# Preparing a clinical outcomes assessment set for nephrotic syndrome [Prepare-NS]

> **NIH FDA UG3** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $675,017

## Abstract

Abstract
The PREPARE-NS program will develop and establish the psychometric properties of a core set of clinical
outcome assessments (COAs) for nephrotic syndrome, with primary focus on fluid overload (FO). During
the UG3 phase, a diverse team of experts and stakeholders will be convened, in cooperation with the FDA, to
confirm conditions, measures and anchors and design the studies necessary to identify a rigorous and patient-
centered FO endpoint definition and measure set. The UH3 will focus on testing and implementing the core set
of COAs identified in the UG3 phase. The research conducted in the UH3 phase will allow us to refine the FO
COAs. The final activities will be focused on making the final core set of COAs widely available to the public for
use in trials. For both phases, we will work in close consultation with the project stakeholder engagement and
clinician expert panels, drawing from the perspectives of patients, clinicians, regulators, payers, and drug
developers. Tapping these resources, and relying on our team's wide-ranging clinical, COA development, and
psychometric expertise, we will generate a core set of highly-relevant COAs that will advance patient-focused
drug development in nephrotic syndrome.

## Key facts

- **NIH application ID:** 10282190
- **Project number:** 1UG3FD007308-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** DEBBIE S GIPSON
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2021
- **Award amount:** $675,017
- **Award type:** 1
- **Project period:** 2021-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10282190

## Citation

> US National Institutes of Health, RePORTER application 10282190, Preparing a clinical outcomes assessment set for nephrotic syndrome [Prepare-NS] (1UG3FD007308-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10282190. Licensed CC0.

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