Computational modeling and simulations are being increasingly used for device development, testing and validation. However, the application of these in regulatory decision making lags behind device development. Computational modeling of the heart is fast-moving towards clinical applications such as the optimization of ablation, defibrillation, and cardiac resynchronization therapy. Our research efforts are focused on developing modeling/simulation methods in conjunction with appropriate validation methodologies together with guidance on assessing credibility that help devices enter the marketplace utilizing least burdensome approaches.
(Left) voltage on the surface of the heart. (Right) ‘Filaments’ inside the heart, which are the ‘organizing centers’ of the re-entrant electrical activity (similar to the eye of a hurricane).
Safety-critical applications require the reliability, credibility and robustness of model predictions to be rigorously assessed, across all of the component parts of the models as well, together with the risk associated with their role in the decision making process. Unfortunately, there has been very little work in developing our understanding and application of rigorous model assessment methods (verification, validation and uncertainty quantification, or VVUQ) on mechanistic physiological computational models. Established VVUQ methods for assessing the credibility of computational models have been developed by the physics and engineering communities and are currently being adopted by the biomedical community. However, applying VVUQ to physiological models can be extremely challenging and burdensome, due largely to the enormous complexity of the models. The aim of this project is to enable innovation by developing VVUQ-based tools and methodologies for assessing cardiac simulations, allowing FDA to critically assess submissions as well reducing the potential burden in such submissions. Attempting to understand how best to assess complex physiological models such as whole-heart models has led to important insight into assessment methods for all complex computational models. Therefore, our work has recently broadened into the development of methods for assessing credibility of simulations that are applicable to wide range of computational models.
In addition, we are involved in research to: 1) compare and contrast predictions from various cell models; 2) develop new models that are mathematically “identifiable”, i.e., not over parameterized; and 3) investigate the robustness and credibility of integrating models across multiple scales and disciplines (this research includes studying what size anatomical structures in the heart are relevant to fibrillation and defibrillation).
See below for funding sources, formal collaborations, and publications.
Current funding sources
Richard Gray, Ph.D
Pras Pathmanathan, Ph.D
Suran Galappaththige, Ph.D
Relevant Standards & Guidances
Selected peer-review publications
- Mirams G et al. White paper: Uncertainty and variability in computational and mathematical models of cardiac physiology Journal of Physiology, 2016.
- Shotwell M and Gray RA, Pathmanathan P. A Parsimonious Model of the Rabbit Action Potential Elucidates the Minimal Physiological Requirements for Alternans and Spiral Wave Breakup. PLOS Computational Biology, 2016, 12(10): e1005087. doi:10.1371/journal.pcbi.1005087.
- Pathmanathan and Gray, Filament Dynamics during Simulated Ventricular Fibrillation in a High-Resolution Rabbit Heart, BioMed Research International, 2015.
- Pathmanathan et al. Uncertainty quantification of fast sodium current steady-state inactivation for multi-scale models of cardiac electrophysiology, Progress in biophysics and molecular biology, 2015.
- Gurev et al., A high-resolution computational model of the deforming human heart, Biomechanics and modeling in mechanobiology, 2015.
- Franz et al., Drug-induced post-repolarization refractoriness as an antiarrhythmic principle and its underlying mechanism, Europace, 2015.
- Blinova et al., Acute effects of nonexcitatory electrical stimulation during systole in isolated cardiac myocytes and perfused heart, Physiol Rep, 2014.
- Johannesen et al., Improving the assessment of heart toxicity for all new drugs through translational regulatory science, Clinical Pharmacology
- Pathmanathan and Gray, Verification of computational models of cardiac electro-physiology, International journal for numerical methods in biomedical engineering, 2014.