1
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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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2
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Fedida D, Sastre D, Dou Y, Westhoff M, Eldstrom J. Evaluating sequential and allosteric activation models in IKs channels with mutated voltage sensors. J Gen Physiol 2024; 156:e202313465. [PMID: 38294435 PMCID: PMC10829594 DOI: 10.1085/jgp.202313465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/30/2023] [Accepted: 01/03/2024] [Indexed: 02/01/2024] Open
Abstract
The ion-conducting IKs channel complex, important in cardiac repolarization and arrhythmias, comprises tetramers of KCNQ1 α-subunits along with 1-4 KCNE1 accessory subunits and calmodulin regulatory molecules. The E160R mutation in individual KCNQ1 subunits was used to prevent activation of voltage sensors and allow direct determination of transition rate data from complexes opening with a fixed number of 1, 2, or 4 activatable voltage sensors. Markov models were used to test the suitability of sequential versus allosteric models of IKs activation by comparing simulations with experimental steady-state and transient activation kinetics, voltage-sensor fluorescence from channels with two or four activatable domains, and limiting slope currents at negative potentials. Sequential Hodgkin-Huxley-type models approximately describe IKs currents but cannot explain an activation delay in channels with only one activatable subunit or the hyperpolarizing shift in the conductance-voltage relationship with more activatable voltage sensors. Incorporating two voltage sensor activation steps in sequential models and a concerted step in opening via rates derived from fluorescence measurements improves models but does not resolve fundamental differences with experimental data. Limiting slope current data that show the opening of channels at negative potentials and very low open probability are better simulated using allosteric models of activation with one transition per voltage sensor, which implies that movement of all four sensors is not required for IKs conductance. Tiered allosteric models with two activating transitions per voltage sensor can fully account for IKs current and fluorescence activation kinetics in constructs with different numbers of activatable voltage sensors.
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Affiliation(s)
- David Fedida
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Daniel Sastre
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Ying Dou
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Maartje Westhoff
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
| | - Jodene Eldstrom
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
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3
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Bhatt LK, Shah CR, Patel SD, Patel SR, Patel VA, Patel RJ, Joshi NM, Shah NA, Patel JH, Dwivedi P, Sundar R, Jain MR. A Retrospective Comparison of Electrocardiographic Parameters in Ketamine and Tiletamine-Zolazepam Anesthetized Indian Rhesus Monkeys ( Macaca mulatta). Int J Toxicol 2024; 43:184-195. [PMID: 38108647 DOI: 10.1177/10915818231221276] [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: 12/19/2023]
Abstract
Electrocardiographic evaluation is performed in rhesus monkeys to establish the cardiovascular safety of candidate molecules before progressing to clinical trials. These animals are usually immobilized chemically by ketamine (KTM) and tiletamine-zolazepam (TZ) to obtain a steady-state heart rate and to ensure adequate human safety. The present study aimed to evaluate the effect of these anesthetic regimens on different electrocardiographic parameters. Statistically significant lower HR and higher P-wave duration, RR, QRS, and QT intervals were observed in the KTM-anesthetized group in comparison to TZ-anesthetized animals. No significant changes were noticed in the PR interval and p-wave amplitude. Sex-based significance amongst these parameters was observed in male and female animals of TZ- and KTM-anesthetized groups. Regression analysis of four QTc formulas in TZ-anesthetized rhesus monkeys revealed that QTcNAK (Nakayama) better corrected the QT interval than QTcHAS (Hassimoto), QTcBZT (Bazett), and QTcFRD (Fridericia) formulas. QTcNAK exhibited the least correlation with the RR interval (slope closest to zero and r = .01) and displayed no statistical significance between male and female animals. These data will prove useful in the selection of anesthetic regimens for chemical restraint of rhesus monkeys in nonclinical safety evaluation studies.
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4
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Aguado-Sierra J, Brigham R, Baron AK, Gomez PD, Houzeaux G, Guerra JM, Carreras F, Filgueiras-Rama D, Vazquez M, Iaizzo PA, Iles TL, Butakoff C. HPC Framework for Performing in Silico Trials Using a 3D Virtual Human Cardiac Population as Means to Assess Drug-Induced Arrhythmic Risk. Methods Mol Biol 2024; 2716:307-334. [PMID: 37702946 DOI: 10.1007/978-1-0716-3449-3_14] [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: 09/14/2023]
Abstract
Following the 3 R's principles of animal research-replacement, reduction, and refinement-a high-performance computational framework was produced to generate a platform to perform human cardiac in-silico clinical trials as means to assess the pro-arrhythmic risk after the administrations of one or combination of two potentially arrhythmic drugs. The drugs assessed in this study were hydroxychloroquine and azithromycin. The framework employs electrophysiology simulations on high-resolution three-dimensional, biventricular human heart anatomies including phenotypic variabilities, so as to determine if differential QT-prolongation responds to drugs as observed clinically. These simulations also reproduce sex-specific ionic channel characteristics. The derived changes in the pseudo-electrocardiograms, calcium concentrations, as well as activation patterns within 3D geometries were evaluated for signs of induced arrhythmia. The virtual subjects could be evaluated at two different cycle lengths: at a normal heart rate and at a heart rate associated with stress as means to analyze the proarrhythmic risks after the administrations of hydroxychloroquine and azithromycin. Additionally, a series of experiments performed on reanimated swine hearts utilizing Visible Heart® methodologies in a four-chamber working heart model were performed to verify the arrhythmic behaviors observed in the in silico trials.The obtained results indicated similar pro-arrhythmic risk assessments within the virtual population as compared to published clinical trials (21% clinical risk vs 21.8% in silico trial risk). Evidence of transmurally heterogeneous action potential prolongations after providing a large dose of hydroxychloroquine was found as the observed mechanisms for elicited arrhythmias, both in the in vitro and the in silico models. The proposed workflow for in silico clinical drug cardiotoxicity trials allows for reproducing the complex behavior of cardiac electrophysiology in a varied population, in a matter of a few days as compared to the months or years it requires for most in vivo human clinical trials. Importantly, our results provided evidence of the common phenotype variants that produce distinct drug-induced arrhythmogenic outcomes.
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Affiliation(s)
- Jazmin Aguado-Sierra
- Barcelona Supercomputing Center, Barcelona, Spain.
- Elem Biotech S.L., Barcelona, Spain.
| | - Renee Brigham
- Visible Heart® Laboratories, Department of Surgery and the Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN, USA
| | | | | | | | - Jose M Guerra
- Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, CIBERCV, Barcelona, Spain
| | - Francesc Carreras
- Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, CIBERCV, Barcelona, Spain
| | - David Filgueiras-Rama
- Fundación Centro Nacional de Investigaciones Cardiovasculares (CNIC), Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), CIBERCV, Madrid, Spain
| | - Mariano Vazquez
- Barcelona Supercomputing Center, Barcelona, Spain
- Elem Biotech S.L., Barcelona, Spain
| | - Paul A Iaizzo
- Visible Heart® Laboratories, Department of Surgery and the Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Tinen L Iles
- Department of Surgery, Medical School, University of Minnesota, Minneapolis, MN, USA
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5
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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: a tool for more efficient computation in pharmacological studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.16.553497. [PMID: 38234850 PMCID: PMC10793461 DOI: 10.1101/2023.08.16.553497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
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 0.47mV in normal APs and of 14.5mV 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 0.21 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 Graz
- NAWI Graz, University of Graz
| | - Christoph M Augustin
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Medical Physics and Biophysics, Medical University of Graz
- BioTechMed-Graz
| | - Gundolf Haase
- Department of Mathematics and Scientific Computing, University of Graz
| | - Norbert Jost
- Department of Pharmacology and Pharmacotherapy, University of Szeged
- HUN-REN-TKI, Research Group of Pharmacology
| | - Gary R Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham
| | - Steven A Niederer
- Division of Imaging Sciences & Biomedical Engineering, King's College London
| | - Gernot Plank
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Medical Physics and Biophysics, Medical University of Graz
- BioTechMed-Graz
| | - András Varró
- Department of Pharmacology and Pharmacotherapy, University of Szeged
- HUN-REN-TKI, Research Group of Pharmacology
| | - László Virág
- Department of Pharmacology and Pharmacotherapy, University of Szeged
| | - Alexander Jung
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging - Division of Medical Physics and Biophysics, Medical University of Graz
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6
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Davies MR. Cardiac Safety Pharmacology Modeling. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11545-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
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7
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Raphel F, De Korte T, Lombardi D, Braam S, Gerbeau JF. A greedy classifier optimization strategy to assess ion channel blocking activity and pro-arrhythmia in hiPSC-cardiomyocytes. PLoS Comput Biol 2020; 16:e1008203. [PMID: 32976482 PMCID: PMC7549820 DOI: 10.1371/journal.pcbi.1008203] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 10/12/2020] [Accepted: 07/28/2020] [Indexed: 02/05/2023] Open
Abstract
Novel studies conducting cardiac safety assessment using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are promising but might be limited by their specificity and predictivity. It is often challenging to correctly classify ion channel blockers or to sufficiently predict the risk for Torsade de Pointes (TdP). In this study, we developed a method combining in vitro and in silico experiments to improve machine learning approaches in delivering fast and reliable prediction of drug-induced ion-channel blockade and proarrhythmic behaviour. The algorithm is based on the construction of a dictionary and a greedy optimization, leading to the definition of optimal classifiers. Finally, we present a numerical tool that can accurately predict compound-induced pro-arrhythmic risk and involvement of sodium, calcium and potassium channels, based on hiPSC-CM field potential data.
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Affiliation(s)
- Fabien Raphel
- Inria, Paris, France
- NOTOCORD part of Instem, Le Pecq, France
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8
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Davies MR, Martinec M, Walls R, Schwarz R, Mirams GR, Wang K, Steiner G, Surinach A, Flores C, Lavé T, Singer T, Polonchuk L. Use of Patient Health Records to Quantify Drug-Related Pro-arrhythmic Risk. CELL REPORTS MEDICINE 2020; 1:100076. [PMID: 33205069 PMCID: PMC7659582 DOI: 10.1016/j.xcrm.2020.100076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Revised: 06/09/2020] [Accepted: 07/29/2020] [Indexed: 12/30/2022]
Abstract
There is an increasing expectation that computational approaches may supplement existing human decision-making. Frontloading of models for cardiac safety prediction is no exception to this trend, and ongoing regulatory initiatives propose use of high-throughput in vitro data combined with computational models for calculating proarrhythmic risk. Evaluation of these models requires robust assessment of the outcomes. Using FDA Adverse Event Reporting System reports and electronic healthcare claims data from the Truven-MarketScan US claims database, we quantify the incidence rate of arrhythmia in patients and how this changes depending on patient characteristics. First, we propose that such datasets are a complementary resource for determining relative drug risk and assessing the performance of cardiac safety models for regulatory use. Second, the results suggest important determinants for appropriate stratification of patients and evaluation of additional drug risk in prescribing and clinical support algorithms and for precision health. In vitro data and computational models can assist with calculating pro-arrhythmic risk We use patient health records and FDA Adverse Event Reporting System reports Use of such datasets helps assess relative drug risk and cardiac safety models We quantify how patient characteristics can affect arrhythmia incidence
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Affiliation(s)
| | - Michael Martinec
- PHC Data Science, Personalized Healthcare, Product Development, F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Robert Walls
- PHC Data Science, Personalized Healthcare, Product Development, F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Roman Schwarz
- Safety Analytics and Reporting, Drug Safety, Pharmaceutical Development, F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Gary R Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK
| | - Ken Wang
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Guido Steiner
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland
| | | | | | - Thierry Lavé
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Thomas Singer
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Liudmila Polonchuk
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland
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9
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Hastings JF, O'Donnell YEI, Fey D, Croucher DR. Applications of personalised signalling network models in precision oncology. Pharmacol Ther 2020; 212:107555. [PMID: 32320730 DOI: 10.1016/j.pharmthera.2020.107555] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 04/07/2020] [Indexed: 02/07/2023]
Abstract
As our ability to provide in-depth, patient-specific characterisation of the molecular alterations within tumours rapidly improves, it is becoming apparent that new approaches will be required to leverage the power of this data and derive the full benefit for each individual patient. Systems biology approaches are beginning to emerge within this field as a potential method of incorporating large volumes of network level data and distilling a coherent, clinically-relevant prediction of drug response. However, the initial promise of this developing field is yet to be realised. Here we argue that in order to develop these precise models of individual drug response and tailor treatment accordingly, we will need to develop mathematical models capable of capturing both the dynamic nature of drug-response signalling networks and key patient-specific information such as mutation status or expression profiles. We also review the modelling approaches commonly utilised within this field, and outline recent examples of their use in furthering the application of systems biology for a precision medicine approach to cancer treatment.
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Affiliation(s)
- Jordan F Hastings
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Sydney, Australia
| | | | - Dirk Fey
- Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland; School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - David R Croucher
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Sydney, Australia; School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland; St Vincent's Hospital Clinical School, University of New South Wales, Sydney, NSW 2052, Australia.
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10
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Bai J, Lu Y, Zhang H. In silico study of the effects of anti-arrhythmic drug treatment on sinoatrial node function for patients with atrial fibrillation. Sci Rep 2020; 10:305. [PMID: 31941982 PMCID: PMC6962222 DOI: 10.1038/s41598-019-57246-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 12/23/2019] [Indexed: 12/21/2022] Open
Abstract
Sinus node dysfunction (SND) is often associated with atrial fibrillation (AF). Amiodarone is the most frequently used agent for maintaining sinus rhythm in patients with AF, but it impairs the sinoatrial node (SAN) function in one-third of AF patients. This study aims to gain mechanistic insights into the effects of the antiarrhythmic agents in the setting of AF-induced SND. We have adapted a human SAN model to characterize the SND conditions by incorporating experimental data on AF-induced electrical remodelling, and then integrated actions of drugs into the modified model to assess their efficacy. Reductions in pacing rate upon the implementation of AF-induced electrical remodelling associated with SND agreed with the clinical observations. And the simulated results showed the reduced funny current (If) in these remodelled targets mainly contributed to the heart rate reduction. Computational drug treatment simulations predicted a further reduction in heart rate during amiodarone administration, indicating that the reduction was the result of actions of amiodarone on INa, IKur, ICaL, ICaT, If and beta-adrenergic receptors. However, the heart rate was increased in the presence of disopyramide. We concluded that disopyramide may be a desirable choice in reversing the AF-induced SND phenotype.
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Affiliation(s)
- Jieyun Bai
- Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou, China.
| | - Yaosheng Lu
- Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Henggui Zhang
- Biological Physics Group, School of Physics & Astronomy, The University of Manchester, Manchester, United Kingdom.
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11
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Clerx M, Beattie KA, Gavaghan DJ, Mirams GR. Four Ways to Fit an Ion Channel Model. Biophys J 2019; 117:2420-2437. [PMID: 31493859 PMCID: PMC6990153 DOI: 10.1016/j.bpj.2019.08.001] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 06/20/2019] [Accepted: 08/01/2019] [Indexed: 12/16/2022] Open
Abstract
Mathematical models of ionic currents are used to study the electrophysiology of the heart, brain, gut, and several other organs. Increasingly, these models are being used predictively in the clinic, for example, to predict the risks and results of genetic mutations, pharmacological treatments, or surgical procedures. These safety-critical applications depend on accurate characterization of the underlying ionic currents. Four different methods can be found in the literature to fit voltage-sensitive ion channel models to whole-cell current measurements: method 1, fitting model equations directly to time-constant, steady-state, and I-V summary curves; method 2, fitting by comparing simulated versions of these summary curves to their experimental counterparts; method 3, fitting to the current traces themselves from a range of protocols; and method 4, fitting to a single current trace from a short and rapidly fluctuating voltage-clamp protocol. We compare these methods using a set of experiments in which hERG1a current was measured in nine Chinese hamster ovary cells. In each cell, the same sequence of fitting protocols was applied, as well as an independent validation protocol. We show that methods 3 and 4 provide the best predictions on the independent validation set and that short, rapidly fluctuating protocols like that used in method 4 can replace much longer conventional protocols without loss of predictive ability. Although data for method 2 are most readily available from the literature, we find it performs poorly compared to methods 3 and 4 both in accuracy of predictions and computational efficiency. Our results demonstrate how novel experimental and computational approaches can improve the quality of model predictions in safety-critical applications.
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Affiliation(s)
- Michael Clerx
- Computational Biology & Health Informatics, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Kylie A Beattie
- Computational Biology & Health Informatics, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - David J Gavaghan
- Computational Biology & Health Informatics, Department of Computer Science, 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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12
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Okada JI, Yoshinaga T, Kurokawa J, Washio T, Furukawa T, Sawada K, Sugiura S, Hisada T. Arrhythmic hazard map for a 3D whole-ventricle model under multiple ion channel block. Br J Pharmacol 2018; 175:3435-3452. [PMID: 29745425 PMCID: PMC6086978 DOI: 10.1111/bph.14357] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2017] [Revised: 03/12/2018] [Accepted: 04/20/2018] [Indexed: 01/05/2023] Open
Abstract
Background and Purpose To date, proposed in silico models for preclinical cardiac safety testing are limited in their predictability and usability. We previously reported a multi‐scale heart simulation that accurately predicts arrhythmogenic risk for benchmark drugs. Experimental Approach We created a comprehensive hazard map of drug‐induced arrhythmia based on the electrocardiogram (ECG) waveforms simulated under wide range of drug effects using the multi‐scale heart simulator described here, implemented with cell models of human cardiac electrophysiology. Key Results A total of 9075 electrocardiograms constitute the five‐dimensional hazard map, with coordinates representing the extent of the block of each of the five ionic currents (rapid delayed rectifier potassium current (IKr), fast (INa) and late (INa,L) components of the sodium current, L‐type calcium current (ICa,L) and slow delayed rectifier current (IKs)), involved in arrhythmogenesis. Results of the evaluation of arrhythmogenic risk based on this hazard map agreed well with the risk assessments reported in the literature. ECG databases also suggested that the interval between the J‐point and the T‐wave peak is a superior index of arrhythmogenicity when compared to the QT interval due to its ability to characterize the multi‐channel effects compared with QT interval. Conclusion and Implications Because concentration‐dependent effects on electrocardiograms of any drug can be traced on this map based on in vitro current assay data, its arrhythmogenic risk can be evaluated without performing costly and potentially risky human electrophysiological assays. Hence, the map serves as a novel tool for use in pharmaceutical research and development.
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Affiliation(s)
- Jun-Ichi Okada
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.,UT-Heart Inc., Tokyo, Japan
| | | | - Junko Kurokawa
- School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Takumi Washio
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.,UT-Heart Inc., Tokyo, Japan
| | - Tetsushi Furukawa
- Department of Bio-informational Pharmacology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan
| | - Kohei Sawada
- Global CV Assessment, Eisai Co., Ltd., Ibaraki, Japan
| | - Seiryo Sugiura
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.,UT-Heart Inc., Tokyo, Japan
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Romero L, Cano J, Gomis-Tena J, Trenor B, Sanz F, Pastor M, Saiz J. In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk. J Chem Inf Model 2018; 58:867-878. [PMID: 29547274 DOI: 10.1021/acs.jcim.7b00440] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Drug-induced proarrhythmicity is a major concern for regulators and pharmaceutical companies. For novel drug candidates, the standard assessment involves the evaluation of the potassium hERG channels block and the in vivo prolongation of the QT interval. However, this method is known to be too restrictive and to stop the development of potentially valuable therapeutic drugs. The aim of this work is to create an in silico tool for early detection of drug-induced proarrhythmic risk. The system is based on simulations of how different compounds affect the action potential duration (APD) of isolated endocardial, midmyocardial, and epicardial cells as well as the QT prolongation in a virtual tissue. Multiple channel-drug interactions and state-of-the-art human ventricular action potential models ( O'Hara , T. , PLos Comput. Biol. 2011 , 7 , e1002061 ) were used in our simulations. Specifically, 206.766 cellular and 7072 tissue simulations were performed by blocking the slow and the fast components of the delayed rectifier current ( IKs and IKr, respectively) and the L-type calcium current ( ICaL) at different levels. The performance of our system was validated by classifying the proarrhythmic risk of 84 compounds, 40 of which present torsadogenic properties. On the basis of these results, we propose the use of a new index (Tx) for discriminating torsadogenic compounds, defined as the ratio of the drug concentrations producing 10% prolongation of the cellular endocardial, midmyocardial, and epicardial APDs and the QT interval, over the maximum effective free therapeutic plasma concentration (EFTPC). Our results show that the Tx index outperforms standard methods for early identification of torsadogenic compounds. Indeed, for the analyzed compounds, the Tx tests accuracy was in the range of 87-88% compared with a 73% accuracy of the hERG IC50 based test.
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Affiliation(s)
- Lucia Romero
- Centro de Investigación e Innovación en Bioingeniería (CI2B) , Universitat Politècnica de València , camino de Vera, s/n , 46022 Valencia , Spain
| | - Jordi Cano
- Centro de Investigación e Innovación en Bioingeniería (CI2B) , Universitat Politècnica de València , camino de Vera, s/n , 46022 Valencia , Spain
| | - Julio Gomis-Tena
- Centro de Investigación e Innovación en Bioingeniería (CI2B) , Universitat Politècnica de València , camino de Vera, s/n , 46022 Valencia , Spain
| | - Beatriz Trenor
- Centro de Investigación e Innovación en Bioingeniería (CI2B) , Universitat Politècnica de València , camino de Vera, s/n , 46022 Valencia , Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics (GRIB), Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Department of Experimental and Health Sciences , Universitat Pompeu Fabra , Carrer del Dr. Aiguader 88 , 08002 Barcelona , Spain
| | - Manuel Pastor
- Research Programme on Biomedical Informatics (GRIB), Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Department of Experimental and Health Sciences , Universitat Pompeu Fabra , Carrer del Dr. Aiguader 88 , 08002 Barcelona , Spain
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (CI2B) , Universitat Politècnica de València , camino de Vera, s/n , 46022 Valencia , Spain
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14
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Tixier E, Raphel F, Lombardi D, Gerbeau JF. Composite Biomarkers Derived from Micro-Electrode Array Measurements and Computer Simulations Improve the Classification of Drug-Induced Channel Block. Front Physiol 2018; 8:1096. [PMID: 29354067 PMCID: PMC5762138 DOI: 10.3389/fphys.2017.01096] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 12/13/2017] [Indexed: 12/19/2022] Open
Abstract
The Micro-Electrode Array (MEA) device enables high-throughput electrophysiology measurements that are less labor-intensive than patch-clamp based techniques. Combined with human-induced pluripotent stem cells cardiomyocytes (hiPSC-CM), it represents a new and promising paradigm for automated and accurate in vitro drug safety evaluation. In this article, the following question is addressed: which features of the MEA signals should be measured to better classify the effects of drugs? A framework for the classification of drugs using MEA measurements is proposed. The classification is based on the ion channels blockades induced by the drugs. It relies on an in silico electrophysiology model of the MEA, a feature selection algorithm and automatic classification tools. An in silico model of the MEA is developed and is used to generate synthetic measurements. An algorithm that extracts MEA measurements features designed to perform well in a classification context is described. These features are called composite biomarkers. A state-of-the-art machine learning program is used to carry out the classification of drugs using experimental MEA measurements. The experiments are carried out using five different drugs: mexiletine, flecainide, diltiazem, moxifloxacin, and dofetilide. We show that the composite biomarkers outperform the classical ones in different classification scenarios. We show that using both synthetic and experimental MEA measurements improves the robustness of the composite biomarkers and that the classification scores are increased.
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Affiliation(s)
- Eliott Tixier
- Inria Paris, Paris, France.,Sorbonne Universités, Université Pierre et Marie Curie-Paris 6, UMR 7598 LJLL, Paris, France
| | - Fabien Raphel
- Inria Paris, Paris, France.,Sorbonne Universités, Université Pierre et Marie Curie-Paris 6, UMR 7598 LJLL, Paris, France
| | - Damiano Lombardi
- Inria Paris, Paris, France.,Sorbonne Universités, Université Pierre et Marie Curie-Paris 6, UMR 7598 LJLL, Paris, France
| | - Jean-Frédéric Gerbeau
- Inria Paris, Paris, France.,Sorbonne Universités, Université Pierre et Marie Curie-Paris 6, UMR 7598 LJLL, Paris, France
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15
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McMillan B, Gavaghan DJ, Mirams GR. Early afterdepolarisation tendency as a simulated pro-arrhythmic risk indicator. Toxicol Res (Camb) 2017; 6:912-921. [PMID: 29456831 PMCID: PMC5779076 DOI: 10.1039/c7tx00141j] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 09/12/2017] [Indexed: 12/19/2022] Open
Abstract
Drug-induced Torsades de Pointes (TdP) arrhythmia is of major interest in predictive toxicology. Drugs which cause TdP block the hERG cardiac potassium channel. However, not all drugs that block hERG cause TdP. As such, further understanding of the mechanistic route to TdP is needed. Early afterdepolarisations (EADs) are a cell-level phenomenon in which the membrane of a cardiac cell depolarises a second time before repolarisation, and EADs are seen in hearts during TdP. Therefore, we propose a method of predicting TdP using induced EADs combined with multiple ion channel block in simulations using biophysically-based mathematical models of human ventricular cell electrophysiology. EADs were induced in cardiac action potential models using interventions based on diseases that are known to cause EADs, including: increasing the conduction of the L-type calcium channel, decreasing the conduction of the hERG channel, and shifting the inactivation curve of the fast sodium channel. The threshold of intervention that was required to cause an EAD was used to classify drugs into clinical risk categories. The metric that used L-type calcium induced EADs was the most accurate of the EAD metrics at classifying drugs into the correct risk categories, and increased in accuracy when combined with action potential duration measurements. The EAD metrics were all more accurate than hERG block alone, but not as predictive as simpler measures such as simulated action potential duration. This may be because different routes to EADs represent risk well for different patient subgroups, something that is difficult to assess at present.
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Affiliation(s)
- Beth McMillan
- Computational Biology , Dept. of Computer Science , University of Oxford , Oxford , OX1 3QD , UK . ; ; Tel: +44 (0)1865 273838
| | - David J Gavaghan
- Computational Biology , Dept. of Computer Science , University of Oxford , Oxford , OX1 3QD , UK . ; ; Tel: +44 (0)1865 273838
| | - Gary R Mirams
- Centre for Mathematical Biology , School of Mathematical Sciences , University of Nottingham , Nottingham , NG7 2RD , UK
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16
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Abbate E, Boulakia M, Coudière Y, Gerbeau JF, Zitoun P, Zemzemi N. In silico assessment of the effects of various compounds in MEA/hiPSC-CM assays: Modeling and numerical simulations. J Pharmacol Toxicol Methods 2017; 89:59-72. [PMID: 29066291 DOI: 10.1016/j.vascn.2017.10.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 06/05/2017] [Accepted: 10/14/2017] [Indexed: 01/29/2023]
Abstract
We propose a mathematical approach for the analysis of drugs effects on the electrical activity of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) based on multi-electrode array (MEA) experiments. Our goal is to produce an in silico tool able to simulate drugs action in MEA/hiPSC-CM assays. The mathematical model takes into account the geometry of the MEA and the electrodes' properties. The electrical activity of the stem cells at the ion-channel level is governed by a system of ordinary differential equations (ODEs). The ODEs are coupled to the bidomain equations, describing the propagation of the electrical wave in the stem cells preparation. The field potential (FP) measured by the MEA is modeled by the extracellular potential of the bidomain equations. First, we propose a strategy allowing us to generate a field potential in good agreement with the experimental data. We show that we are able to reproduce realistic field potentials by introducing different scenarios of heterogeneity in the action potential. This heterogeneity reflects the differentiation atria/ventricles and the age of the cells. Second, we introduce a drug/ion channels interaction based on a pore block model. We conduct different simulations for five drugs (mexiletine, dofetilide, bepridil, ivabradine and BayK). We compare the simulation results with the field potential collected from experimental measurements. Different biomarkers computed on the FP are considered, including depolarization amplitude, repolarization delay, repolarization amplitude and depolarization-repolarization segment. The simulation results show that the model reflect properly the main effects of these drugs on the FP.
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Affiliation(s)
- Emanuela Abbate
- Università degli Studi dell'Insubria, via Valleggio, Como 22100, Italy; Université de Bordeaux and IMB, UMR 5251, F-33400 Talence, France
| | | | - Yves Coudière
- Inria Bordeaux, Université de Bordeaux and IMB, UMR 5251, F-33400 Talence, France
| | | | | | - Nejib Zemzemi
- Inria Bordeaux, Université de Bordeaux and IMB, UMR 5251, F-33400 Talence, France.
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17
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Passini E, Britton OJ, Lu HR, Rohrbacher J, Hermans AN, Gallacher DJ, Greig RJH, Bueno-Orovio A, Rodriguez B. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity. Front Physiol 2017; 8:668. [PMID: 28955244 PMCID: PMC5601077 DOI: 10.3389/fphys.2017.00668] [Citation(s) in RCA: 168] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Accepted: 08/23/2017] [Indexed: 01/08/2023] Open
Abstract
Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na+ and Ca2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca2+-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.
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Affiliation(s)
- Elisa Passini
- Computational Cardiovascular Science Group, Department of Computer Science, University of OxfordOxford, United Kingdom
| | - Oliver J Britton
- Computational Cardiovascular Science Group, Department of Computer Science, University of OxfordOxford, United Kingdom
| | - Hua Rong Lu
- Global Safety, Pharmacology, Discovery Sciences, Janssen Research and Development, Janssen Pharmaceutica NVBeerse, Belgium
| | - Jutta Rohrbacher
- Global Safety, Pharmacology, Discovery Sciences, Janssen Research and Development, Janssen Pharmaceutica NVBeerse, Belgium
| | - An N Hermans
- Global Safety, Pharmacology, Discovery Sciences, Janssen Research and Development, Janssen Pharmaceutica NVBeerse, Belgium
| | - David J Gallacher
- Global Safety, Pharmacology, Discovery Sciences, Janssen Research and Development, Janssen Pharmaceutica NVBeerse, Belgium
| | | | - Alfonso Bueno-Orovio
- Computational Cardiovascular Science Group, Department of Computer Science, University of OxfordOxford, United Kingdom
| | - Blanca Rodriguez
- Computational Cardiovascular Science Group, Department of Computer Science, University of OxfordOxford, United Kingdom
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18
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Lee S. Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine. J Pharmacopuncture 2015; 18:11-8. [PMID: 26388998 PMCID: PMC4573803 DOI: 10.3831/kpi.2015.18.020] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Accepted: 08/31/2015] [Indexed: 12/14/2022] Open
Abstract
Objectives: Systems biology is a novel subject in the field of life science that aims at a systems’ level understanding of biological systems. Because of the significant progress in high-throughput technologies and molecular biology, systems biology occupies an important place in research during the post-genome era. Methods: The characteristics of systems biology and its applicability to traditional medicine research have been discussed from three points of view: data and databases, network analysis and inference, and modeling and systems prediction. Results: The existing databases are mostly associated with medicinal herbs and their activities, but new databases reflecting clinical situations and platforms to extract, visualize and analyze data easily need to be constructed. Network pharmacology is a key element of systems biology, so addressing the multi-component, multi-target aspect of pharmacology is important. Studies of network pharmacology highlight the drug target network and network target. Mathematical modeling and simulation are just in their infancy, but mathematical modeling of dynamic biological processes is a central aspect of systems biology. Computational simulations allow structured systems and their functional properties to be understood and the effects of herbal medicines in clinical situations to be predicted. Conclusion: Systems biology based on a holistic approach is a pivotal research methodology for understanding the mechanisms of traditional medicine. If systems biology is to be incorporated into traditional medicine, computational technologies and holistic insights need to be integrated.
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Affiliation(s)
- Soojin Lee
- Department of Physiology, College of Korean Medicine, Sangji University, Wonju, Korea
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19
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Okada JI, Yoshinaga T, Kurokawa J, Washio T, Furukawa T, Sawada K, Sugiura S, Hisada T. Screening system for drug-induced arrhythmogenic risk combining a patch clamp and heart simulator. SCIENCE ADVANCES 2015; 1:e1400142. [PMID: 26601174 PMCID: PMC4640654 DOI: 10.1126/sciadv.1400142] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2014] [Accepted: 04/04/2015] [Indexed: 05/31/2023]
Abstract
To save time and cost for drug discovery, a paradigm shift in cardiotoxicity testing is required. We introduce a novel screening system for drug-induced arrhythmogenic risk that combines in vitro pharmacological assays and a multiscale heart simulator. For 12 drugs reported to have varying cardiotoxicity risks, dose-inhibition curves were determined for six ion channels using automated patch clamp systems. By manipulating the channel models implemented in a heart simulator consisting of more than 20 million myocyte models, we simulated a standard electrocardiogram (ECG) under various doses of drugs. When the drug concentrations were increased from therapeutic levels, each drug induced a concentration-dependent characteristic type of ventricular arrhythmia, whereas no arrhythmias were observed at any dose with drugs known to be safe. We have shown that our system combining in vitro and in silico technologies can predict drug-induced arrhythmogenic risk reliably and efficiently.
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Affiliation(s)
- Jun-ichi Okada
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
- UT-Heart Inc., 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003, Japan
| | - Takashi Yoshinaga
- Global CV Assessment, Eisai Co. Ltd., Tokodai 5-1-3, Tsukua-shi, Ibaraki 300-2635, Japan
| | - Junko Kurokawa
- Department of Bio-informational Pharmacology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Takumi Washio
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
- UT-Heart Inc., 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003, Japan
| | - Tetsushi Furukawa
- Department of Bio-informational Pharmacology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Kohei Sawada
- Global CV Assessment, Eisai Co. Ltd., Tokodai 5-1-3, Tsukua-shi, Ibaraki 300-2635, Japan
| | - Seiryo Sugiura
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
- UT-Heart Inc., 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003, Japan
| | - Toshiaki Hisada
- Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
- UT-Heart Inc., 3-25-8 Nozawa, Setagaya-ku, Tokyo 154-0003, Japan
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20
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Yuan Y, Bai X, Luo C, Wang K, Zhang H. The virtual heart as a platform for screening drug cardiotoxicity. Br J Pharmacol 2015; 172:5531-47. [PMID: 25363597 PMCID: PMC4667856 DOI: 10.1111/bph.12996] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2014] [Revised: 10/23/2014] [Accepted: 10/28/2014] [Indexed: 01/01/2023] Open
Abstract
To predict the safety of a drug at an early stage in its development is a major challenge as there is a lack of in vitro heart models that correlate data from preclinical toxicity screening assays with clinical results. A biophysically detailed computer model of the heart, the virtual heart, provides a powerful tool for simulating drug–ion channel interactions and cardiac functions during normal and disease conditions and, therefore, provides a powerful platform for drug cardiotoxicity screening. In this article, we first review recent progress in the development of theory on drug–ion channel interactions and mathematical modelling. Then we propose a family of biomarkers that can quantitatively characterize the actions of a drug on the electrical activity of the heart at multi‐physical scales including cellular and tissue levels. We also conducted some simulations to demonstrate the application of the virtual heart to assess the pro‐arrhythmic effects of cisapride and amiodarone. Using the model we investigated the mechanisms responsible for the differences between the two drugs on pro‐arrhythmogenesis, even though both prolong the QT interval of ECGs. Several challenges for further development of a virtual heart as a platform for screening drug cardiotoxicity are discussed. Linked Articles This article is part of a themed section on Chinese Innovation in Cardiovascular Drug Discovery. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2015.172.issue-23
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Affiliation(s)
- Yongfeng Yuan
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Xiangyun Bai
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Cunjin Luo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Kuanquan Wang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Henggui Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.,Biological Physics Group, School of Physics and Astronomy, The University of Manchester, Manchester, UK
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21
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Wiśniowska B, Mendyk A, Fijorek K, Polak S. Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges. Europace 2015; 16:724-35. [PMID: 24798962 DOI: 10.1093/europace/euu009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
It is likely that computer modelling and simulations will become an element of comprehensive cardiac safety testing. Their role would be primarily the integration and the interpretation of previously gathered data. There are still unanswered questions and issues which we list and describe below. They include sources of data used for the development of the models as well as data utilized as input information, which can come from the in vitro studies and the quantitative structure-activity relationship models. The pharmacokinetics of the drugs in question play a crucial role as their active concentration should be considered, yet the question remains where is the right place to assess it. The pharmacodynamic angle includes complications coming from multiple drugs (i.e. active metabolites) acting in parallel as well as the type of interaction with (potentially) multiple affected channels. Once established, the model and the methodology of its use should be further validated, optimistically against individual data reported at the clinical level as the physiological, anatomical, and genetic parameters play a crucial role in the drug-triggered arrhythmia induction. All the abovementioned issues should be at least considered and-hopefully-resolved, to properly utilize the mathematical models for a cardiac safety assessment.
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Affiliation(s)
- Barbara Wiśniowska
- Unit of Pharmacoepidemiology and Pharmacoeconomics, Faculty of Pharmacy, Medical College, Jagiellonian University, Medyczna 9 Street, 30-688 Kraków, Poland
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22
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Chain ASY, Sturkenboom MCJM, Danhof M, Della Pasqua OE. Establishing in vitro to clinical correlations in the evaluation of cardiovascular safety pharmacology. DRUG DISCOVERY TODAY. TECHNOLOGIES 2013; 10:e373-e383. [PMID: 24050134 DOI: 10.1016/j.ddtec.2012.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Preclinical studies are vital in establishing the efficacy and safety of a new chemical entity (NCE) in humans. To deliver meaningful information, experiments have to be well defined and provide outcome that is relevant and translatable to humans. This review briefly surveys the various preclinical experiments that are frequently conducted to assess drug effects on cardiac conductivity in early drug development. We examine the different approaches used to establish correlations between non-clinical and clinical settings and discuss their value in the evaluation of cardiovascular risk.
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23
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Beattie KA, Luscombe C, Williams G, Munoz-Muriedas J, Gavaghan DJ, Cui Y, Mirams GR. Evaluation of an in silico cardiac safety assay: using ion channel screening data to predict QT interval changes in the rabbit ventricular wedge. J Pharmacol Toxicol Methods 2013; 68:88-96. [PMID: 23624022 PMCID: PMC4142193 DOI: 10.1016/j.vascn.2013.04.004] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2013] [Revised: 04/08/2013] [Accepted: 04/17/2013] [Indexed: 12/22/2022]
Abstract
INTRODUCTION Drugs that prolong the QT interval on the electrocardiogram present a major safety concern for pharmaceutical companies and regulatory agencies. Despite a range of assays performed to assess compound effects on the QT interval, QT prolongation remains a major cause of attrition during compound development. In silico assays could alleviate such problems. In this study we evaluated an in silico method of predicting the results of a rabbit left-ventricular wedge assay. METHODS Concentration-effect data were acquired from either: the high-throughput IonWorks/FLIPR; the medium-throughput PatchXpress ion channel assays; or QSAR, a statistical IC50 value prediction model, for hERG, fast sodium, L-type calcium and KCNQ1/minK channels. Drug block of channels was incorporated into a mathematical differential equation model of rabbit ventricular myocyte electrophysiology through modification of the maximal conductance of each channel by a factor dependent on the IC50 value, Hill coefficient and concentration of each compound tested. Simulations were performed and agreement with experimental results, based upon input data from the different assays, was evaluated. RESULTS The assay was found to be 78% accurate, 72% sensitive and 81% specific when predicting QT prolongation (>10%) using PatchXpress assay data (77 compounds). Similar levels of predictivity were demonstrated using IonWorks/FLIPR data (121 compounds) with 78% accuracy, 73% sensitivity and 80% specificity. QT shortening (<-10%) was predicted with 77% accuracy, 33% sensitivity and 90% specificity using PatchXpress data and 71% accuracy, 42% sensitivity and 81% specificity using IonWorks/FLIPR data. Strong quantitative agreement between simulation and experimental results was also evident. DISCUSSION The in silico action potential assay demonstrates good predictive ability, and is suitable for very high-throughput use in early drug development. Adoption of such an assay into cardiovascular safety assessment, integrating ion channel data from routine screens to infer results of animal-based tests, could provide a cost- and time-effective cardiac safety screen.
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Affiliation(s)
- Kylie A Beattie
- Computational Biology, Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK.
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24
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Quinn TA, Kohl P. Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies. Cardiovasc Res 2013; 97:601-11. [PMID: 23334215 PMCID: PMC3583260 DOI: 10.1093/cvr/cvt003] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2012] [Revised: 01/08/2013] [Accepted: 01/15/2013] [Indexed: 11/17/2022] Open
Abstract
Since the development of the first mathematical cardiac cell model 50 years ago, computational modelling has become an increasingly powerful tool for the analysis of data and for the integration of information related to complex cardiac behaviour. Current models build on decades of iteration between experiment and theory, representing a collective understanding of cardiac function. All models, whether computational, experimental, or conceptual, are simplified representations of reality and, like tools in a toolbox, suitable for specific applications. Their range of applicability can be explored (and expanded) by iterative combination of 'wet' and 'dry' investigation, where experimental or clinical data are used to first build and then validate computational models (allowing integration of previous findings, quantitative assessment of conceptual models, and projection across relevant spatial and temporal scales), while computational simulations are utilized for plausibility assessment, hypotheses-generation, and prediction (thereby defining further experimental research targets). When implemented effectively, this combined wet/dry research approach can support the development of a more complete and cohesive understanding of integrated biological function. This review illustrates the utility of such an approach, based on recent examples of multi-scale studies of cardiac structure and mechano-electric function.
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Affiliation(s)
- T Alexander Quinn
- National Heart and Lung Institute, Imperial College London, Heart Science Centre, Harefield UB9 6JH, UK.
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Mirams GR, Davies MR, Cui Y, Kohl P, Noble D. Application of cardiac electrophysiology simulations to pro-arrhythmic safety testing. Br J Pharmacol 2012; 167:932-45. [PMID: 22568589 PMCID: PMC3492977 DOI: 10.1111/j.1476-5381.2012.02020.x] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2011] [Revised: 03/23/2012] [Accepted: 04/26/2012] [Indexed: 12/19/2022] Open
Abstract
Concerns over cardiac side effects are the largest single cause of compound attrition during pharmaceutical drug development. For a number of years, biophysically detailed mathematical models of cardiac electrical activity have been used to explore how a compound, interfering with specific ion-channel function, may explain effects at the cell-, tissue- and organ-scales. With the advent of high-throughput screening of multiple ion channels in the wet-lab, and improvements in computational modelling of their effects on cardiac cell activity, more reliable prediction of pro-arrhythmic risk is becoming possible at the earliest stages of drug development. In this paper, we review the current use of biophysically detailed mathematical models of cardiac myocyte electrical activity in drug safety testing, and suggest future directions to employ the full potential of this approach.
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Affiliation(s)
- Gary R Mirams
- Computational Biology, Department of Computer Science, University of OxfordOxford, UK
| | - Mark R Davies
- Computational Biology, Discovery SciencesAstraZeneca, Alderley Park, UK
| | - Yi Cui
- Safety Pharmacology, Safety Assessment, GlaxoSmithKline, R&D WareUK
| | - Peter Kohl
- Computational Biology, Department of Computer Science, University of OxfordOxford, UK
- National Heart and Lung Institute, Imperial College LondonLondon, UK
| | - Denis Noble
- Computational Biology, Department of Computer Science, University of OxfordOxford, UK
- Department of Physiology, Anatomy & Genetics, University of OxfordOxford, UK
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Davies MR, Mistry HB, Hussein L, Pollard CE, Valentin JP, Swinton J, Abi-Gerges N. An in silico canine cardiac midmyocardial action potential duration model as a tool for early drug safety assessment. Am J Physiol Heart Circ Physiol 2012; 302:H1466-80. [DOI: 10.1152/ajpheart.00808.2011] [Citation(s) in RCA: 63] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Cell lines expressing ion channels (IC) and the advent of plate-based electrophysiology device have enabled a molecular understanding of the action potential (AP) as a means of early QT assessment. We sought to develop an in silico AP (isAP) model that provides an assessment of the effect of a compound on the myocyte AP duration (APD) using concentration-effect curve data from a panel of five ICs (hNav1.5, hCav1.2, hKv4.3/hKChIP2.2, hKv7.1/hminK, hKv11.1). A test set of 53 compounds was selected to cover a range of selective and mixed IC modulators that were tested for their effects on optically measured APD. A threshold of >10% change in APD at 90% repolarization (APD90) was used to signify an effect at the top test concentration. To capture the variations observed in left ventricular midmyocardial myocyte APD data from 19 different dogs, the isAP model was calibrated to produce an ensemble of 19 model variants that could capture the shape and form of the APs and also quantitatively replicate dofetilide- and diltiazem-induced APD90 changes. Provided with IC panel data only, the isAP model was then used, blinded, to predict APD90 changes greater than 10%. At a simulated concentration of 30 μM and based on a criterion that six of the variants had to agree, isAP prediction was scored as showing greater than 80% predictivity of compound activity. Thus, early in drug discovery, the isAP model allows integrating separate IC data and is amenable to the throughput required for use as a virtual screen.
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Affiliation(s)
| | | | - L. Hussein
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
| | - C. E. Pollard
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
| | - J.-P. Valentin
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
| | - J. Swinton
- Computational Biology, Discovery Sciences and
| | - N. Abi-Gerges
- Safety Pharmacology, Safety Assessment United Kingdom, AstraZeneca R&D, Macclesfield, United Kingdom
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Erdemli G, Kim AM, Ju H, Springer C, Penland RC, Hoffmann PK. Cardiac Safety Implications of hNav1.5 Blockade and a Framework for Pre-Clinical Evaluation. Front Pharmacol 2012; 3:6. [PMID: 22303294 PMCID: PMC3266668 DOI: 10.3389/fphar.2012.00006] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2011] [Accepted: 01/12/2012] [Indexed: 12/17/2022] Open
Abstract
The human cardiac sodium channel (hNav1.5, encoded by the SCN5A gene) is critical for action potential generation and propagation in the heart. Drug-induced sodium channel inhibition decreases the rate of cardiomyocyte depolarization and consequently conduction velocity and can have serious implications for cardiac safety. Genetic mutations in hNav1.5 have also been linked to a number of cardiac diseases. Therefore, off-target hNav1.5 inhibition may be considered a risk marker for a drug candidate. Given the potential safety implications for patients and the costs of late stage drug development, detection, and mitigation of hNav1.5 liabilities early in drug discovery and development becomes important. In this review, we describe a pre-clinical strategy to identify hNav1.5 liabilities that incorporates in vitro, in vivo, and in silico techniques and the application of this information in the integrated risk assessment at different stages of drug discovery and development.
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Affiliation(s)
- Gül Erdemli
- Center for Proteomic Chemistry, Novartis Institutes for Biomedical Research Cambridge, MA, USA
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Nordsletten DA, Yankama B, Umeton R, Ayyadurai VAS, Dewey CF. Multiscale mathematical modeling to support drug development. IEEE Trans Biomed Eng 2011; 58:3508-12. [PMID: 22042123 DOI: 10.1109/tbme.2011.2173245] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
It is widely recognized that major improvements are required in the methods currently being used to develop new therapeutic drugs. The time from initial target identification to commercialization can be 10-14 years and incur a cost in the hundreds of millions of dollars. Even after substantial investment, only 30-40% of the candidate compounds entering clinical trials are successful. We propose that multiscale mathematical pathway modeling can be used to decrease time required to bring candidate drugs to clinical trial and increase the probability that they will be successful in humans. The requirements for multiple time scales and spatial scales are discussed, and new computational paradigms are identified to address the increased complexity of modeling.
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29
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Supplemental Studies for Cardiovascular Risk Assessment in Safety Pharmacology: A Critical Overview. Cardiovasc Toxicol 2011; 11:285-307. [DOI: 10.1007/s12012-011-9133-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Obiol-Pardo C, Gomis-Tena J, Sanz F, Saiz J, Pastor M. A Multiscale Simulation System for the Prediction of Drug-Induced Cardiotoxicity. J Chem Inf Model 2011; 51:483-92. [DOI: 10.1021/ci100423z] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Cristian Obiol-Pardo
- Research Programme on Biomedical Informatics (GRIB), IMIM, Universitat Pompeu Fabra, PRBB, Dr. Aiguader 88, E-08003 Barcelona, Spain
| | - Julio Gomis-Tena
- Grupo Bioelectronica I3BH, Universitat Politecnica de Valencia, Camino de Vera s/n, E-46022 Valencia, Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics (GRIB), IMIM, Universitat Pompeu Fabra, PRBB, Dr. Aiguader 88, E-08003 Barcelona, Spain
| | - Javier Saiz
- Grupo Bioelectronica I3BH, Universitat Politecnica de Valencia, Camino de Vera s/n, E-46022 Valencia, Spain
| | - Manuel Pastor
- Research Programme on Biomedical Informatics (GRIB), IMIM, Universitat Pompeu Fabra, PRBB, Dr. Aiguader 88, E-08003 Barcelona, Spain
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31
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Fink M, Noble D. Pharmacodynamic effects in the cardiovascular system: the modeller's view. Basic Clin Pharmacol Toxicol 2010; 106:243-9. [PMID: 20470255 DOI: 10.1111/j.1742-7843.2009.00534.x] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Cardiovascular disease, and the cardiovascular side effects of drugs, are essentially multifactorial problems involving interactions between many proteins, dependent on highly organized cell, tissue and organ structures. This is one reason why the side effects of drugs are often unanticipated. It is impossible to unravel such problems without using a systems approach, i.e. focussing on processes, not just molecular components. This inevitably involves modelling as the interactions require quantitative analysis. Modelling is a tool of analysis aimed at understanding, first, and predicting, eventually. We illustrate these principles using modelling of the heart. Models of the cardiac myocyte have benefited from several decades of interaction between experimentation and simulation. They are now sufficiently detailed to have been of use in the development of new drug compounds like ranolazine and ivabradine. With the help of cardiac modelling, we have also been able to unravel the mechanisms underlying the beneficial effect of sodium calcium exchange block for long QT syndrome (LQTS) 2 and LQTS3 patients. Detailed models of the interaction between ion channels and blocking agents provide the basis for modelling drug action from basic principles and predict changes in the inhomogeneous tissue of the heart. We demonstrate that mathematical models are beneficial for unravelling the complex interactions of pharmacodynamics in the heart. Embedding these detailed biophysical cellular scale models into anatomically correct models of the ventricle geometry will enable reconstructions of Torsades de Pointes arrhythmias and of fibrillation, providing a mechanism for linking detailed cellular scale experimental data to clinical applications.
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Affiliation(s)
- Martin Fink
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
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Lee N, Authier S, Pugsley MK, Curtis MJ. The continuing evolution of torsades de pointes liability testing methods: Is there an end in sight? Toxicol Appl Pharmacol 2010; 243:146-53. [DOI: 10.1016/j.taap.2009.12.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2009] [Revised: 12/04/2009] [Accepted: 12/04/2009] [Indexed: 01/08/2023]
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Zhou Q, Zygmunt AC, Cordeiro JM, Siso-Nadal F, Miller RE, Buzzard GT, Fox JJ. Identification of Ikr kinetics and drug binding in native myocytes. Ann Biomed Eng 2009; 37:1294-309. [PMID: 19353268 PMCID: PMC2690829 DOI: 10.1007/s10439-009-9690-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2008] [Accepted: 03/27/2009] [Indexed: 12/19/2022]
Abstract
Determining the effect of a compound on IKr is a standard screen for drug safety. Often the effect is described using a single IC50 value, which is unable to capture complex effects of a drug. Using verapamil as an example, we present a method for using recordings from native myocytes at several drug doses along with qualitative features of IKr from published studies of HERG current to estimate parameters in a mathematical model of the drug effect on IKr. IKr was recorded from canine left ventricular myocytes using ruptured patch techniques. A voltage command protocol was used to record tail currents at voltages from −70 to −20 mV, following activating pulses over a wide range of voltages and pulse durations. Model equations were taken from a published IKr Markov model and the drug was modeled as binding to the open state. Parameters were estimated using a combined global and local optimization algorithm based on collected data with two additional constraints on IKrI–V relation and IKr inactivation. The method produced models that quantitatively reproduce both the control IKr kinetics and dose dependent changes in the current. In addition, the model exhibited use and rate dependence. The results suggest that: (1) the technique proposed here has the practical potential to develop data-driven models that quantitatively reproduce channel behavior in native myocytes; (2) the method can capture important drug effects that cannot be reproduced by the IC50 method. Although the method was developed for IKr, the same strategy can be applied to other ion channels, once appropriate channel-specific voltage protocols and qualitative features are identified.
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Affiliation(s)
- Qinlian Zhou
- Gene Network Sciences, 58 Charles Street, Cambridge, MA 02141, USA.
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34
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Soubret A, Helmlinger G, Dumotier B, Bibas R, Georgieva A. Modeling and Simulation of Preclinical Cardiac Safety: Towards an Integrative Framework. Drug Metab Pharmacokinet 2009; 24:76-90. [DOI: 10.2133/dmpk.24.76] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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35
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Brennan T, Fink M, Rodriguez B. Multiscale modelling of drug-induced effects on cardiac electrophysiological activity. Eur J Pharm Sci 2008; 36:62-77. [PMID: 19061955 DOI: 10.1016/j.ejps.2008.09.013] [Citation(s) in RCA: 75] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2008] [Accepted: 09/08/2008] [Indexed: 01/09/2023]
Abstract
Many drugs fail in the clinical trials and therefore do not reach the market due to adverse effects on cardiac electrical function. This represents a growing concern for both regulatory and pharmaceutical agencies as it translates into important socio-economic costs. Drugs affecting cardiac activity come from diverse pharmacological groups and their interaction with cardiac electrophysiology can result in increased risk of potentially life threatening arrhythmias, such as Torsade de Pointes. The mechanisms of drug interaction with the heart are very complex and the effects span from the ion channel to the whole organ level. This makes their investigation using solely experimental in vitro and in vivo techniques very difficult. Computational modelling of cardiac electrophysiological behaviour has provided insight into the mechanisms of cardiac arrhythmogenesis, with high spatio-temporal resolution, from the ion channel to the whole organ level. It therefore represents a powerful tool in investigating mechanisms of drug-induced changes in cardiac behaviour and in their pro-arrhythmic potential. This article presents a comprehensive review of the recent advances in detailed models of drug action on cardiac electrophysiological activity.
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Affiliation(s)
- T Brennan
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
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36
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Noble D. Computational models of the heart and their use in assessing the actions of drugs. J Pharmacol Sci 2008; 107:107-17. [PMID: 18566519 DOI: 10.1254/jphs.cr0070042] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
Models of cardiac cells are sufficiently well developed to answer questions concerning the actions of drugs on repolarization and the initiation of arrhythmias. These models can be used to characterize drug-receptor action profiles that would be expected to avoid arrhythmia and so help to identify drugs that may be safer. Several examples of such action profiles are presented here, including a recently-developed blocker of persistent sodium current, ranolazine. The models have also been incorporated into tissue and organ models that enable arrhythmia to be modelled also at these levels. Work at these levels can reproduce both re-entrant arrhythmia and fibrillation.
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Affiliation(s)
- Denis Noble
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.
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37
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Recanatini M, Cavalli A. QSAR and Pharmacophores for Drugs Involved in hERG Blockage. ACTA ACUST UNITED AC 2008. [DOI: 10.1002/9783527621460.ch5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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38
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39
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Rand DG, Zhou Q, Buzzard GT, Fox JJ. Computationally efficient strategy for modeling the effect of ion current modifiers. IEEE Trans Biomed Eng 2008; 55:3-13. [PMID: 18232341 DOI: 10.1109/tbme.2007.896594] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Electrophysiological studies often seek to relate changes in ion current properties caused by a chemical modifier to changes in cellular properties. Therefore, quantifying concentration-dependent effects of modifiers on ion currents is a topic of importance. In this paper, we sought a mathematical method for using ion current data to predict the effect of several theoretical ion current modifiers on cellular and tissue properties that is computationally efficient without compromising predictive power. We focused on the K+ current I(K,r) as an example case due to its link to long QT syndrome and arrhythmias, but these methods should be generally applicable to other electrophysiological studies. We compared predictions using a Markov model with mass action binding of the modifiers to specific conformational states of the channel to predictions generated by two simplified models. We investigated scaling I(K,r) conductance, and found that although this method produced predictions that agreed qualitatively with the more complicated model, it did not generate quantitatively consistent predictions for all modifiers tested. Our simulations showed that a more computationally efficient Hodgkin-Huxley model that incorporates the effect of modifiers through functional changes in the current produced quantitatively consistent predictions of concentration-dependent changes in cell and tissue properties for all modifiers tested.
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Affiliation(s)
- David G Rand
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138-3758, USA.
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40
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Helliwell RM. Recording hERG potassium currents and assessing the effects of compounds using the whole-cell patch-clamp technique. Methods Mol Biol 2008; 491:279-95. [PMID: 18998101 DOI: 10.1007/978-1-59745-526-8_22] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
The complex gating of the hERG channel makes it ideally suited to its principal role in controlling phase 3 repolarization of the cardiac ventricular action potential. Any abnormal delay in repolarization can lead to the re-activation of Ca(2)+ channels, giving rise to early after-depolarizations, and coupled with increased cardiac dispersion, typically associated with these delays, provides respectively both the trigger and substrate for the potentially life threatening arrhythmia Torsardes de Pointes (TdP). Owing to the fundamental role of hERG in controlling the duration of the cardiac action potential, it is not surprising that any drugs that potently and selectively block this channel are liable to have these effects. Consequently, much effort has been expended in developing standard voltage protocols to reliably assess the effects of compounds on hERG currents in vitro. This chapter describes how to record hERG currents in a recombinant cell line using the whole-cell patch-clamp technique. It also provides typical voltage protocols used for assessing the basic electrophysiological properties of these currents and for assessing the effects of compounds on hERG tail currents.
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Dumotier BM, Georgieva AV. Preclinical cardio-safety assessment of torsadogenic risk and alternative methods to animal experimentation: The inseparable twins. Cell Biol Toxicol 2007; 23:293-302. [PMID: 17216548 DOI: 10.1007/s10565-006-0882-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2006] [Accepted: 11/29/2006] [Indexed: 11/25/2022]
Abstract
The last decade has been marked by the withdrawal from the market of several medicines whose use in patients has been associated with the development of torsade de pointes (TdP), a potentially life-threatening polymorphic tachycardia. In a few cases, TdP can degenerate into ventricular fibrillation and lead to sudden death, thus constituting a real problem of public health. The recently finalized ICH S7B guideline defines the prolongation of the QT interval on the electrocardiogram as the best biomarker for predicting the torsadogenic risk of a given compound. However, a growing body of evidence suggests that drugs' torsadogenic potential may not necessarily be proportional to their ability to prolong the QT interval. It is a dynamic combination of multiple predisposing factors and components rather than a single particular event that can trigger this particular tachycardia. Following recommendations of the guideline, pharmaceutical companies have intensively implemented methodologies to assess the possible risk of QT prolongation and TdP in humans. The main problem in cardiac safety pharmacology is how best to combine the capabilities of different methodologies with their strengths and limitations in order to detect the potential of one molecular entity to induce a lethal arrhythmia of very low clinical incidence. This publication will review the current methodologies, focusing on the alternative methods to animal experimentation, including an overview of cardiac modeling.
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Affiliation(s)
- B M Dumotier
- Novartis Pharma AG, Development, Safety Profiling & Assessment, Safety Pharmacology, Basel, Switzerland.
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42
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Abstract
Experimentally based models of the heart have been developed since 1960, starting with the discovery and modelling of potassium channels. The early models were based on extensions of the Hodgkin-Huxley nerve impulse equations. The first models including calcium balance and signalling were made in the 1980s and have now reached a high degree of physiological detail. During the 1990s these cell models have been incorporated into anatomically detailed tissue and organ models to create the first virtual organ, the Virtual Heart. With over 40 years of interaction between simulation and experiment, the models are now sufficiently refined to begin to be of use in drug development.
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Affiliation(s)
- Denis Noble
- Department of Physiology, Anatomy and Genetics, Parks Road, Oxford, OX1 3PT, UK.
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44
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Suter W. Predictive value of in vitro safety studies. Curr Opin Chem Biol 2006; 10:362-6. [PMID: 16815733 DOI: 10.1016/j.cbpa.2006.06.023] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2006] [Accepted: 06/21/2006] [Indexed: 10/24/2022]
Abstract
The predictive value of in vitro safety studies is discussed for three important areas of pharmaceutical safety evaluations. In genetic toxicology, currently assays are sensitive for the prediction of cancer, but their overall predictive value is strongly diminished because of their low specificity. In the area of safety pharmacology blockage of hERG channel in vitro has recently been introduced to predict cardiac repolarization delay (QT interval prolongation) in patients. There is a plethora of in vitro methods to predict and characterize liver toxicity. However, little data is available that demonstrate a reliable prediction for hepatotoxicity in vivo over a wide range of chemical structures. In all three areas, further improvements are needed. 'Omics' technologies and new cell lines derived from stem cells are expected to strongly contribute to establish new and more predictive in vitro assays.
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Affiliation(s)
- Willi Suter
- Exploratory Development, Safety Profiling and Assessment, Novartis Pharma AG, CH 4002 Basel, Switzerland.
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45
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Cho CR, Labow M, Reinhardt M, van Oostrum J, Peitsch MC. The application of systems biology to drug discovery. Curr Opin Chem Biol 2006; 10:294-302. [PMID: 16822703 DOI: 10.1016/j.cbpa.2006.06.025] [Citation(s) in RCA: 73] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2006] [Accepted: 06/21/2006] [Indexed: 01/06/2023]
Abstract
Recent advances in the 'omics' technologies, scientific computing and mathematical modeling of biological processes have started to fundamentally impact the way we approach drug discovery. Recent years have witnessed the development of genome-scale functional screens, large collections of reagents, protein microarrays, databases and algorithms for data and text mining. Taken together, they enable the unprecedented descriptions of complex biological systems, which are testable by mathematical modeling and simulation. While the methods and tools are advancing, it is their iterative and combinatorial application that defines the systems biology approach.
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Affiliation(s)
- Carolyn R Cho
- Department of Systems Biology, Genome and Proteome Sciences, Novartis Institutes of BioMedical Research, Cambridge MA 02139, USA
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