# iPSC-Derived Neuronal Models of Alzheimer's Disease for Phenotypic Drug Screening

> **NIH NIH R44** · PHENOVISTA BIOSCIENCES, LLC · 2021 · $634,006

## Abstract

PROJECT SUMMARY
Alzheimer’s disease (AD), a progressive late onset neurodegenerative disease, represents a serious challenge
for the development of novel drugs. There have been no new AD drugs since 2003, a growing number of
researchers and stakeholders are proposing that AD drug discovery modeling requires a refocus. The
successful development and commercialization of next generation, low-cost, high-performance technology for
modeling both disease biology and the effects of investigational drugs on neurons, would help improve the
development process for new therapies—thereby reducing national healthcare costs and improving patient
outcomes throughout the nation. Therefore, the overall goal of this phase II SBIR project is to further develop,
validate, and commercialize an in vitro high throughput, high content phenotypic AD disease modeling called
the “PhenoFingerprint platform (PFP)”. This Phenovista proprietary PTP will be a next-generation in vitro
system for ranking the relative efficacy and toxicity of CNS therapies, to be incorporated as a part of the
regulatory framework for therapeutic commercialization for AD drug discovery and development.

## Key facts

- **NIH application ID:** 10233977
- **Project number:** 5R44AG058520-03
- **Recipient organization:** PHENOVISTA BIOSCIENCES, LLC
- **Principal Investigator:** Anthony Weber Essex
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $634,006
- **Award type:** 5
- **Project period:** 2017-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10233977

## Citation

> US National Institutes of Health, RePORTER application 10233977, iPSC-Derived Neuronal Models of Alzheimer's Disease for Phenotypic Drug Screening (5R44AG058520-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10233977. Licensed CC0.

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