Changeflow GovPing Healthcare & Life Sciences System and Method for Detection of Disease usin...
Routine Notice Added Final

System and Method for Detection of Disease using Machine Learning

Email

Summary

The USPTO has published a new patent application (US20260088169A1) detailing systems and methods for detecting systemic disease from bacterial samples using machine learning. The application, filed by inventors Mark Driscoll and Daniel Fasulo, focuses on correlating microbiome sequence data with disease states or risk.

Published by USPTO on changeflow.com . Detected, standardized, and enriched by GovPing. Review our methodology and editorial standards .

What changed

This document is a USPTO patent application (US20260088169A1) for a system and method to detect systemic disease using machine learning on bacterial samples. The invention utilizes a high-throughput microbial profiling platform to diagnose disease or identify risk by correlating patient microbiome sequence data with disease states. The application was filed on September 23, 2024.

As this is a patent application, it does not impose direct regulatory obligations on healthcare providers or manufacturers. However, it signals potential future technological advancements in disease diagnostics and risk assessment. Compliance officers in the healthcare and pharmaceutical sectors should be aware of emerging technologies that may impact diagnostic tools, data analysis, and patient risk stratification in the future.

Archived snapshot

Mar 26, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

SYSTEM AND METHOD FOR DETECTION OF DISEASE

Application US20260088169A1 Kind: A1 Mar 26, 2026

Inventors

Mark Driscoll, Daniel Fasulo

Abstract

The present invention provides systems and methods for the detection of systemic disease from bacterial content samples obtained from a subject. Also provided are methods of training a machine learning algorithm to correlate patient microbiome sequence data with a disease state or disease development risk. These systems and methods utilize a high-resolution, database-independent, high-throughput microbial profiling platform to diagnose systemic disease in patients or to identify those patients at risk of developing systemic disease. Also provided are systems and kits for carrying out the methods.

CPC Classifications

G16H 50/20 G16B 30/00 G16B 40/20 G16H 10/40 G16H 50/30 G16H 50/70

Filing Date

2024-09-23

Application No.

18445677

View original document →

Named provisions

Abstract Inventors CPC Classifications

Get daily alerts for USPTO Patent Applications - Health Informatics (G16H)

Daily digest delivered to your inbox.

Free. Unsubscribe anytime.

About this page

What is GovPing?

Every important government, regulator, and court update from around the world. One place. Real-time. Free. Our mission

What's from the agency?

Source document text, dates, docket IDs, and authority are extracted directly from USPTO.

What's AI-generated?

The summary, classification, recommended actions, deadlines, and penalty information are AI-generated from the original text and may contain errors. Always verify against the source document.

Last updated

Classification

Agency
USPTO
Instrument
Notice
Legal weight
Non-binding
Stage
Final
Change scope
Minor
Document ID
US20260088169A1

Who this affects

Applies to
Healthcare providers Drug manufacturers
Industry sector
3254 Pharmaceutical Manufacturing 6211 Healthcare Providers 3345 Medical Device Manufacturing
Activity scope
Disease Diagnosis Medical Research
Geographic scope
United States US

Taxonomy

Primary area
Healthcare
Operational domain
Research & Development
Compliance frameworks
FDA 21 CFR Part 11 GxP
Topics
Artificial Intelligence Data Privacy

Get alerts for this source

We'll email you when USPTO Patent Applications - Health Informatics (G16H) publishes new changes.

Free. Unsubscribe anytime.

You're subscribed!