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This regulatory science tool comprises a computer model of a human action potential, which includes the effects of heart failure (HF) and the anti-arrhythmic drugs amiodarone (AM) and d-sotalol (DS).
Technical Description
Therapy for heart failure patients may include anti-arrhythmic drugs and a variety of medical devices, which should work together to achieve the required put outcomes for patients.. Computational modeling of the mechanisms of therapy at the cellular level has the potential for the design and testing of novel drug, medical device, and combination therapies.>
Cardiac electrophysiological computational models are comprised of numerous complex non-linear equations that predict the action potential in the heart at one or multiple sites. Cardiac electrophysiological modeling is a mature field which has been integrated with experimental studies to develop and test hypotheses for decades. Such models are highly modular and equations are often reused and/or modified.
The RST is comprised of 10 models (1 HF and 1 HF+DS and 8 HF+AM models). Eight AM models were developed to represent the variety of the effects of AM including disparate results from animal studies. These models of the human action potential are moderately complex with six currents and seven variables, including a novel phenomenological model of dynamic diastolic calcium concentration (CaiD). These models were calibrated to a variety of human and animal data. Reentrant arrhythmias were induced using programmed stimulation in the HF model in virtual two-dimensional tissue but was prevented in the HF+AM models. As such these models provide insight into the mechanisms of arrhythmia induction in HF patients and the mode of action of AM.
The RST is entirely self-contained although the cardiac model developer or user can modify the equations representing the cell kinetics, stimulation protocol, and numerical solvers to generate the corresponding output for these models.
Intended Purpose
The purpose of this RST, a human action potential model, is to predict the response to programmed electrical stimulation in heart failure patients (with and without Amiodarone treatment) and provides a basis for studies of the initiation of reentry in human ventricular tissue in the presence of heart failure and anti-arrhythmic drugs and medical devices. This RST can also be used in whole heart models of electrical activity including for the design and evaluation of cardiac electrophysiological devices such as pacemakers, defibrillators, and cardiac resynchronization devices, and may be appropriate for the design and analysis of device function in clinical studies and in-vitro experimental studies.
This RST presents a stand-alone model (no user input required) for simulating the human action potential in single cardiac cells and tissue.
Testing
This RST is an exact copy of the model included in the Supplementary Material for the following manuscript:
- Gray, R. A., & Franz, M. R. (2023). Amiodarone prevents wave front-tail interactions in patients with heart failure: an in silico study. American journal of physiology. Heart and circulatory physiology, 325(5), H952–H964. https://doi.org/10.1152/ajpheart.00227.2023
Model development, calibration and validation is described in detail in this manuscript. Briefly, the HF model was calibrated using the results from isolated human tissue and the AM and DS models were calibrated using:
- Action potential duration; and
- Post repolarization refractoriness (PRR) from patients during programmed electrical stimulation; The model was validated by testing whether arrhythmia induction was prevented in HF+AM models.
The level of validation required for a model depends on its “context of use” and the consequences of incorrect model predictions; hence further validation is expected to be required for each specific context.
Limitations
- The model assumes that intra- and extracellular concentrations of ions are constant. The equations are of Hodgkin-Huxley type, Markov models are required to replicate certain features of voltage clamp experiments including drug binding kinetics. Although the model reproduces action potential duration and conduction speed during programmed electrical stimulation, it was not calibrated to steady state or dynamic restitution curves.
Supporting Documentation
The RST is implemented in CellML. The CellML language is an open standard based on the XML markup language. CellML is being developed by the Auckland Bioengineering Institute at the University of Auckland and affiliated research groups.
- Gray, R. A., & Franz, M. R. (2023). Amiodarone prevents wave front-tail interactions in patients with heart failure: an in silico study. American journal of physiology. Heart and circulatory physiology, 325(5), H952–H964. https://doi.org/10.1152/ajpheart.00227.2023.
The code itself is provided in ten files that can be found on GitHub:
- GrayFranzHumanModel2023_HF.cellml
- GrayFranzHumanModel2023_HF_DS.cellml
- GrayFranzHumanModel2023_HF_AM1.cellml
- GrayFranzHumanModel2023_HF_AM2.cellml
- GrayFranzHumanModel2023_HF_AM3.cellml
- GrayFranzHumanModel2023_HF_AM4.cellml
- GrayFranzHumanModel2023_HF_AM5.cellml
- GrayFranzHumanModel2023_HF_AM6.cellml
- GrayFranzHumanModel2023_HF_AM7.cellml
- GrayFranzHumanModel2023_HF_AM8.cellml
Relevant FDA guidance documents and FDA-recognized standards include:
- FDA guidance “Reporting of Computational Modeling Studies in Medical Device Submissions”
- FDA guidance “Assessing the Credibility of Computational Modeling and Simulation in Medical Device Submissions”
- ASME V&V40-2018, “Assessing Credibility of Computational Modeling through Verification and Validation: Application to Medical Devices”
Related Tools:
- Cardiac Action Potential of the Dog
- Parsimonious Cardiac Action Potential Model of the Rabbit
- Identifiability of Cardiac Electrophysiology Models
Contact
Tool Reference
- In addition to citing relevant publications please reference the use of this tool using RST24CV17.01