# Development of the Predictive NeuroCardiovascular Simulator

> **NIH NIH OT2** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2020 · $1,450,692

## Abstract

In 1628 William Harvey wrote, “Every affection of the mind that is attended with either pain or
pleasure, hope or fear, is the cause of an agitation whose influence extends to the heart.”
Despite centuries of recognition of the fundamental connection between the brain and heart,
there is still very poor understanding of the role of autonomic control in normal cardiac control
and in the paroxysmal nature of life threatening cardiac events. To predict the mechanisms
underlying the interaction between nervous system discharge and the resultant emergent
cardiac and vascular events would finally allow for individual identification and specific targeting
of arrhythmia provoking conditions by drugs or even by direct electrical stimulation. We propose
to develop the Neurocardiovascular Simulator suite to solve this problem. The proposed
simulator is unparalleled, as it will integrate anatomical and functional data ranging from the
atomic level for ion channels and key signaling proteins to subcellular to cellular, organ, and
systems data and simulations. Importantly, our simulator incorporates multiscale variability that
reflects individual subject differences, allowing for a uniquely predictive tool. Experiment-
informed simulator predictions will be used to further guide ongoing experiments in SPARC
projects and to interpret patient data, allowing for tight integration and synergy across multiple
arms of the SPARC initiative. The simulator has 8 tasks. In Task 1, we model neural circuitry. In
Task 2, we incorporate into the simulator the anatomical features required for intrinsic
autonomic regulation of cardiovascular function. In Task 3, we simulate synaptic control of
vascular and cardiac myocytes. Task 4 involves modeling autonomic effects on subcellular
signaling and electrophysiology in vascular and cardiac myocytes, while Task 5 deals with
atomic-scale details of the molecular interactions in the adrenergic signaling cascade. Task 6
integrates data from the previous 5 tasks to predict autonomic effects on the cardiovascular
system. In Task 7, we develop tools (workflows) for model dissemination and use by others.
Finally, in Task 8 we incorporate into the simulator uncertainty quantification, sensitivity
analysis, and robustness tests. The proposed studies have the potential of transforming our
understanding of how cardiac and vascular function is regulated by the autonomic nervous
system and provide insights into how this neuro-cardiovascular axis could be clinically tuned
with molecular precision to improve patient outcomes.

## Key facts

- **NIH application ID:** 10215080
- **Project number:** 3OT2OD026580-01S3
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** COLLEEN E CLANCY
- **Activity code:** OT2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,450,692
- **Award type:** 3
- **Project period:** 2018-08-01 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10215080

## Citation

> US National Institutes of Health, RePORTER application 10215080, Development of the Predictive NeuroCardiovascular Simulator (3OT2OD026580-01S3). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10215080. Licensed CC0.

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