Epigenomic and Machine Learning Models to Predict Pancreatic Cancer
- Disease/Condition
- Pancreatic Cancer
- Drug/Device/Intervention
- Early diagnosis for Pancreatic Cancers in high-risk asymptomatic subject groups
- Study type
- Interventional
- Intervention type
- diagnostic test
- Primary sponsor
- European Institute of Oncology
- Location
- Toulouse,Milan,Cluj-Napoca,Barcelona, France,Italy,Romania,Spain
- Phase
- N/A
- Start date
- Feb 03, 2023
- End date
- Dec 31, 2024
- Enrollment
- 170 participants
Observation of a two or three-fold enrichment in early detection of suspicious pancreatic lesion using the CRPA algorithm,Identification of one or more abnormal methylation changes present in blood cells of participants with suspicious lesions versus methylation profiles of participants with no identified lesions,Validation of igenetic biomarker testing in liquid biopsy followed by radiological exam as early cancer diagnostic tool
The goal of the multicentric and interdisciplinary IMAGene project is to pursue early
 diagnosis for Pancreatic Cancers in high-risk asymptomatic subject groups, by developing and
 validating a comprehensive cancer risk prediction algorithm (CRPA) as a clinical support tool
 to calculate a personalized risk profile.
 
 The study is a longitudinal, non-randomized exploratory clinical study. A total of 170
 asymptomatic first-degree relatives of PC patients.
- Registry
- ClinicalTrials.gov
- Trial ID
- NCT06334458
- Type
- Non-Device Trial
Access comprehensive clinical trial information for NCT06334458 through Pure Global AI's free database. This phase not specified trial is sponsored by European Institute of Oncology and is currently Recruitment Completed. The study focuses on Pancreatic Cancer. Target enrollment is 170 participants.
This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.