# A System Approach to Animal-Level Antimicrobial Use Monitoring in Dairy Cattle

> **NIH FDA U01** · CORNELL UNIVERSITY · 2024 · $199,907

## Abstract

PROJECT SUMMARY
 There is a fundamental gap in our ability to monitor antimicrobial use (AMU) at the individual animal
level in dairy cattle nationally. The continued existence of this gap hinders the development of data-driven
antimicrobial stewardship and understanding of the relationships between AMU in dairy cattle and antimicrobial
resistance—one of the most pressing One Health challenges we face today. AMU monitoring requires an
approach to collecting and quantifying data on AMU. Also, most herds must participate in data sharing for an
AMU monitoring system to succeed. However, farmers lack the incentive to participate in monitoring, the labor
involved in data collection is prohibitive for already busy farmers, and they have concerns about the loss of
privacy and business advantage through sharing their AMU data via a monitoring system. These major
bottlenecks are impeding the establishment of AMU monitoring in dairy cattle in the US. Thus, there is an
urgent need for a system approach to animal-level AMU monitoring in dairy cattle that provides private value to
the participating farmer, automates laborious data collection tasks, protects farmers’ privacy, and advances
One Health goals. Our long-term goal is to deploy a functional and efficient system for monitoring AMU in food
animals. Thus, the overall objective of this application is to develop a system for monitoring AMU in dairy cattle
that provides farmers with actionable clinical and business insights, automates data collection, and protects
their proprietary information. The rationale that underlines the proposed research is that such an AMU
monitoring system will incentivize dairy farmer participation and enable One Health to benefit from the national-
level AMU monitoring. This objective will be achieved by systematically building the three pillars of an effective
AMU monitoring system: Data, Models, and People. Specifically, we will pursue the following specific aims: (1)
Collect detailed, complete, and validated multi-year animal-level AMU data on dairy farms; (2) Develop a
system approach to animal-level AMU monitoring in dairy cattle; and (3) Evaluate perceptions of farmers and
veterinarians about AMU monitoring in dairy cattle. The AMU monitoring system developed in Aim 2 will have
four innovative elements: (i) instant private clinical/business insights for the farmer to incentivize their
participation in data collection and sharing, (ii) standardization and automation to ease the data collection
burden on farmers, (iii) augmentation with synthetic data, and (iv) privatization techniques that give the farmer
the governance over their AMU data while allowing peer learning, further incentivizing participation in AMU
monitoring. The proposed research is significant because it is expected to enable scaling up monitoring
animal-level AMU on dairy farms in the US with a system approach and technology that are tailored to the dairy
farming industry and have translational value to ot...

## Key facts

- **NIH application ID:** 11088543
- **Project number:** 1U01FD008421-01
- **Recipient organization:** CORNELL UNIVERSITY
- **Principal Investigator:** Renata Ivanek Miojevic
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2024
- **Award amount:** $199,907
- **Award type:** 1
- **Project period:** 2024-09-15 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11088543

## Citation

> US National Institutes of Health, RePORTER application 11088543, A System Approach to Animal-Level Antimicrobial Use Monitoring in Dairy Cattle (1U01FD008421-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11088543. Licensed CC0.

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