# Personalized Behavioral Modifications Algorithm and Software Based on Analysis and Computer Simulation of Voiding Patterns in Patients with Lower Urinary Tract Symptoms

> **NIH NIH R21** · ARBOR RESEARCH COLLABORATIVE FOR  HEALTH · 2020 · $220,812

## Abstract

7. Project Summary/Abstract
Lower urinary tract symptoms (LUTS), such as urinary urgency, frequency, nocturia, and incontinence affect
approximately three-quarters of the population over age 40 in the United States and are associated with
decreased quality of life. Bladder Diaries are a simple, inexpensive tool to capture real-life symptoms and
voiding behavior. Simple recommendations based on the Bladder Diaries have already been shown to have a
profound impact on LUTS, including incontinence. We are striving to go further and develop individualized
advice for patients, rather than a generic “drink less, void every 2 hours, and restrict fluids before bed”
recommendation, which may not improve LUTS in all patients. Bladder Diaries provide the timing of fluid
intake, which is the primary driver of urinary output, but the time lapse between intake and output is not
straightforward. To fill this knowledge gap, we plan to develop a parsimonious mechanistic model based on
current understanding of the physiology and neural regulation of urination and fluid shifts in the body that
describes voiding patterns in people with and without LUTS. We will be using Bladder Diary data collected in
two studies: Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) and Establishing
Prevalence of Incontinence (EPI). The mathematical model will consider: 1) ingestion time and amount; 2)
variability in delivery to the bladder; and 3) variation in bladder sensation and excretion. This model could
serve future researchers in evaluation of voiding variables and in mechanistic studies of LUTS. Based on the
model, we plan to develop an algorithm and software to provide individualized recommendations to modify
intake patterns in order to minimize “adverse urinary events” (i.e., leaking or excessive night voids).
Optimization of the intake patterns will be performed to minimize number of simulated adverse urinary events
for a given simulated patient based on the model developed from the Bladder Diary of a real patient. The goal
is to develop a “precision medicine” tool for assessment of Bladder Diaries so that clinicians will be able to
provide individualized behavior modification recommendations. This work would represent the first systematic
mathematical model of fluid intake and voiding behavior based on Bladder Diary data that would help
understanding individual voiding patterns, mechanisms of disease, and opportunities for treatment.

## Key facts

- **NIH application ID:** 10004605
- **Project number:** 5R21DK121065-02
- **Recipient organization:** ARBOR RESEARCH COLLABORATIVE FOR  HEALTH
- **Principal Investigator:** Victor P. Andreev
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $220,812
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10004605

## Citation

> US National Institutes of Health, RePORTER application 10004605, Personalized Behavioral Modifications Algorithm and Software Based on Analysis and Computer Simulation of Voiding Patterns in Patients with Lower Urinary Tract Symptoms (5R21DK121065-02). Retrieved via AI Analytics 2026-06-02 from https://api.ai-analytics.org/grant/nih/10004605. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*