# Point of Care Diagnostics for Liver Disease using Fluorescent Nanosensors

> **NIH NIH R01** · UNIVERSITY OF MASSACHUSETTS AMHERST · 2024 · $465,760

## Abstract

Project Summary/Abstract
Point of Care Diagnostics for Liver Disease using Fluorescent Nanosensors
 Liver fibrosis/cirrhosis is a major driver of mortality and morbidity worldwide. Rapid diagnosis of liver
fibrosis is crucial to optimizing patient outcome and minimizing economic impact of this disease. Current
strategies for detecting liver damage (fibrosis/cirrhosis) use biomarker and mechanical strategies that are
expensive and difficult to translate into Point of Care (PoC) platforms. Robust PoC liver diagnostics would
enable regular monitoring of chemotherapy patients and game-changing diagnostics for the developing world.
In preliminary studies we have demonstrated that polymer-based sensor arrays on paper substrates can
generate serum ‘signatures’ that can diagnose liver fibrosis with clinical relevance. In our proposed research
we will build on this foundation to create effective lateral flow device (LFD) diagnostics for liver fibrosis. In our
multi-pronged strategy, we will:
Aim 1: Synthesize engineered polymer conjugates (Rotello) and use these as sensor elements to provide
 multi-channel outputs serum sensing. Protein/serum selectivity will be guided by integration of
 synthesis (Rotello) with computational/machine learning tools (Van Lehn) in a feedback-driven cycle.
 Thesse studies will be performed in solution to facilitate sensor optimization.
Aim 2: Fabricate LFD devices and immobilize polymers downselected from Aim 1 onto surfaces to provide
 prototype sensing systems suitable for PoC use. (Rotello) These sensors will be tested and optimized
 using model sera generated by spiking healthy serum.
Aim 3: Apply LFDs downselected from Aim 2 to profile liver fibrosis using pathological samples and liver
 diagnostics insight provided by Rosenberg and Peveler. These studies will focus on detection and
 staging of liver fibrosis, using statistical methods developed by C. Rotello.
Aim 4: Effective sensor systems identified in Aim 3 will be explored using proteomics by Vachet. These
 studies characterize protein binding to the polymer sensors, providing insight into how the sensor works
 and potentially new biomarkers for fibrosis.
 The key driver of the proposed research is the development of PoC systems for diagnosis of liver fibrosis;
effective achievement of this goal would provide strategies that could be translated to numerous disease
states. The focus on polymer-protein affinity and selectivity will provide new insight into fundamental aspects of
these interactions, and the integration of machine learning into this process will develop new polymer design
strategies biomedical applications.

## Key facts

- **NIH application ID:** 10981661
- **Project number:** 2R01DK121351-17
- **Recipient organization:** UNIVERSITY OF MASSACHUSETTS AMHERST
- **Principal Investigator:** VINCENT M. ROTELLO
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $465,760
- **Award type:** 2
- **Project period:** 2020-02-01 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10981661

## Citation

> US National Institutes of Health, RePORTER application 10981661, Point of Care Diagnostics for Liver Disease using Fluorescent Nanosensors (2R01DK121351-17). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10981661. Licensed CC0.

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