# An Integrated Reverse Engineering Approach Toward Rapid drug Re positioning for Alzheimer's Disease

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2020 · $607,249

## Abstract

PROJECT SUMMARY
Alzheimer disease (AD) is the most common cause of dementia and one of the leading sources of morbidity
and mortality in the aging population. Despite enormous social and economic costs associated with AD,
current drugs are directed towards symptomatic relief and none are curative.
In this project titled “An integrated reverse engineering approach toward rapid drug repositioning for
Alzheimer’s disease,” we propose to develop an innovative integrated drug repositioning strategy that
combines computation-based drug prediction, computation-based human brain-blood-barrier (BBB)
permeability prediction, retrospective large-scale clinical corroboration, and prospective experimental testing to
rapidly identify anti-AD drug candidates. First, we will develop novel computational approaches to identify
repositioning anti-AD candidates from all (>2,600) FDA-approved drugs. Second, we will develop novel
multifaceted biology-based computational methods to predict which repositioned drug candidates can cross
BBB in humans. Third, we will perform large-scale retrospective case-control studies to corroborate the clinical
efficacy of repositioned drug candidates using patient electronic health record (EHR) data of >50 million
patients. Finally, we will evaluate the therapeutic potential of promising repositioned candidates in experimental
models. Our study will generate a large amount of data/knowledge/hypotheses that could serve as a starting
point for us and others to conduct hypothesis-driven drug repositioning studies in other animal models of AD
and in AD patients. We will build a comprehensive Alzheimer Drug Repositioning Knowledge Base (ADRKB)
and develop interactive web applications to make ADRKB publicly available.
The unique and powerful strength of our project is our ability to seamlessly combine novel computational
predictions, retrospective clinical corroboration using patient EHRs, and experimental testing in animal models
of AD to rapidly identify innovative drug candidates that may work in real-world AD patients. The repositioned
drug candidates will have interpretable mechanisms of action, are highly likely to cross BBB in humans, have
clinical effectiveness evidence gathered from ‘real-world’ AD patients, and have demonstrated efficacy in
mouse models of AD. We anticipate that these findings can be expeditiously translated into clinical trials and
benefit 5.4 million AD patients in United States and 47 million AD patients worldwide.

## Key facts

- **NIH application ID:** 9949583
- **Project number:** 5R01AG057557-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Rong Xu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $607,249
- **Award type:** 5
- **Project period:** 2017-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9949583

## Citation

> US National Institutes of Health, RePORTER application 9949583, An Integrated Reverse Engineering Approach Toward Rapid drug Re positioning for Alzheimer's Disease (5R01AG057557-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9949583. Licensed CC0.

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