NCT06362629

AI App for Management of Atopic Dermatitis

Recruiting now NA Last updated 15 October 2024

What this trial tests

NA trial testing Artificial Intelligence assistant decision-making system (AIADMS) App in Atopic Dermatitis in 232 participants. Currently enrolling.

Timeline

1 September 2024

Primary endpoint
31 December 2028

31 August 2029

Quick facts

Lead sponsor	West China Hospital
Phase	NA
Status	Recruiting now
Study type	INTERVENTIONAL
Allocation	randomized
Design	parallel
Masking	none
Primary purpose	treatment
Enrollment	232
Start date	1 September 2024
Primary completion	31 December 2028
Estimated completion	31 August 2029
Sites	1 location across China

Drugs / interventions tested

• Artificial Intelligence assistant decision-making system (AIADMS) App

Conditions studied

• Atopic Dermatitis — all drugs for Atopic Dermatitis →
• Artificial Intelligence — all drugs for Artificial Intelligence →

Sponsor

West China Hospital

Who can join

Adults 1 to 75, any sex, with Atopic Dermatitis or Artificial Intelligence. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by recurrent rashes and itching, which seriously affects the quality of life of patients and brings heavy economic burden to society. The Treat to Target (T2T) strategy was proposed to guide optimal use of systemic therapies in patients with moderate to severe AD, and it is emphasized patients' adherence and combined evaluation from both health providers and patients. While effective treatments for AD are available, non-adherence of treatment is common in clinical practice due to the patients' unawareness of self-evaluation and lack of concern about the specific follow-up time points in clinics, which leads to the treatment failure and repeated relapse of AD.

Hypothesis: An Artificial Intelligence assistant decision-making system (AIADMS) with implementation of the T2T framework could help control the disease progression and improve the clinical outcomes for AD.

Overall objectives:

the investigators aim to develop an AIADMS in the form of smartphone app to integrate T2T approach for both clinicians and patients, and design clinical trials to verify the effectiveness and safety of the app. Methods: This project consists of three parts, AI training model for diagnosis and severity grading of AD based on deep learning, development of Artificial Intelligence assistant decision-making system (AIADMS) in the form of app, and design of a randomized controlled trial to verify the effectiveness and safety of AIADMS App for improvement of the clinical outcomes in AD patients.

Expected results: With application of AIADMS based app, the goal of T2T for patients with AD could be realized better, the prognosis could be improved, and more satisfaction could be achieved for both patients and clinicians.

Impact: This is the first AIADMS based app for AD management running through thediagnosis, patients' self-participation, medical follow-up, and evaluation of achievement of goal of T2T.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Construction and Evaluation of an Artificial Intelligence Assistant Decision-Making System Focused on the Treat-to-Target Framework and Full Process Management for Atopic Dermatitis: Study Protocol for a Randomized Controlled Trial.
   Li M, Liu Q, Chen Y, Liu Y, et al · · 2025 · cited 1× · PMID 40364047 · DOI 10.3390/jcm14093015