AI for Newborn Metabolic Screening

January 24, 2026 updated by: huzhenzhen, The Children's Hospital of Zhejiang University School of Medicine

Development and Clinical Validation of an Artificial Intelligence-Based Interpretation System for Newborn Screening of Inherited Metabolic Disorders

The goal of this clinical trial is to evaluate whether an artificial intelligence (AI)-based interpretation system can accurately diagnose inherited metabolic disorders in newborns undergoing routine screening. The main questions it aims to answer are:

What is the sensitivity and specificity of the AI system compared to standard manual interpretation? Does the AI system reduce variability in screening results? Researchers will compare the AI interpretation results with those from standard manual review by trained laboratory staff to assess diagnostic performance.

Participants will:

Have their routine newborn screening blood samples analyzed using both the AI system and standard manual interpretation Be followed according to national newborn screening guidelines if either method indicates a positive result

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

200000

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Zhejiang
      • Hangzhou, Zhejiang, China, 310000
        • The Children's Hospital, Zhejiang University School of Medicine
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Newborns who underwent routine newborn screening for inherited metabolic disorders at the Zhejiang Provincial Newborn Screening Center between May 2025 and December 2027
  • Blood samples collected between 2 and 28 days of age
  • Availability of complete newborn screening test data and essential clinical information

Exclusion Criteria:

  • Missing, incomplete, or poor-quality screening data
  • Duplicate samples from the same newborn

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Screening
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: AI and Manual Interpretation of Newborn Screening Data
Diagnostic test: Artificial intelligence-based interpretation system for newborn genetic metabolic disease screening
This intervention is a deep learning-based software algorithm designed specifically for the interpretation of tandem mass spectrometry (MS/MS) data from routine newborn screening in Chinese neonates. It integrates clinical covariates-including gestational age, birth weight, and blood collection time-to perform multiple-of-the-median (MOM) normalization and simultaneously evaluates 42 inherited metabolic disorders. Unlike existing AI tools developed for older-generation screening panels (e.g., those covering only 29 analytes), this system is trained and validated on over 300,000 real-world Chinese newborn samples, making it the first AI diagnostic tool tailored to China's current expanded newborn screening program.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
Sensitivity of the AI interpretation system for detecting inherited metabolic disorders
Time Frame: Within 12 months after newborn screening
Within 12 months after newborn screening
Specificity of the AI interpretation system for detecting inherited metabolic disorders
Time Frame: Within 12 months after newborn screening
Within 12 months after newborn screening

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

The Children's Hospital of Zhejiang University School of Medicine

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

January 1, 2027

Primary Completion (Estimated)

June 30, 2028

Study Completion (Estimated)

November 30, 2028

Study Registration Dates

First Submitted

January 16, 2026

First Submitted That Met QC Criteria

January 16, 2026

First Posted (Actual)

January 26, 2026

Study Record Updates

Last Update Posted (Actual)

January 27, 2026

Last Update Submitted That Met QC Criteria

January 24, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • 2025-IRB-0550-P-01

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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