# Creating a disease-agnostic scalable platform for decentralized observational and validation of digital biomarkers studies and piloting it for people with familial ALS and ultra-rare MNDs

> **NIH FDA U01** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $399,250

## Abstract

PROJECT SUMMARY
One of the greatest challenges facing biomedical sciences is the development of fundamentally better treatments
for neurodegenerative diseases. Natural History studies (NHS) are critical to enhance our understanding of the
disease, find external matching controls, identify people living with rare and ultra-rare forms of the diseases, and
bring them into clinical research ecosystem.
The heterogeneity of ALS and other neurodegenerative diseases complicates predictions of disease progression
and development of potential therapies, making clinical trials challenging. Uncertainty surrounding prognosis is
an enormous burden for people with ALS and their families. Implementing better models to identify and recruit
people living with ultra-rare forms of diseases like ALS with known genetic mutations or PLS is essential.
“Traditional” models of NHS in ultra-rare diseases are not effective, as participating in NHS research sites are
being selected first, while people living with those conditions may not be attending the preselected clinics.
While the Food and Drug Administration encourages the use of approaches and technologies to minimize the
burden of trials on patients and limit the need for travel to study sites and is open to exploring the utility of digital
biomarkers as clinical endpoints, implementation of such methods as decentralized clinical research with key
endpoint measures at baseline and at intervals during the trial conducted in a standardized fashion at central
testing facilities, remote monitoring for some of the visits, etc. are not utilized broadly..
We propose a decentralized model for the NHS conduct, in which we implement a disease-agnostic people-
centric Platform, NeuroPRO™, for recruitment and e-consent study participants, diagnosis confirmation, and
baseline data acquisition. This Platform will be used to:
 • Conduct a stand-alone decentralized longitudinal NHS utilizing digital biomarkers and periodic home or
 nearest clinical hubs visits.
 • Conduct a hybrid NHS, in which this people-centric platform may serve either as an equal partner to a
 “traditional” NHS (ALS/MND Natural History Study), or as participants identification and recruitment tool,
 while clinical outcomes are still being measured during clinical visits, or as also an optimization tool for
 participating sites selection based on geographical distribution of recruited participants (PLS Natural
 History Study).
 • Provide regulatory compliant environment for rapid simultaneous validation of digital biomarkers against
 widely utilized outcomes.
The data from the studies will be anonymized and shared with the medical research community.

## Key facts

- **NIH application ID:** 10931549
- **Project number:** 5U01FD008125-02
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Alexander V Sherman
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** FDA
- **Fiscal year:** 2024
- **Award amount:** $399,250
- **Award type:** 5
- **Project period:** 2023-09-15 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10931549

## Citation

> US National Institutes of Health, RePORTER application 10931549, Creating a disease-agnostic scalable platform for decentralized observational and validation of digital biomarkers studies and piloting it for people with familial ALS and ultra-rare MNDs (5U01FD008125-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10931549. Licensed CC0.

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