophysiological parameters or arrhythmia. No QTc prolongation was noted up to 2.7 mM unbound plasma levels in conscious dogs, corresponding to 10-fold the FTPC. Nonclinical assessment integrating CiPA assays shows the absence of QT prolongation and proarrhythmic risk of LEV up to at least 10-fold the FTPC and the good concordance with clinical and postmarketing data, although this does not exclude very rare occurrence of QT prolongation cases in patients with underlying risk factors.
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Affiliation(s)
| | | | - Miranda Cornet
- Development SciencesUCB Biopharma SRLBraine‐l'AlleudBelgium
| | | | | | | | - Juliane Koch
- Patient Safety, UCB Biosciences GmbHMonheimGermany
| | | | | | - Elisa Passini
- Department of Computer ScienceUniversity of OxfordOxfordUK
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25
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Chiu K, Racz R, Burkhart K, Florian J, Ford K, Iveth Garcia M, Geiger RM, Howard KE, Hyland PL, Ismaiel OA, Kruhlak NL, Li Z, Matta MK, Prentice KW, Shah A, Stavitskaya L, Volpe DA, Weaver JL, Wu WW, Rouse R, Strauss DG. New science, drug regulation, and emergent public health issues: The work of FDA's division of applied regulatory science. Front Med (Lausanne) 2023; 9:1109541. [PMID: 36743666 PMCID: PMC9893027 DOI: 10.3389/fmed.2022.1109541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 12/13/2022] [Indexed: 01/20/2023] Open
Abstract
The U.S. Food and Drug Administration (FDA) Division of Applied Regulatory Science (DARS) moves new science into the drug review process and addresses emergent regulatory and public health questions for the Agency. By forming interdisciplinary teams, DARS conducts mission-critical research to provide answers to scientific questions and solutions to regulatory challenges. Staffed by experts across the translational research spectrum, DARS forms synergies by pulling together scientists and experts from diverse backgrounds to collaborate in tackling some of the most complex challenges facing FDA. This includes (but is not limited to) assessing the systemic absorption of sunscreens, evaluating whether certain drugs can convert to carcinogens in people, studying drug interactions with opioids, optimizing opioid antagonist dosing in community settings, removing barriers to biosimilar and generic drug development, and advancing therapeutic development for rare diseases. FDA tasks DARS with wide ranging issues that encompass regulatory science; DARS, in turn, helps the Agency solve these challenges. The impact of DARS research is felt by patients, the pharmaceutical industry, and fellow regulators. This article reviews applied research projects and initiatives led by DARS and conducts a deeper dive into select examples illustrating the impactful work of the Division.
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Affiliation(s)
- Kimberly Chiu
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Rebecca Racz
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Keith Burkhart
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Jeffry Florian
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Kevin Ford
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - M. Iveth Garcia
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Robert M. Geiger
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Kristina E. Howard
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Paula L. Hyland
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Omnia A. Ismaiel
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Naomi L. Kruhlak
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Zhihua Li
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Murali K. Matta
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Kristin W. Prentice
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States,Booz Allen Hamilton, McLean, VA, United States
| | - Aanchal Shah
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States,Booz Allen Hamilton, McLean, VA, United States
| | - Lidiya Stavitskaya
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Donna A. Volpe
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - James L. Weaver
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Wendy W. Wu
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - Rodney Rouse
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States
| | - David G. Strauss
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, United States,*Correspondence: David G. Strauss,
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26
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Baltov B, Beyl S, Baburin I, Reinhardt J, Szkokan P, Garifulina A, Timin E, Kraushaar U, Potterat O, Hamburger M, Kügler P, Hering S. Assay for evaluation of proarrhythmic effects of herbal products: Case study with 12 Evodia preparations. Toxicol Rep 2023; 10:589-599. [PMID: 37213814 PMCID: PMC10196857 DOI: 10.1016/j.toxrep.2023.04.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/11/2023] [Accepted: 04/24/2023] [Indexed: 05/23/2023] Open
Abstract
Guidelines for preclinical drug development reduce the occurrence of arrhythmia-related side effects. Besides ample evidence for the presence of arrhythmogenic substances in plants, there is no consensus on a research strategy for the evaluation of proarrhythmic effects of herbal products. Here, we propose a cardiac safety assay for the detection of proarrhythmic effects of plant extracts based on the experimental approaches described in the Comprehensive In vitro Proarrhythmia Assay (CiPA). Microelectrode array studies (MEAs) and voltage sensing optical technique on human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) were combined with ionic current measurements in mammalian cell lines, In-silico simulations of cardiac action potentials (APs) and statistic regression analysis. Proarrhythmic effects of 12 Evodia preparations, containing different amounts of the hERG inhibitors dehydroevodiamine (DHE) and hortiamine were analysed. Extracts produced different prolongation of the AP, occurrence of early after depolarisations and triangulation of the AP in hiPSC-CMs depending on the contents of the hERG inhibitors. DHE and hortiamine dose-dependently prolonged the field potential duration in hiPSC-CMs studied with MEAs. In-silico simulations of ventricular AP support a scenario where proarrhythmic effects of Evodia extracts are predominantly caused by the content of the selective hERG inhibitors. Statistic regression analysis revealed a high torsadogenic risk for both compounds that was comparable to drugs assigned to the high-risk category in a CiPA study.
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Affiliation(s)
- Bozhidar Baltov
- Division of Pharmacology and Toxicology, Department of Pharmaceutical Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria
- ChanPharm GmbH, Am Kanal 27, 1110 Vienna, Austria
| | | | - Igor Baburin
- ChanPharm GmbH, Am Kanal 27, 1110 Vienna, Austria
| | - Jakob Reinhardt
- Pharmaceutical Biology, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland
| | | | - Aleksandra Garifulina
- Division of Pharmacology and Toxicology, Department of Pharmaceutical Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria
| | - Eugen Timin
- ChanPharm GmbH, Am Kanal 27, 1110 Vienna, Austria
| | - Udo Kraushaar
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany
| | - Olivier Potterat
- Pharmaceutical Biology, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland
| | - Matthias Hamburger
- Pharmaceutical Biology, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland
| | - Philipp Kügler
- University of Hohenheim, Institute of Applied Mathematics and Statistics and Computational Science Hub, 70599 Stuttgart, Germany
| | - Steffen Hering
- Division of Pharmacology and Toxicology, Department of Pharmaceutical Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria
- ChanPharm GmbH, Am Kanal 27, 1110 Vienna, Austria
- Correspondence to: Am Kanal 27,2/3/5–7, 1110 Vienna, Austria.
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27
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Zhou H, Zhang Z, Zhu L, Li P, Hong S, Liu L, Liu X. Prediction of drug pro-arrhythmic cardiotoxicity using a semi-physiologically based pharmacokinetic model linked to cardiac ionic currents inhibition. Toxicol Appl Pharmacol 2022; 457:116312. [PMID: 36343672 DOI: 10.1016/j.taap.2022.116312] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 10/23/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
Drug-induced torsades de pointes (TdP) risks are responsible for the withdrawal of many drugs from the market. Nowadays, assessments of drug-induced TdP risks are mainly based on maximum effective free therapeutic plasma concentration (EFTPCmax) and cardiac ionic current inhibitions using the human ventricular myocytes model (Tor-ORd model). Myocytes are targets of drug-induced TdP. The TdP risks may be directly linked to myocyte drug concentrations. We aimed to develop a semi-physiologically based pharmacokinetic (Semi-PBPK) model linked to cardiac ionic current inhibition (pharmacodynamics, PD) (Semi-PBPK-PD) to simultaneously predict myocyte drug concentrations and their TdP risks in humans. Alterations in action potential duration (ΔAPD90) were simulated using the Tor-ORd model and ionic current inhibition parameters based on myocyte or plasma drug concentrations. The predicted ΔAPD90 values were translated into in vivo alterations in QT interval(ΔQTc) induced by moxifloxacin, dofetilide, or sotalol. Myocyte drug concentrations of moxifloxacin, dofetilide, and sotalol gave better predictions of ΔQTc than plasma. Following validating the developed semi-PBPK-PD model, TdP risks of 37 drugs were assessed using ΔAPD90 and early afterdepolarization occurrence, which were estimated based on 10 × EFTPCmax and 10 × EFTMCmax (maximum effective free therapeutic myocyte concentration). 10 × EFTMCmax gave more sensitive and accurate predictions of pro-arrhythmic cardiotoxicity and the predicted TdP risks were also closer to clinic practice than 10 × EFTPCmax. In conclusion, pharmacokinetics and TdP risks of 37 drugs were successfully predicted using the semi-PBPK-PD model. Myocyte drug concentrations gave better predictions of ΔQTc and TdP risks than plasma.
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Affiliation(s)
- Han Zhou
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Zexin Zhang
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Liang Zhu
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Ping Li
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Shijin Hong
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Li Liu
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
| | - Xiaodong Liu
- Center of Drug Metabolism and Pharmacokinetics, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
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28
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Jeong DU, Qashri Mahardika T N, Marcellinus A, Lim KM. qInward variability-based in-silico proarrhythmic risk assessment of drugs using deep learning model. Front Physiol 2022; 13:1080190. [PMID: 36589462 PMCID: PMC9794579 DOI: 10.3389/fphys.2022.1080190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 11/29/2022] [Indexed: 12/15/2022] Open
Abstract
Many researchers have suggested evaluation methods and Torsades de Pointes (TdP) metrics to assess the proarrhythmic risk of a drug based on the in silico simulation, as part of the Comprehensive in-vitro Proarrhythmia Assay (CiPA) project. In the previous study, we validated the robustness of 12 in silico features using the ordinal logistic regression (OLR) model by comparing the classification performances of metrics according to the in-vitro experimental datasets used; however, the OLR model using 12 in silico features did not provide desirable results. This study proposed a convolutional neural network (CNN) model using the variability of promising in silico TdP metrics hypothesizing that the variability of in silico features based on beats has more information than the single value of in silico features. We performed the action potential (AP) simulation using a human ventricular myocyte model to calculate seven in silico features representing the electrophysiological cell states of drug effects over 1,000 beats: qNet, qInward, intracellular calcium duration at returning to 50% baseline (CaD50) and 90% baseline (CaD90), AP duration at 50% repolarization (APD50) and 90% repolarization (APD90), and dVm/dtMax_repol. The proposed CNN classifier was trained using 12 train drugs and tested using 16 test drugs among CiPA drugs. The torsadogenic risk of drugs was classified as high, intermediate, and low risks. We determined the CNN classifier by comparing the classification performance according to the variabilities of seven in silico biomarkers computed from the in silico drug simulation using the Chantest dataset. The proposed CNN classifier performed the best when using qInward variability to classify the TdP-risk drugs with 0.94 AUC for high risk and 0.93 AUC for low risk. In addition, the final CNN classifier was validated using the qInward variability obtained after merging three in-vitro datasets, but the model performance decreased to a moderate level of 0.75 and 0.78 AUC. These results suggest the need for the proposed CNN model to be trained and tested using various types of drugs.
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Affiliation(s)
- Da Un Jeong
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Gyeongbuk, South Korea
| | - Nurul Qashri Mahardika T
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Gyeongbuk, South Korea
| | - Aroli Marcellinus
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Gyeongbuk, South Korea
| | - Ki Moo Lim
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Gyeongbuk, South Korea,Department of Medical IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Gyeongbuk, South Korea,Meta Heart Inc., Gumi, Gyeongbuk, South Korea,*Correspondence: Ki Moo Lim,
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Wiśniowska B, Holbrook M, Pollard C, Polak S. Utilization of mechanistic modelling and simulation to analyse fenspiride proarrhythmic potency - Role of physiological and other non-drug related parameters. J Clin Pharm Ther 2022; 47:2152-2161. [PMID: 36068182 DOI: 10.1111/jcpt.13762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 07/28/2022] [Accepted: 08/02/2022] [Indexed: 12/24/2022]
Abstract
WHAT IS KNOWN AND OBJECTIVE Fenspiride, a drug that had been used for decades for the treatment of respiratory diseases, was recently withdrawn from the market due to the potential risk of QT prolongation and proarrhythmia. This is the first such withdrawal for many years and hence poses a question whether such risk could have been predicted and to what degree non-drug-specific parameters play a role in the reported QT prolongation and cases of TdP. The study aim was to test various 'what-if' scenarios to assess the influence of age, gender, heart rate, and plasma potassium concentration on QT interval prolongation due to various doses of fenspiride with the use of mechanistic mathematical modelling. METHODS Concentration-time profiles were simulated with the use of a PBPK model developed based on published physico-chemical data, data from in vitro ADME experiments, and in vivo PK study results. Pharmacodynamic effect, that is, drug-triggered pseudoECG signal modification was simulated using a biophysically detailed model of human cardiac myocytes. Analysis of the qNet metric was also performed to classify proarrhythmic risk related to fenspiride. RESULTS In the simulation study, arrhythmia was not observed even in the 'what-if' scenarios with extreme exposure, age, heart rate, and plasma potassium concentration. The qNet metric value positioned fenspiride in the intermediate risk class. WHAT IS NEW AND CONCLUSION It can be hypothesized that the clinically observed arrhythmia cases were not directly caused by fenspiride alone but a combination of multiple factors, including comedications.
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Affiliation(s)
- Barbara Wiśniowska
- Faculty of Pharmacy, Unit of Pharmacoepidemiology and Pharmacoeconomics, Jagiellonian University Medical College, Krakow, Poland
| | | | | | - Sebastian Polak
- Faculty of Pharmacy, Unit of Pharmacoepidemiology and Pharmacoeconomics, Jagiellonian University Medical College, Krakow, Poland.,Simcyp Division, Certara UK Limited, Sheffield, UK
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30
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Kohjitani H, Koda S, Himeno Y, Makiyama T, Yamamoto Y, Yoshinaga D, Wuriyanghai Y, Kashiwa A, Toyoda F, Zhang Y, Amano A, Noma A, Kimura T. Gradient-based parameter optimization method to determine membrane ionic current composition in human induced pluripotent stem cell-derived cardiomyocytes. Sci Rep 2022; 12:19110. [PMID: 36351955 PMCID: PMC9646722 DOI: 10.1038/s41598-022-23398-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
Premature cardiac myocytes derived from human induced pluripotent stem cells (hiPSC-CMs) show heterogeneous action potentials (APs), probably due to different expression patterns of membrane ionic currents. We developed a method for determining expression patterns of functional channels in terms of whole-cell ionic conductance (Gx) using individual spontaneous AP configurations. It has been suggested that apparently identical AP configurations can be obtained using different sets of ionic currents in mathematical models of cardiac membrane excitation. If so, the inverse problem of Gx estimation might not be solved. We computationally tested the feasibility of the gradient-based optimization method. For a realistic examination, conventional 'cell-specific models' were prepared by superimposing the model output of AP on each experimental AP recorded by conventional manual adjustment of Gxs of the baseline model. Gxs of 4-6 major ionic currents of the 'cell-specific models' were randomized within a range of ± 5-15% and used as an initial parameter set for the gradient-based automatic Gxs recovery by decreasing the mean square error (MSE) between the target and model output. Plotting all data points of the MSE-Gx relationship during optimization revealed progressive convergence of the randomized population of Gxs to the original value of the cell-specific model with decreasing MSE. The absence of any other local minimum in the global search space was confirmed by mapping the MSE by randomizing Gxs over a range of 0.1-10 times the control. No additional local minimum MSE was obvious in the whole parameter space, in addition to the global minimum of MSE at the default model parameter.
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Affiliation(s)
- Hirohiko Kohjitani
- grid.258799.80000 0004 0372 2033Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Shigeya Koda
- grid.262576.20000 0000 8863 9909Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Yukiko Himeno
- grid.262576.20000 0000 8863 9909Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Takeru Makiyama
- grid.258799.80000 0004 0372 2033Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yuta Yamamoto
- grid.258799.80000 0004 0372 2033Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Daisuke Yoshinaga
- grid.258799.80000 0004 0372 2033Department Pediatrics, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yimin Wuriyanghai
- grid.258799.80000 0004 0372 2033Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Asami Kashiwa
- grid.258799.80000 0004 0372 2033Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Futoshi Toyoda
- grid.410827.80000 0000 9747 6806Department of Physiology, Shiga University of Medical Science, Otsu, Japan
| | - Yixin Zhang
- grid.262576.20000 0000 8863 9909Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Akira Amano
- grid.262576.20000 0000 8863 9909Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Akinori Noma
- grid.262576.20000 0000 8863 9909Graduate School of Life Sciences, Ritsumeikan University, Kusatsu, Japan
| | - Takeshi Kimura
- grid.258799.80000 0004 0372 2033Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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31
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Jeong DU, Danadibrata RZ, Marcellinus A, Lim KM. Validation of in silico biomarkers for drug screening through ordinal logistic regression. Front Physiol 2022; 13:1009647. [PMID: 36277213 PMCID: PMC9583152 DOI: 10.3389/fphys.2022.1009647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Since the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiation, many studies have suggested various in silico features based on ionic charges, action potentials (AP), or intracellular calcium (Ca) to assess proarrhythmic risk. These in silico features are computed through electrophysiological simulations using in vitro experimental datasets as input, therefore changing with the quality of in vitro experimental data; however, research to validate the robustness of in silico features for proarrhythmic risk assessment of drugs depending on in vitro datasets has not been conducted. This study aims to verify the availability of in silico features commonly used in assessing the cardiac toxicity of drugs through an ordinal logistic regression model and three in vitro datasets measured under different experimental environments and with different purposes. We performed in silico drug simulations using the Tomek-Ohara Rudy (ToR-ORD) ventricular myocyte model and computed 12 in silico features comprising six AP features, four Ca features, and two ion charge features, which reflected the effect and characteristics of each in vitro data for CiPA 28 drugs. We then compared the classific performances of ordinal logistic regressions according to these 12 in silico features and used in vitro datasets to validate which in silico feature is the best for assessing the proarrhythmic risk of drugs at high, intermediate, and low levels. All 12 in silico features helped determine high-risky torsadogenic drugs, regardless of the in vitro datasets used in the in silico simulation as input. In the three types of in silico features, AP features were the most reliable for determining the three Torsade de Pointes (TdP) risk standards. Among AP features, AP duration at 50% repolarization (APD50) was the best when individually using in silico features per in vitro dataset. In contrast, the AP repolarization velocity (dVm/dtMax_repol) was the best when merging all in silico features computed through three in vitro datasets.
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Affiliation(s)
- Da Un Jeong
- Computational Medicine Lab, Kumoh National Institute of Technology, Department of IT Convergence Engineering, Gumi, South Korea
| | - Rakha Zharfarizqi Danadibrata
- Computational Medicine Lab, Kumoh National Institute of Technology, Department of IT Convergence Engineering, Gumi, South Korea
| | - Aroli Marcellinus
- Computational Medicine Lab, Kumoh National Institute of Technology, Department of IT Convergence Engineering, Gumi, South Korea
| | - Ki Moo Lim
- Computational Medicine Lab, Kumoh National Institute of Technology, Department of IT Convergence Engineering, Gumi, South Korea
- Computational Medicine Lab, Kumoh National Institute of Technology, Department of Medical IT Convergence Engineering, Gumi, South Korea
- *Correspondence: Ki Moo Lim,
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32
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Trovato C, Mohr M, Schmidt F, Passini E, Rodriguez B. Cross clinical-experimental-computational qualification of in silico drug trials on human cardiac purkinje cells for proarrhythmia risk prediction. FRONTIERS IN TOXICOLOGY 2022; 4:992650. [PMID: 36278026 PMCID: PMC9581132 DOI: 10.3389/ftox.2022.992650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 09/20/2022] [Indexed: 11/06/2022] Open
Abstract
The preclinical identification of drug-induced cardiotoxicity and its translation into human risk are still major challenges in pharmaceutical drug discovery. The ICH S7B Guideline and Q&A on Clinical and Nonclinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential promotes human in silico drug trials as a novel tool for proarrhythmia risk assessment. To facilitate the use of in silico data in regulatory submissions, explanatory control compounds should be tested and documented to demonstrate consistency between predictions and the historic validation data. This study aims to quantify drug-induced electrophysiological effects on in silico cardiac human Purkinje cells, to compare them with existing in vitro rabbit data, and to assess their accuracy for clinical pro-arrhythmic risk predictions. The effects of 14 reference compounds were quantified in simulations with a population of in silico human cardiac Purkinje models. For each drug dose, five electrophysiological biomarkers were quantified at three pacing frequencies, and results compared with available in vitro experiments and clinical proarrhythmia reports. Three key results were obtained: 1) In silico, repolarization abnormalities in human Purkinje simulations predicted drug-induced arrhythmia for all risky compounds, showing higher predicted accuracy than rabbit experiments; 2) Drug-induced electrophysiological changes observed in human-based simulations showed a high degree of consistency with in vitro rabbit recordings at all pacing frequencies, and depolarization velocity and action potential duration were the most consistent biomarkers; 3) discrepancies observed for dofetilide, sotalol and terfenadine are mainly caused by species differences between humans and rabbit. Taken together, this study demonstrates higher accuracy of in silico methods compared to in vitro animal models for pro-arrhythmic risk prediction, as well as a high degree of consistency with in vitro experiments commonly used in safety pharmacology, supporting the potential for industrial and regulatory adoption of in silico trials for proarrhythmia prediction.
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Affiliation(s)
- Cristian Trovato
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Marcel Mohr
- Sanofi-Aventis Deutschland GmbH, R&D Preclinical Safety, Frankfurt, Germany
| | - Friedemann Schmidt
- Sanofi-Aventis Deutschland GmbH, R&D Preclinical Safety, Frankfurt, Germany
| | - Elisa Passini
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford, Oxford, United Kingdom,*Correspondence: Blanca Rodriguez,
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33
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Koivumäki JT, Hoffman J, Maleckar MM, Einevoll GT, Sundnes J. Computational cardiac physiology for new modelers: Origins, foundations, and future. Acta Physiol (Oxf) 2022; 236:e13865. [PMID: 35959512 DOI: 10.1111/apha.13865] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 01/29/2023]
Abstract
Mathematical models of the cardiovascular system have come a long way since they were first introduced in the early 19th century. Driven by a rapid development of experimental techniques, numerical methods, and computer hardware, detailed models that describe physical scales from the molecular level up to organs and organ systems have been derived and used for physiological research. Mathematical and computational models can be seen as condensed and quantitative formulations of extensive physiological knowledge and are used for formulating and testing hypotheses, interpreting and directing experimental research, and have contributed substantially to our understanding of cardiovascular physiology. However, in spite of the strengths of mathematics to precisely describe complex relationships and the obvious need for the mathematical and computational models to be informed by experimental data, there still exist considerable barriers between experimental and computational physiological research. In this review, we present a historical overview of the development of mathematical and computational models in cardiovascular physiology, including the current state of the art. We further argue why a tighter integration is needed between experimental and computational scientists in physiology, and point out important obstacles and challenges that must be overcome in order to fully realize the synergy of experimental and computational physiological research.
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Affiliation(s)
- Jussi T Koivumäki
- Faculty of Medicine and Health Technology, and Centre of Excellence in Body-on-Chip Research, Tampere University, Tampere, Finland
| | - Johan Hoffman
- Division of Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Mary M Maleckar
- Computational Physiology Department, Simula Research Laboratory, Oslo, Norway
| | - Gaute T Einevoll
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway.,Department of Physics, Norwegian University of Life Sciences, Ås, Norway
| | - Joakim Sundnes
- Computational Physiology Department, Simula Research Laboratory, Oslo, Norway
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34
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Watt ED, Lee T, Feng SL, Kilfoil P, Ackley D, Keefer C, Wisialowski T, Jenkinson S. Use of high throughput ion channel profiling and statistical modeling to predict off-target arrhythmia risk - One pharma's experience and perspective. J Pharmacol Toxicol Methods 2022; 118:107213. [PMID: 36084863 DOI: 10.1016/j.vascn.2022.107213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 08/18/2022] [Accepted: 08/29/2022] [Indexed: 11/29/2022]
Abstract
INTRODUCTION The use of high throughput patch clamp profiling to determine mixed ion channel-mediated arrhythmia risk was assessed using profiling data generated using proprietary internal and clinical reference compounds. We define the reproducibility of the platform and highlight inherent platform issues. The data generated was used to develop predictive models for cardiac arrhythmia risk, specifically Torsades de Pointes (TdP). METHODS A retrospective analysis was performed using profiling data generated over a 3-year period, including patch clamp data from hERG, Cav1.2, and Nav1.5 (peak/late), together with hERG binding. RESULTS Assay reproducibility was robust over the 3-year period examined. High throughput hERG patch IC50 values correlated well with GLP-hERG data (Pearson = 0.87). A disconnect between hERG binding and patch was observed for ∼10% compounds and trended with passive cellular permeability. hERG and Cav1.2 potency did not correlate for proprietary compounds, with more potent hERG compounds showing selectivity versus Cav1.2. For clinical compounds where hERG and Cav1.2 activity was more balanced, an analysis of TdP risk versus hERG/Cav1.2 ratio demonstrated low TdP probability when the hERG/Cav1.2 potency ratios were < 1. Modeling of clinical compound data revealed a lack of impact of the Nav1.5 (late) current in predicting TdP. Moreover, models using hERG binding data (ROC AUC = 0.876) showed an improved ability to predict TdP risk versus hERG patch clamp (ROC AUC = 0.787). DISCUSSION The data highlight the value of high throughput patch clamp data in the prediction of TdP risk, as well as some potential limitations with this approach.
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Affiliation(s)
- Eric D Watt
- Worldwide Research, Development and Medical, Pfizer Inc., Groton, CT 06340, USA
| | - Tiffany Lee
- Worldwide Research, Development and Medical, Pfizer Inc., San Diego, CA 92121, USA
| | - Shuyun Lily Feng
- Worldwide Research, Development and Medical, Pfizer Inc., San Diego, CA 92121, USA
| | - Peter Kilfoil
- Worldwide Research, Development and Medical, Pfizer Inc., San Diego, CA 92121, USA
| | - David Ackley
- Worldwide Research, Development and Medical, Pfizer Inc., Groton, CT 06340, USA
| | - Christopher Keefer
- Worldwide Research, Development and Medical, Pfizer Inc., Groton, CT 06340, USA
| | - Todd Wisialowski
- Worldwide Research, Development and Medical, Pfizer Inc., Groton, CT 06340, USA
| | - Stephen Jenkinson
- Worldwide Research, Development and Medical, Pfizer Inc., San Diego, CA 92121, USA.
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35
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Translating the measurement of hERG kinetics and drug block for CiPA to a high throughput platform. J Pharmacol Toxicol Methods 2022; 117:107192. [PMID: 35750310 DOI: 10.1016/j.vascn.2022.107192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/13/2022] [Accepted: 06/16/2022] [Indexed: 11/23/2022]
Abstract
The Comprehensive in vitro Proarrhythmic Assay (CiPA) has promoted use of in silico models of drug effects on cardiac repolarization to improve proarrhythmic risk prediction. These models contain a pharmacodynamic component describing drug binding to hERG channels that required in vitro data for kinetics of block, in addition to potency, to constrain them. To date, development and validation has been undertaken using data from manual patch-clamp. The application of this approach at scale requires the development of a high-throughput, automated patch-clamp (APC) implementation. Here, we present a comprehensive analysis of the implementation of the Milnes, or CiPA dynamic protocol, on an APC platform, including quality control and data analysis. Kinetics and potency of block were assessed for bepridil, cisapride, terfenadine and verapamil with data retention/QC pass rate of 21.8% overall, or as high as 50.4% when only appropriate sweep lengths were considered for drugs with faster kinetics. The variability in IC50 and kinetics between manual and APC was comparable to that seen between sites/platforms in previous APC studies of potency. Whilst the experimental success is less than observed in screens of potency alone, it is still significantly greater than manual patch. With the modifications to protocol design, including sweep length, number of repetitions, and leak correction recommended in this study, this protocol can be applied on APC to acquire data comparable to manual patch clamp.
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36
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Bartolucci C, Forouzandehmehr M, Severi S, Paci M. A Novel In Silico Electromechanical Model of Human Ventricular Cardiomyocyte. Front Physiol 2022; 13:906146. [PMID: 35721558 PMCID: PMC9198403 DOI: 10.3389/fphys.2022.906146] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 05/10/2022] [Indexed: 11/25/2022] Open
Abstract
Contractility has become one of the main readouts in computational and experimental studies on cardiomyocytes. Following this trend, we propose a novel mathematical model of human ventricular cardiomyocytes electromechanics, BPSLand, by coupling a recent human contractile element to the BPS2020 model of electrophysiology. BPSLand is the result of a hybrid optimization process and it reproduces all the electrophysiology experimental indices captured by its predecessor BPS2020, simultaneously enabling the simulation of realistic human active tension and its potential abnormalities. The transmural heterogeneity in both electrophysiology and contractility departments was simulated consistent with previous computational and in vitro studies. Furthermore, our model could capture delayed afterdepolarizations (DADs), early afterdepolarizations (EADs), and contraction abnormalities in terms of aftercontractions triggered by either drug action or special pacing modes. Finally, we further validated the mechanical results of the model against previous experimental and in silico studies, e.g., the contractility dependence on pacing rate. Adding a new level of applicability to the normative models of human cardiomyocytes, BPSLand represents a robust, fully-human in silico model with promising capabilities for translational cardiology.
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Affiliation(s)
- Chiara Bartolucci
- Computational Physiopathology Unit, Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | | | - Stefano Severi
- Computational Physiopathology Unit, Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | - Michelangelo Paci
- BioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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37
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Llopis-Lorente J, Trenor B, Saiz J. Considering population variability of electrophysiological models improves the in silico assessment of drug-induced torsadogenic risk. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 221:106934. [PMID: 35687995 DOI: 10.1016/j.cmpb.2022.106934] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 05/31/2022] [Accepted: 06/02/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND AND OBJECTIVE In silico tools are known to aid in drug cardiotoxicity assessment. However, computational models do not usually consider electrophysiological variability, which may be crucial when predicting rare adverse events such as drug-induced Torsade de Pointes (TdP). In addition, classification tools are usually binary and are not validated using an external data set. Here we analyze the role of incorporating electrophysiological variability in the prediction of drug-induced arrhythmogenic-risk, using a ternary classification and two external validation datasets. METHODS The effects of the 12 training CiPA drugs were simulated at three different concentrations using a single baseline model and an electrophysiologically calibrated population of models. 9 biomarkers related with action potential (AP), calcium dynamics and net charge were measured for each simulated concentration. These biomarkers were used to build ternary classifiers based on Support Vector Machines (SVM) methodology. Classifiers were validated using two external drug sets: the 16 validation CiPA drugs and 81 drugs from CredibleMeds database. RESULTS Population of models allowed to obtain different AP responses under the same pharmacological intervention and improve the prediction of drug-induced TdP with respect to the baseline model. The classification tools based on population of models achieve an accuracy higher than 0.8 and a mean classification error (MCE) lower than 0.3 for both validation drug sets and for the two electrophysiological action potential models studied (Tomek et al. 2020 and a modified version of O'Hara et al. 2011). In addition, simulations with population of models allowed the identification of individuals with lower conductances of IKr, IKs, and INaK and higher conductances of ICaL, INaL, and INCX, which are more prone to develop TdP. CONCLUSIONS The methodology presented here provides new opportunities to assess drug-induced TdP-risk, taking into account electrophysiological variability and may be helpful to improve current cardiac safety screening methods.
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Affiliation(s)
- Jordi Llopis-Lorente
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, Valencia 46022, Spain
| | - Beatriz Trenor
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, Valencia 46022, Spain
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, Valencia 46022, Spain.
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38
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Barral YSHM, Shuttleworth JG, Clerx M, Whittaker DG, Wang K, Polonchuk L, Gavaghan DJ, Mirams GR. A Parameter Representing Missing Charge Should Be Considered when Calibrating Action Potential Models. Front Physiol 2022; 13:879035. [PMID: 35557969 PMCID: PMC9086858 DOI: 10.3389/fphys.2022.879035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 03/16/2022] [Indexed: 11/13/2022] Open
Abstract
Computational models of the electrical potential across a cell membrane are longstanding and vital tools in electrophysiology research and applications. These models describe how ionic currents, internal fluxes, and buffering interact to determine membrane voltage and form action potentials (APs). Although this relationship is usually expressed as a differential equation, previous studies have shown it can be rewritten in an algebraic form, allowing direct calculation of membrane voltage. Rewriting in this form requires the introduction of a new parameter, called Γ0 in this manuscript, which represents the net concentration of all charges that influence membrane voltage but are not considered in the model. Although several studies have examined the impact of Γ0 on long-term stability and drift in model predictions, there has been little examination of its effects on model predictions, particularly when a model is refit to new data. In this study, we illustrate how Γ0 affects important physiological properties such as action potential duration restitution, and examine the effects of (in)correctly specifying Γ0 during model calibration. We show that, although physiologically plausible, the range of concentrations used in popular models leads to orders of magnitude differences in Γ0, which can lead to very different model predictions. In model calibration, we find that using an incorrect value of Γ0 can lead to biased estimates of the inferred parameters, but that the predictive power of these models can be restored by fitting Γ0 as a separate parameter. These results show the value of making Γ0 explicit in model formulations, as it forces modellers and experimenters to consider the effects of uncertainty and potential discrepancy in initial concentrations upon model predictions.
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Affiliation(s)
- Yann-Stanislas H M Barral
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.,Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Joseph G Shuttleworth
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Michael Clerx
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Dominic G Whittaker
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Ken Wang
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Liudmila Polonchuk
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - David J Gavaghan
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Gary R Mirams
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
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39
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Jeong DU, Yoo Y, Marcellinus A, Kim K, Lim KM. Proarrhythmic risk assessment of drugs by dV m /dt shapes using the convolutional neural network. CPT Pharmacometrics Syst Pharmacol 2022; 11:653-664. [PMID: 35579100 PMCID: PMC9124356 DOI: 10.1002/psp4.12803] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 03/16/2022] [Accepted: 03/21/2022] [Indexed: 01/08/2023] Open
Abstract
Comprehensive in vitro Proarrhythmia Assay (CiPA) projects for assessing proarrhythmic drugs suggested a logistic regression model using qNet as the Torsades de Pointes (TdP) risk assessment biomarker, obtained from in silico simulation. However, using a single in silico feature, such as qNet, cannot reflect whole characteristics related to TdP in the entire action potential (AP) shape. Thus, this study proposed a deep convolutional neural network (CNN) model using differential action potential shapes to classify three proarrhythmic risk levels: high, intermediate, and low, considering both characteristics related to TdP not only in the depolarization phase but also the repolarization phase of AP shape. We performed an in silico simulation and got AP shapes with drug effects using half-maximal inhibitory concentration and Hill coefficients of 28 drugs released by CiPA groups. Then, we trained the deep CNN model with the differential AP shapes of 12 drugs and tested it with those of 16 drugs. Our model had a better performance for classifying the proarrhythmic risk of drugs than the traditional logistic regression model using qNet. The classification accuracy was 98% for high-risk level drugs, 94% for intermediate-risk level drugs, and 89% for low-risk level drugs.
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Affiliation(s)
- Da Un Jeong
- Department of IT Convergence EngineeringKumoh National Institute of TechnologyGumiKorea
| | - Yedam Yoo
- Department of IT Convergence EngineeringKumoh National Institute of TechnologyGumiKorea
| | - Aroli Marcellinus
- Department of IT Convergence EngineeringKumoh National Institute of TechnologyGumiKorea
| | - Ki‐Suk Kim
- R&D Center for Advanced Pharmaceuticals and EvaluationKorea Institute of ToxicologyDaejeonKorea
| | - Ki Moo Lim
- Department of IT Convergence EngineeringKumoh National Institute of TechnologyGumiKorea
- Department of Medical IT Convergence EngineeringKumoh National Institute of TechnologyGumiKorea
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40
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Accurate in silico simulation of the rabbit Purkinje fiber electrophysiological assay to facilitate early pharmaceutical cardiosafety assessment: Dream or reality? J Pharmacol Toxicol Methods 2022; 115:107172. [DOI: 10.1016/j.vascn.2022.107172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/31/2022] [Accepted: 04/08/2022] [Indexed: 11/24/2022]
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41
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Integrative Computational Modeling of Cardiomyocyte Calcium Handling and Cardiac Arrhythmias: Current Status and Future Challenges. Cells 2022; 11:cells11071090. [PMID: 35406654 PMCID: PMC8997666 DOI: 10.3390/cells11071090] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/22/2022] [Accepted: 03/22/2022] [Indexed: 12/26/2022] Open
Abstract
Cardiomyocyte calcium-handling is the key mediator of cardiac excitation-contraction coupling. In the healthy heart, calcium controls both electrical impulse propagation and myofilament cross-bridge cycling, providing synchronous and adequate contraction of cardiac muscles. However, calcium-handling abnormalities are increasingly implicated as a cause of cardiac arrhythmias. Due to the complex, dynamic and localized interactions between calcium and other molecules within a cardiomyocyte, it remains experimentally challenging to study the exact contributions of calcium-handling abnormalities to arrhythmogenesis. Therefore, multiscale computational modeling is increasingly being used together with laboratory experiments to unravel the exact mechanisms of calcium-mediated arrhythmogenesis. This article describes various examples of how integrative computational modeling makes it possible to unravel the arrhythmogenic consequences of alterations to cardiac calcium handling at subcellular, cellular and tissue levels, and discusses the future challenges on the integration and interpretation of such computational data.
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42
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Occurrence of early afterdepolarization under healthy or hypertrophic cardiomyopathy conditions in the human ventricular endocardial myocyte: In silico study using 109 torsadogenic or non-torsadogenic compounds. Toxicol Appl Pharmacol 2022; 438:115914. [DOI: 10.1016/j.taap.2022.115914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 01/19/2022] [Accepted: 02/05/2022] [Indexed: 11/18/2022]
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Yoo Y, Marcellinus A, Jeong DU, Kim KS, Lim KM. Assessment of Drug Proarrhythmicity Using Artificial Neural Networks With in silico Deterministic Model Outputs. Front Physiol 2021; 12:761691. [PMID: 34955882 PMCID: PMC8703011 DOI: 10.3389/fphys.2021.761691] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 11/23/2021] [Indexed: 11/13/2022] Open
Abstract
As part of the Comprehensive in vitro Proarrhythmia Assay initiative, methodologies for predicting the occurrence of drug-induced torsade de pointes via computer simulations have been developed and verified recently. However, their predictive performance still requires improvement. Herein, we propose an artificial neural networks (ANN) model that uses nine multiple input features, considering the action potential morphology, calcium transient morphology, and charge features to further improve the performance of drug toxicity evaluation. The voltage clamp experimental data for 28 drugs were augmented to 2,000 data entries using an uncertainty quantification technique. By applying these data to the modified O'Hara Rudy in silico model, nine features (dVm/dtmax, APresting, APD90, APD50, Caresting, CaD90, CaD50, qNet, and qInward) were calculated. These nine features were used as inputs to an ANN model to classify drug toxicity into high-risk, intermediate-risk, and low-risk groups. The model was trained with data from 12 drugs and tested using the data of the remaining 16 drugs. The proposed ANN model demonstrated an AUC of 0.92 in the high-risk group, 0.83 in the intermediate-risk group, and 0.98 in the low-risk group. This was higher than the classification performance of the method proposed in previous studies.
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Affiliation(s)
- Yedam Yoo
- Computational Medicine Laboratory, Department of IT convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Aroli Marcellinus
- Computational Medicine Laboratory, Department of IT convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Da Un Jeong
- Computational Medicine Laboratory, Department of IT convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Ki-Suk Kim
- R&D Center for Advanced Pharmaceuticals and Evaluation, Korea Institute of Toxicology, Daejeon, South Korea
| | - Ki Moo Lim
- Computational Medicine Laboratory, Department of IT convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
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44
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Thomet U, Amuzescu B, Knott T, Mann SA, Mubagwa K, Radu BM. Assessment of proarrhythmogenic risk for chloroquine and hydroxychloroquine using the CiPA concept. Eur J Pharmacol 2021; 913:174632. [PMID: 34785211 PMCID: PMC8590616 DOI: 10.1016/j.ejphar.2021.174632] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 10/29/2021] [Accepted: 11/11/2021] [Indexed: 12/25/2022]
Abstract
Chloroquine and hydroxychloroquine have been proposed recently as therapy for SARS-CoV-2-infected patients, but during 3 months of extensive use concerns were raised related to their clinical effectiveness and arrhythmogenic risk. Therefore, we estimated for these compounds several proarrhythmogenic risk predictors according to the Comprehensive in vitro Proarrhythmia Assay (CiPA) paradigm. Experiments were performed with either CytoPatch™2 automated or manual patch-clamp setups on HEK293T cells stably or transiently transfected with hERG1, hNav1.5, hKir2.1, hKv7.1+hMinK, and on Pluricyte® cardiomyocytes (Ncardia), using physiological solutions. Dose-response plots of hERG1 inhibition fitted with Hill functions yielded IC50 values in the low micromolar range for both compounds. We found hyperpolarizing shifts of tens of mV, larger for chloroquine, in the voltage-dependent activation but not inactivation, as well as a voltage-dependent block of hERG current, larger at positive potentials. We also found inhibitory effects on peak and late INa and on IK1, with IC50 of tens of μM and larger for chloroquine. The two compounds, tested on Pluricyte® cardiomyocytes using the β-escin-perforated method, inhibited IKr, ICaL, INa peak, but had no effect on If. In current-clamp they caused action potential prolongation. Our data and those from literature for Ito were used to compute proarrhythmogenic risk predictors Bnet (Mistry HB, 2018) and Qnet (Dutta S et al., 2017), with hERG1 blocking/unblocking rates estimated from time constants of fractional block. Although the two antimalarials are successfully used in autoimmune diseases, and chloroquine may be effective in atrial fibrillation, assays place these drugs in the intermediate proarrhythmogenic risk group.
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Affiliation(s)
- Urs Thomet
- Anaxon A.G., Brünnenstrasse 90, 3018, Bern, Switzerland
| | - Bogdan Amuzescu
- Dept. Anatomy, Animal Physiology & Biophysics, Faculty of Biology, University of Bucharest, Splaiul Independentei 91-95, 050095, Bucharest, Romania.
| | - Thomas Knott
- CytoBioScience Inc., 3463 Magic Drive, San Antonio, TX, 78229, USA
| | - Stefan A Mann
- Cytocentrics Bioscience GmbH, Nattermannallee 1, 50829, Cologne, Germany
| | - Kanigula Mubagwa
- Dept. Cardiovascular Sciences, Faculty of Medicine, K U Leuven, B-3000, Leuven, Belgium; Dept. Basic Sciences, Faculty of Medicine, Université Catholique de Bukavu, Bukavu, DR Congo
| | - Beatrice Mihaela Radu
- Dept. Anatomy, Animal Physiology & Biophysics, Faculty of Biology, University of Bucharest, Splaiul Independentei 91-95, 050095, Bucharest, Romania
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Macrophage-Dependent Interleukin-6-Production and Inhibition of IK Contributes to Acquired QT Prolongation in Lipotoxic Guinea Pig Heart. Int J Mol Sci 2021; 22:ijms222011249. [PMID: 34681909 PMCID: PMC8537919 DOI: 10.3390/ijms222011249] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/08/2021] [Accepted: 10/16/2021] [Indexed: 11/17/2022] Open
Abstract
In the heart, the delayed rectifier K current, IK, composed of the rapid (IKr) and slow (IKs) components contributes prominently to normal cardiac repolarization. In lipotoxicity, chronic elevation of pro-inflammatory cytokines may remodel IK, elevating the risk for ventricular arrythmias and sudden cardiac death. We investigated whether and how the pro-inflammatory interleukin-6 altered IK in the heart, using electrophysiology to evaluate changes in IK in adult guinea pig ventricular myocytes. We found that palmitic acid (a potent inducer of lipotoxicity), induced a rapid (~24 h) and significant increase in IL-6 in RAW264.7 cells. PA-diet fed guinea pigs displayed a severely prolonged QT interval when compared to low-fat diet fed controls. Exposure to isoproterenol induced torsade de pointes, and ventricular fibrillation in lipotoxic guinea pigs. Pre-exposure to IL-6 with the soluble IL-6 receptor produced a profound depression of IKr and IKs densities, prolonged action potential duration, and impaired mitochondrial ATP production. Only with the inhibition of IKr did a proarrhythmic phenotype of IKs depression emerge, manifested as a further prolongation of action potential duration and QT interval. Our data offer unique mechanistic insights with implications for pathological QT interval in patients and vulnerability to fatal arrhythmias.
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46
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Qauli AI, Marcellinus A, Lim KM. Sensitivity Analysis of Ion Channel Conductance on Myocardial Electromechanical Delay: Computational Study. Front Physiol 2021; 12:697693. [PMID: 34512377 PMCID: PMC8430256 DOI: 10.3389/fphys.2021.697693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 07/29/2021] [Indexed: 02/03/2023] Open
Abstract
It is well known that cardiac electromechanical delay (EMD) can cause dyssynchronous heart failure (DHF), a prominent cardiovascular disease (CVD). This work computationally assesses the conductance variation of every ion channel on the cardiac cell to give rise to EMD prolongation. The electrical and mechanical models of human ventricular tissue were simulated, using a population approach with four conductance reductions for each ion channel. Then, EMD was calculated by determining the difference between the onset of action potential and the start of cell shortening. Finally, EMD data were put into the optimized conductance dimensional stacking to show which ion channel has the most influence in elongating the EMD. We found that major ion channels, such as L-type calcium (CaL), slow-delayed rectifier potassium (Ks), rapid-delayed rectifier potassium (Kr), and inward rectifier potassium (K1), can significantly extend the action potential duration (APD) up to 580 ms. Additionally, the maximum intracellular calcium (Cai) concentration is greatly affected by the reduction in channel CaL, Ks, background calcium, and Kr. However, among the aforementioned major ion channels, only the CaL channel can play a superior role in prolonging the EMD up to 83 ms. Furthermore, ventricular cells with long EMD have been shown to inherit insignificant mechanical response (in terms of how strong the tension can grow and how far length shortening can go) compared with that in normal cells. In conclusion, despite all variations in every ion channel conductance, only the CaL channel can play a significant role in extending EMD. In addition, cardiac cells with long EMD tend to have inferior mechanical responses due to a lack of Cai compared with normal conditions, which are highly likely to result in a compromised pump function of the heart.
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Affiliation(s)
- Ali Ikhsanul Qauli
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Aroli Marcellinus
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
| | - Ki Moo Lim
- Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea
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Pesti K, Földi MC, Zboray K, Toth AV, Lukacs P, Mike A. Characterization of Compound-Specific, Concentration-Independent Biophysical Properties of Sodium Channel Inhibitor Mechanism of Action Using Automated Patch-Clamp Electrophysiology. Front Pharmacol 2021; 12:738460. [PMID: 34497526 PMCID: PMC8419314 DOI: 10.3389/fphar.2021.738460] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 08/10/2021] [Indexed: 01/15/2023] Open
Abstract
We have developed an automated patch-clamp protocol that allows high information content screening of sodium channel inhibitor compounds. We have observed that individual compounds had their specific signature patterns of inhibition, which were manifested irrespective of the concentration. Our aim in this study was to quantify these properties. Primary biophysical data, such as onset rate, the shift of the half inactivation voltage, or the delay of recovery from inactivation, are concentration-dependent. We wanted to derive compound-specific properties, therefore, we had to neutralize the effect of concentration. This study describes how this is done, and shows how compound-specific properties reflect the mechanism of action, including binding dynamics, cooperativity, and interaction with the membrane phase. We illustrate the method using four well-known sodium channel inhibitor compounds, riluzole, lidocaine, benzocaine, and bupivacaine. Compound-specific biophysical properties may also serve as a basis for deriving parameters for kinetic modeling of drug action. We discuss how knowledge about the mechanism of action may help to predict the frequency-dependence of individual compounds, as well as their potential persistent current component selectivity. The analysis method described in this study, together with the experimental protocol described in the accompanying paper, allows screening for inhibitor compounds with specific kinetic properties, or with specific mechanisms of inhibition.
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Affiliation(s)
- Krisztina Pesti
- Department of Biochemistry, ELTE Eötvös Loránd University, Budapest, Hungary
- School of Ph.D. Studies, Semmelweis University, Budapest, Hungary
| | - Mátyás C. Földi
- Department of Biochemistry, ELTE Eötvös Loránd University, Budapest, Hungary
- Plant Protection Institute, Centre for Agricultural Research, Martonvásár, Hungary
| | - Katalin Zboray
- Plant Protection Institute, Centre for Agricultural Research, Martonvásár, Hungary
| | - Adam V. Toth
- Department of Biochemistry, ELTE Eötvös Loránd University, Budapest, Hungary
- Plant Protection Institute, Centre for Agricultural Research, Martonvásár, Hungary
| | - Peter Lukacs
- Department of Biochemistry, ELTE Eötvös Loránd University, Budapest, Hungary
- Plant Protection Institute, Centre for Agricultural Research, Martonvásár, Hungary
| | - Arpad Mike
- Department of Biochemistry, ELTE Eötvös Loránd University, Budapest, Hungary
- Plant Protection Institute, Centre for Agricultural Research, Martonvásár, Hungary
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48
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Goto A, Sakamoto K, Kambayashi R, Nunoi Y, Izumi-Nakaseko H, Kawai S, Takei Y, Matsumoto A, Kanda Y, Sugiyama A. Torsadogenic Action of Cisapride, dl-Sotalol, Bepridil, and Verapamil Analyzed by the Chronic Atrioventricular Block Cynomolgus Monkeys: Comparison With That Reported in the CiPA In Silico Mechanistic Model. Toxicol Sci 2021; 181:125-133. [PMID: 33544870 DOI: 10.1093/toxsci/kfab015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
In order to bridge the gap of information between the in silico model and human subjects, we evaluated torsadogenic risk of cisapride, dl-sotalol, bepridil and verapamil selected from 12 training compounds in the comprehensive in vitro proarrhythmia assay using the chronic atrioventricular block monkeys. Cisapride (0, 1, and 5 mg/kg, n = 5 for each dose), dl-sotalol (0, 1, 3, and 10 mg/kg, n = 5 for each dose), bepridil (0, 10, and 100 mg/kg, n = 4 for each dose), verapamil (0, 1.5, 15, and 75 mg/kg, n = 4 for each dose) were orally administered to the monkeys in conscious state. Five mg/kg of cisapride, 1, 3, and 10 mg/kg of dl-sotalol and 100 mg/kg of bepridil prolonged ΔΔQTcF, which was not observed by verapamil. Torsade de pointes was induced by 5 mg/kg of cisapride in 2 out of 5 animals, by 10 mg/kg of dl-sotalol in 5 out of 5 and by 100 mg/kg of bepridil in 2 out of 4, which was not induced by verapamil. These torsadogenic doses were normalized by their maximum clinical daily ones to estimate torsadogenic risk. The order of risk was dl-sotalol >bepridil ≥cisapride >verapamil in our study. Since the order was bepridil ≥dl-sotalol >cisapride >verapamil in comprehensive in vitro proarrhythmia assay (CiPA) in silico mechanistic model validation, sympathetic regulation on the heart may play a pivotal role in the onset of torsade de pointes in vivo.
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Affiliation(s)
- Ai Goto
- Department of Pharmacology, Toho University Graduate School of Medicine, Ota-ku, Tokyo 143-8540, Japan
| | - Kengo Sakamoto
- Safety Research Center Ina Research Inc., Ina-shi, Nagano 399-4501, Japan
| | - Ryuichi Kambayashi
- Department of Pharmacology, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
| | - Yoshio Nunoi
- Department of Pharmacology, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
| | - Hiroko Izumi-Nakaseko
- Department of Pharmacology, Toho University Graduate School of Medicine, Ota-ku, Tokyo 143-8540, Japan.,Department of Pharmacology, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
| | - Shinichi Kawai
- Department of Inflammation & Pain Control Research, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
| | - Yoshinori Takei
- Department of Translational Research & Cellular Therapeutics, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
| | - Akio Matsumoto
- Department of Aging Pharmacology, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
| | - Yasunari Kanda
- Division of Pharmacology, National Institute of Health Sciences, Kawasaki, Kanagawa 210-9501, Japan
| | - Atsushi Sugiyama
- Department of Pharmacology, Toho University Graduate School of Medicine, Ota-ku, Tokyo 143-8540, Japan.,Department of Pharmacology, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan.,Department of Inflammation & Pain Control Research, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan.,Department of Translational Research & Cellular Therapeutics, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan.,Department of Aging Pharmacology, Faculty of Medicine, Toho University, Ota-ku, Tokyo 143-8540, Japan
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49
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Charrez B, Charwat V, Siemons BA, Goswami I, Sakolish C, Luo YS, Finsberg H, Edwards AG, Miller EW, Rusyn I, Healy KE. Heart Muscle Microphysiological System for Cardiac Liability Prediction of Repurposed COVID-19 Therapeutics. Front Pharmacol 2021; 12:684252. [PMID: 34421592 PMCID: PMC8378272 DOI: 10.3389/fphar.2021.684252] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 07/05/2021] [Indexed: 12/27/2022] Open
Abstract
Despite global efforts, it took 7 months between the proclamation of global SARS-CoV-2 pandemic and the first FDA-approved treatment for COVID-19. During this timeframe, clinicians focused their efforts on repurposing drugs, such as hydroxychloroquine (HCQ) or azithromycin (AZM) to treat hospitalized COVID-19 patients. While clinical trials are time-consuming, the exponential increase in hospitalizations compelled the FDA to grant an emergency use authorization for HCQ and AZM as treatment for COVID-19, although there was limited evidence of their combined efficacy and safety. The authorization was revoked 4 months later, giving rise to controversial political and scientific debates illustrating important challenges such as premature authorization of potentially ineffective or unsafe therapeutics, while diverting resources from screening of effective drugs. Here we report on a preclinical drug screening platform, a cardiac microphysiological system (MPS), to rapidly identify clinically relevant cardiac liabilities associated with HCQ and AZM. The cardiac MPS is a microfabricated fluidic system in which cardiomyocytes derived from human induced pluripotent stem cells self-arrange into a uniaxially beating tissue. The drug response was measured using outputs that correlate with clinical measurements such as action potential duration (proxy for clinical QT interval) and drug-biomarker pairing. The cardiac MPS predicted clinical arrhythmias associated with QT prolongation and rhythm instabilities in tissues treated with HCQ. We found no change in QT interval upon acute exposure to AZM, while still observing a significant increase in arrhythmic events. These results suggest that this MPS can not only predict arrhythmias, but it can also identify arrhythmias even when QT prolongation is absent. When exposed to HCQ and AZM polytherapy, this MPS faithfully reflected clinical findings, in that the combination of drugs synergistically increased QT interval when compared to single drug exposure, while not worsening the overall frequency of arrhythmic events. The high content cardiac MPS can rapidly evaluate the cardiac safety of potential therapeutics, ultimately accelerating patients' access to safe and effective treatments.
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Affiliation(s)
- Bérénice Charrez
- Department of Bioengineering and California Institute for Quantitative Biosciences (QB3), University of California at Berkeley, Berkeley, CA, United States
| | - Verena Charwat
- Department of Bioengineering and California Institute for Quantitative Biosciences (QB3), University of California at Berkeley, Berkeley, CA, United States
| | - Brian A. Siemons
- Department of Bioengineering and California Institute for Quantitative Biosciences (QB3), University of California at Berkeley, Berkeley, CA, United States
| | - Ishan Goswami
- Department of Bioengineering and California Institute for Quantitative Biosciences (QB3), University of California at Berkeley, Berkeley, CA, United States
| | - Courtney Sakolish
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
| | - Yu-Syuan Luo
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
| | | | - Andrew G. Edwards
- Department of Pharmacology, School of Medicine, University of California at Davis, Davis, CA, United States
| | - Evan W. Miller
- Department of Chemistry, University of California at Berkeley, Berkeley, CA, United States
- Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, CA, United States
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA, United States
| | - Ivan Rusyn
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
| | - Kevin E. Healy
- Department of Bioengineering and California Institute for Quantitative Biosciences (QB3), University of California at Berkeley, Berkeley, CA, United States
- Department of Materials Science and Engineering, University of California at Berkeley, Berkeley, CA, United States
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50
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Choi SW, Yin MZ, Park NK, Woo JH, Kim SJ. Dual Mechanisms of Cardiac Action Potential Prolongation by 4-Oxo-Nonenal Increasing the Risk of Arrhythmia; Late Na + Current Induction and hERG K + Channel Inhibition. Antioxidants (Basel) 2021; 10:antiox10071139. [PMID: 34356372 PMCID: PMC8301175 DOI: 10.3390/antiox10071139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/13/2021] [Accepted: 07/15/2021] [Indexed: 11/16/2022] Open
Abstract
4-Oxo-nonenal (4-ONE) is an endogenous lipid peroxidation product that is more reactive than 4-hydroxy-nonenal (4-HNE). We previously reported the arrhythmic potential of 4-HNE by suppression of cardiac human Ether-a-go-go Related Gene (hERG) K+ channels with prolonged action potential duration (APD) in cardiomyocytes. Here, we illustrate the higher arrhythmic risk of 4-ONE by modulating the cardiac hNaV1.5 channel currents (INaV). Although the peak amplitude of INaV was not significantly changed by 4-ONE up to 10 μM, the rate of INaV inactivation was slowed, and the late Na+ current (INaL) became larger by 10 μM 4-ONE. The chemical modification of specific residues in hNaV1.5 by 4-ONE was identified using MS-fingerprinting analysis. In addition to the changes in INaV, 4-ONE decreased the delayed rectifier K+ channel currents including the hERG current. The L-type Ca2+ channel current was decreased, whereas its inactivation was slowed by 4-ONE. The APD prolongation by 10 μM of 4-ONE was more prominent than that by 100 μM of 4-HNE. In the computational in silico cardiomyocyte simulation analysis, the changes of INaL by 4-ONE significantly exacerbated the risk of arrhythmia exhibited by the TdP marker, qNet. Our study suggests an arrhythmogenic effect of 4-ONE on cardiac ion channels, especially hNaV1.5.
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Affiliation(s)
- Seong-Woo Choi
- Department of Physiology, Dongguk University College of Medicine, Gyeongju 38066, Korea; (S.-W.C.); (J.-H.W.)
| | - Ming-Zhe Yin
- Department of Physiology, Seoul National University College of Medicine, Seoul 03080, Korea; (M.-Z.Y.); (N.-K.P.)
- Department of Anesthesiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Na-Kyeong Park
- Department of Physiology, Seoul National University College of Medicine, Seoul 03080, Korea; (M.-Z.Y.); (N.-K.P.)
| | - Joo-Han Woo
- Department of Physiology, Dongguk University College of Medicine, Gyeongju 38066, Korea; (S.-W.C.); (J.-H.W.)
| | - Sung-Joon Kim
- Department of Physiology, Seoul National University College of Medicine, Seoul 03080, Korea; (M.-Z.Y.); (N.-K.P.)
- Correspondence: or ; Tel.: +82-2-740-8230
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