Prospective Validation of Ataraxis AI Test for Predicting Treatment Response in Neoadjuvant Breast Cancer

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Conditions studied: Breast Cancer

In brief

This study evaluates the real-world clinical workflow integration of a previously developed artificial intelligence (AI) prognostic test in breast cancer patients receiving neoadjuvant chemotherapy, and validates its accuracy in predicting treatment response. 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.

Key facts

Study ID
NCT07327970
Run by
Young-Joon Kang
People needed
150
Starts
2026-01-20
Expected to finish
2027-12-31
Last updated by the study team
2026-03-27

Who can join

Age: 18 and older. Sex: female. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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