# Development of a biomarker panel for minimally-invasive screening and diagnosis of gynecological disease

> **NIH NIH R41** · MDDX, INC. · 2020 · $299,998

## Abstract

PROJECT SUMMARY
One-third of all women of reproductive age will experience nonmenstrual pelvic pain at some point in their lives
and one-third of outpatient visits to gynecologists in the U.S. are for evaluation of abnormal uterine bleeding.
For many women, these symptoms accompany infertility which is reported in ~10% of all US women and even
higher percentages worldwide. For almost all of these women, these conditions result in a diagnostic odyssey
wherein women struggle through multiple physicians over many years for a definitive diagnosis, frequently
culminating in invasive laparoscopy or hysteroscopy with dilation and curettage (D&C) for definitive diagnosis.
To reduce the burden of diagnosis and enable early treatment, MDDx, Inc. is developing the first biomarker-
based diagnostic test to enable minimally invasive simultaneous diagnosis of four of the most common causes
which together result in chronic pain, uterine bleeding and infertility: adenomyosis, endometrial
polyps, leiomyoma, and endometriosis.
MDDx, Inc. has been leveraging access to >12 years of longitudinally collected and deeply annotated
biobanked uterine lavage samples from the Gynecologic Cancer Translational Research Program (Icahn
School of Medicine at Mount Sinai; New York, NY and Nuvance Health; Danbury, CT) to identify diagnostic
autoantibodies (AAb) that could serve as diagnostic biomarkers for these benign gynecological diseases. By
performing AAb profiling against the entire human proteome and applying our novel machine-learning based
method for classification of molecular profiles we have determined that there is a common set of ~200
biomarkers that could be used to diagnose women with adenomyosis, endometrial polyps, leiomyoma, or
endometriosis. The goal of Phase I is to finalize and validate the optimized set of ~200 diagnostic AAbs, while
Phase II will focus on validation of the commercial diagnostic assay.
In Aim 1 we will expand our proprietary database of uterine lavage autoantibody profiles to ensure that we
have a sample size (~935) that will enable us to confidently apply our machine learning approaches to
identifying the minimal panel of AAbs for the diagnostic. We will use this enhanced database to identify a
prototype panel of ~200 AAbs for construction of classification scoring functions to distinguish between
adenomyosis, endometrial polyps, leiomyoma, and endometriosis. In Aim 2 we will perform a blinded
validation and performance study using an independent set of 300 uterine lavage samples to provide proof-of-
concept for clinically useful sensitivity and specificity prior to large scale prospective validation in Phase II.
Successful completion of this Phase I program will identify the optimized panel of AAbs for an affordable,
laboratory-based diagnostic test that will significantly reduce the number of women who will need to undergo
laparoscopy or hysteroscopy with D&C for definitive diagnosis, enabling early treatment of disease and
reducing the s...

## Key facts

- **NIH application ID:** 10146682
- **Project number:** 1R41HD104402-01
- **Recipient organization:** MDDX, INC.
- **Principal Investigator:** Boris Reva
- **Activity code:** R41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $299,998
- **Award type:** 1
- **Project period:** 2020-09-15 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10146682

## Citation

> US National Institutes of Health, RePORTER application 10146682, Development of a biomarker panel for minimally-invasive screening and diagnosis of gynecological disease (1R41HD104402-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10146682. Licensed CC0.

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