# Diagnostic Tools for Targeted Heart Failure Treatments

> **NIH NIH R43** · INVIVOSCIENCES, INC. · 2022 · $493,728

## Abstract

Heart failure (HF) is a global epidemic at present and is projected to increase in the future.
Despite the critical needs, HF drug discovery efforts are declining because of the requirement of
large and long clinical trials to validate efficacy in morbidity and mortality endpoints. A recently
issued FDA draft guidance, however, clarified that the effect on symptoms or physical function
without a favorable effect on survival or hospitalization could be a basis for approving drugs to
treat heart failure. Developing start diagnostic tools to monitor functional properties of
cardiovascular systems, including myocardium function, will support a new trend of HF drug
development. Annually >1 million diagnostic catheterizations have been performed; numerous
data are stored in the electronic health record. Analyzing those data could provide an
unprecedented opportunity to identify patterns of functional changes in the hemodynamics of
various HFs. Our approach will combine computational and machine learning methods to
achieve this goal. Diabetes mellitus (DM) in men and women have a 2X and 4X, respectively,
higher risk of heart failure (HF) incident. A recent phenogrouping study identified a subgroup of
HFpEF with diabetes having the highest risk of cardiovascular death and hospitalization among
other groups. This study brought up an opportunity to develop a targeted therapy for HFpEF
with DM (dHFpEF) by developing diagnostic tools to identify candidate dHFpEF patients. Here,
we will test the feasibility of diagnostic tools to stratify HFpEF and model it in vitro.
Aim 1 of the study is to optimize an already developed diagnostic platform, AI-Assisted,
Systems-biology Integrated patient Stratification Technology (AASIST), to analyze data
collected by trans-thoracic echocardiography (TTE) and right heart catheterization (RHC) for the
purpose of classifying dHFpEF phenotypes. We expect to identify a few groups of dHFpEF
defined by their mechanical properties of the myocardium (e.g., elevated left ventricular
stiffness).
Aim 2 of this study is to analyze corresponding parameters of LV stiffness and contractility in
vitro using engineered heart tissues, NuHeart, reconstituted derived from DM patients’ cells. We
will culture NuHeart with various environmental challenges to model dHFpEF. While lifestyle
risks (e.g., smoking, low physical activities) may outweigh genetic influences, we hypothesize
that NuHeart derived from a diabetic patient is susceptible to develop HFpEF phenotype
depending on its culture conditions.

## Key facts

- **NIH application ID:** 10546035
- **Project number:** 1R43HL164266-01A1
- **Recipient organization:** INVIVOSCIENCES, INC.
- **Principal Investigator:** Tetsuro Wakatsuki
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $493,728
- **Award type:** 1
- **Project period:** 2022-09-15 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10546035

## Citation

> US National Institutes of Health, RePORTER application 10546035, Diagnostic Tools for Targeted Heart Failure Treatments (1R43HL164266-01A1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10546035. Licensed CC0.

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