Prospective Validation of Ataraxis AI Test for Predicting Treatment Response in Neoadjuvant Breast Cancer
NCT ID: NCT07327970
Last Updated: 2026-01-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
150 participants
OBSERVATIONAL
2026-01-20
2027-12-31
Brief Summary
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The Ataraxis AI test analyzes digitized images of tumor biopsy slides combined with basic clinical information (age, tumor stage, hormone receptor status) to generate a risk score. Prior studies showed the AI test can predict cancer recurrence with accuracy comparable to or better than existing genomic tests.
The study has two stages:
* Stage 1 (30 patients): Assess whether the AI test can be practically integrated into routine clinical workflow, including ease of use, report clarity, and time requirements.
* Stage 2 (70-120 additional patients): Validate the accuracy of AI-predicted pathological complete response (pCR) rates against actual surgical outcomes.
This study uses a blinded design where treating physicians remain blinded to AI results until post-surgical pCR assessment. AI analysis is performed by the research coordinator in collaboration with Ataraxis. After pCR evaluation, AI results are disclosed and physicians complete surveys assessing hypothetical treatment changes. This design eliminates AI influence on treatment decisions and ensures independent validation.
Participants are adults with Stage I-III breast cancer planned for neoadjuvant chemotherapy. The study involves no additional procedures beyond standard care except for completing surveys about the AI test experience.
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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NAC Patients with AI Assessment
Stage I-III invasive breast cancer patients undergoing neoadjuvant chemotherapy. All participants receive standard-of-care treatment. AI analysis is performed but results remain blinded from treating physicians during NAC. AI results are disclosed only after surgery and pCR assessment for retrospective evaluation. Treatment decisions are made independently of AI results.
multi-modal foundation AI test
Multi-modal AI test combining digital pathology features from H\&E-stained core needle biopsy slides with clinical information (age, molecular biomarkers, TNM stage) to generate a continuous risk score (0-1) predicting pathological complete response. Results provided as reference information only; does not influence treatment decisions.
Interventions
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multi-modal foundation AI test
Multi-modal AI test combining digital pathology features from H\&E-stained core needle biopsy slides with clinical information (age, molecular biomarkers, TNM stage) to generate a continuous risk score (0-1) predicting pathological complete response. Results provided as reference information only; does not influence treatment decisions.
Eligibility Criteria
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Inclusion Criteria
* Planned for neoadjuvant chemotherapy
* H\&E-stained slides available from core needle biopsy
* Age 18 years or older
* Able to provide written informed consent
Exclusion Criteria
* Not a candidate for neoadjuvant chemotherapy
* H\&E slides not obtainable from core needle biopsy
* Unable to provide informed consent
18 Years
FEMALE
No
Sponsors
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Young-Joon Kang
OTHER
Responsible Party
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Young-Joon Kang
Assistant Professor
Central Contacts
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Other Identifiers
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ATARAXIS NEOP
Identifier Type: -
Identifier Source: org_study_id
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