Development and Validation of a Digital Twin-based Clinical Research System (X Town Stage I)

Chronic diseases, characterized by their prolonged duration and slow progression, have emerged as predominant contributors to global morbidity and mortality. The investigators have developed a digital twin-based clinical research system (termed X Town) for chronic diseases, to predict clinical outcomes under various interventions. In this study, the investigators aim to evaluate the reliability of the developed digital twin-based clinical research system in predicting short-term clinical outcomes via virtual and real-world clinical studies.

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Key information

Conditions

Chronic Disease Disease Attributes Pathologic Processes Pathological Conditions, Signs and Symptoms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Shanghai Health and Medical Center

Wuxi, Jiangsu, China

Location status: Recruiting

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Age≥18 years old
Receiving care at a community health service centre
Able to understand and comply with the study procedures
Agrees to participate in the study and signs the informed consent form

Exclusion criteria

Patients with severe mental illness
Patients expected to be unable to complete follow-ups

Treatment and study plan

Primary outcomes

The agreement between the simulated short-term clinical outcomes in the virtual clinical studies and the real-world short-term clinical outcomes in the real-world clinical studies

Time frame: Within 3 months

We will use three predefined binary metrics to evaluate the agreement: (1) full statistical significance agreement, defined by effect estimates and CIs of the virtual and real-world clinical studies on the same side of the null; (2) estimate agreement, defined by whether effect estimates for the virtual clinical studies fell within the 95% CI for the real-world clinical study results; (3) standardized difference agreement between treatment effect estimates from the real-world clinical studies and the virtual clinical studies, defined by standardized differences (Reference: JAMA. 2023;329(16):1376-1385. doi:10.1001/jama.2023.4221).

Study contacts

Contact information is provided by the study sponsor or research team.

Huating Li, MD, PhD

CONTACT

[email protected]

+86-17749716891

Sponsors and collaborators

Lead sponsor

Shanghai 6th People's Hospital

Other

Collaborators

Shanghai Jiao Tong University School of Medicine
Tsinghua University

Registry information

Important dates

Study start: 2025
Primary completion: 2025
Study completion: 2025
First posted: Mar 6, 2025
Registry last updated: May 15, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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