# Mechanism-guided drug repurposing for host-directed therapy of infectious diseases using interpretable and integrative ML

> **NIH NIH R21** · MICHIGAN STATE UNIVERSITY · 2022 · $732

## Abstract

ABSTRACT
Our ability to treat infectious diseases is impeded by two major problems. One is the rapid increase of
antimicrobial resistance, and the other is the prohibitive cost and time required for discovering new drugs. A
potential approach to overcome these problems is to focus on repurposing existing drugs for host-directed
therapy. However, this is an emerging application area. While several studies have used this broad approach to
find drug candidates for specific viruses and bacterial infections, there is a dearth of systematic computational
frameworks that can be used to repurpose drugs for any infectious disease, especially ones that focus on drug
and disease mechanisms rather than individual drug and target properties. Also missing are frameworks that
can leverage the massive amounts of data and knowledge available for non-infectious diseases to tackle
infectious disease treatment. In this project, we will develop an integrative framework that uses mechanism-
guided, interpretable machine learning (ML) models to repurpose drugs to bolster host response to infection.
Our framework leverages massive transcriptome data collections and genome-scale human gene interaction
networks; these are two complementary sources of information about molecular mechanisms relevant for this
repurposing effort. It also uses data and knowledge about hundreds of non-infectious diseases and thousands
of small molecules (including FDA-approved drugs) to create numerous repurposing opportunities. Requiring
only host transcriptome data in response to infection, our general-purpose ML framework will be applicable to
new, emerging, and understudied infectious diseases. This project will also result in high-confidence drug
candidates for several infectious diseases along with mechanistic insights into new avenues for host-directed
therapeutics.

## Key facts

- **NIH application ID:** 10442808
- **Project number:** 1R21AI169301-01
- **Recipient organization:** MICHIGAN STATE UNIVERSITY
- **Principal Investigator:** Arjun Krishnan
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $732
- **Award type:** 1
- **Project period:** 2022-05-09 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10442808

## Citation

> US National Institutes of Health, RePORTER application 10442808, Mechanism-guided drug repurposing for host-directed therapy of infectious diseases using interpretable and integrative ML (1R21AI169301-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10442808. Licensed CC0.

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