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AI could help doctors personalize treatment for autoimmune hepatitis

NCT ID NCT07378202

Knowledge-focused Sponsor: Hannover Medical School Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study uses artificial intelligence to analyze data from 5,000 people with autoimmune hepatitis. The goal is to create a computer model that can predict which patients will respond well to standard therapy within 6 to 12 months. By identifying these patterns early, doctors may be able to adjust treatments sooner and improve long-term outcomes.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 5,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jan 2026

Expected to finish

Jan 2028

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

This project utilizes already established registries of patients with autoimmune hepatitis (AIH) from the international autoimmune hepatitis group (IAIHG), the European Reference Network on Rare liver diseases (R-LIVER), the spanish network on autoimmune hepatitis (colHAI) and the canadian network on autoimmune hepatitis (CANAL). Initial reports on the patient populations within the respective registries were separately published (doi: 10.1111/liv.16035, doi: 10.1097/HEP.0000000000000589, 10.1016/j.jhep.2024.03.021, 10.1097/HEP.0000000000000018 ).

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Diagnosis of Autoimmune hepatitis * Consent to provide data to the specific registry * available follow-up data at least within the first 12 months Exclusion Criteria: * variant syndromes * extrahepatic autoimmune disease * immunosuppressive treatment at diagnosis

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Conditions

The condition(s) this trial relates to.

autoimmune hepatitis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Autoimmune hepatitis

Contacts and locations

Locations

  • Else Kroener Fresenius Center for Digital Health, Technical University Dresden

    Dresden, Germany

  • Hannover Medical School

    Hanover, 30625, Germany

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