# Multiscale modeling to map cardiac electrophysiology between species

> **NIH NIH U01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $636,811

## Abstract

PROJECT SUMMARY
The overall goal of this U01 application is to develop novel approaches for multiscale modeling in cardiac
electrophysiology and arrhythmia research. To accomplish this goal, we will use innovative combinations of
experimental and computational studies at multiple spatial scales and across multiple conceptual scales.
Because cardiac cells are complex systems involving dozens of interacting molecular entities, mathematical
modeling has long been a valuable technique for uncovering arrhythmia mechanisms. However, established
methods for combining modeling with experiments have important limitations, including: (1) most studies test
only a limited number of model predictions; (2) models usually predict the response of a sample considered
representative of a population, thereby ignoring differences between individuals; and (3) tissue-level
simulations may incorporate physiological differences between regions but do not account for the fact that
each cell in the tissue is different.
We will address these limitations using innovative and synergistic computational and experimental
methodologies developed by the PIs. These methods allow for rigorous parameter estimation, systematic and
quantitative predictions, and testing multiple perturbations in each experimental sample, and quantitative
mappings between different cell types. To achieve our overall goals, we propose to:
 1. improve heart cell models through rigorous experimental testing and the development of mathematical
 models specific to each cell studied.
 2. calibrate models of heterogeneous cell populations and experimentally test predictions regarding ionic
 current variation and co-variation across populations
 3. develop models to predict the effects of perturbations in one species based on recordings made in a
 different species
 4. predict how variability between individual cells influences arrhythmia risk at the tissue level.
The research is likely to demonstrate improved, broadly applicable methods for rigorous and systematic
coupling between experiments and simulations at multiple spatial scales. By so doing, the combined studies
will provide important insight into the consequences of variability at both the cellular and tissue levels.

## Key facts

- **NIH application ID:** 9859440
- **Project number:** 5U01HL136297-04
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** DAVID J. CHRISTINI
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $636,811
- **Award type:** 5
- **Project period:** 2017-04-15 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9859440

## Citation

> US National Institutes of Health, RePORTER application 9859440, Multiscale modeling to map cardiac electrophysiology between species (5U01HL136297-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9859440. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*