AI-Powered Precision for Neoadjuvant Therapy Planning

Ataraxis™ Breast NEO

Ataraxis Breast NEO is an AI-powered test that helps guide neoadjuvant therapy decision prior to surgery for patients with stage I–III breast cancer across all subtypes. By analyzing morphological features from standard H&E slides together with clinical data, the test delivers an individual’s likelihood of achieving pathologic complete response (pCR) after neoadjuvant therapy.

Overall pCR likelihood: deeper predictive insight for neoadjuvant decision-making

How do we predict likelihood of achieving pCR?

Data you already have

Our platform uses the existing H&E-stained biopsy or resection slide collected during diagnosis, along with standard clinical variables such as:

Tumor size and nodal status
ER, PR, and HER2 status
Age and histologic subtype

Multimodal AI Analysis

The Ataraxis AI model evaluates over 10,000 micro-regions within the slide to capture tumor morphology, immune infiltration, and stromal architecture—features that correlate strongly with treatment response.
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These imaging-derived signals are integrated with clinical variables in a deep neural network that outputs a single, interpretable probability score.

Predictive Output

The test provides a continuous probability (%) of achieving a pathologic complete response (pCR) with neoadjuvant therapy.

It reports one predictive score: Overall pCR likelihood.

How to interpret results:

High likelihood of pCR: Patient is likely to respond to standard neoadjuvant therapy → supports confidence in the treatment plan.
Low likelihood of pCR: Suggests consideration of alternative neoadjuvant regimens or an upfront surgery approach.

Ataraxis Breast NEO was trained and evaluated on ~2500 patients from US and abroad

~1,000 patients

Training

~1,500 patients

Evaluation

Neo categories help to classify patients into groups based on pCR likelihood

HR+HER2- (n=296)

AUC:0.85 (0.76-0.96)

HER2+ (N=916)

AUC:0.66 (0.60-0.73)

TNBC (N=254)

AUC:0.77 (0.68-0.86)

NEO identifies which clinically node-positive patients will achieve nodal clearence (ypN0) after neoadjuvant therapy

75% of HR+/HER2-cN+ patients with NEO-High score (~20% of all HR+/HER2- patients) acheived nodal clearance.

NEO categories help to classify patients into groups based on pCR likelihood

Ataraxis Breast NEO accurately predicts neoadjuvant therapy response in all subtypes

High

64%

Average pCR rate in HER2-positive patients

55.1%

Ataraxis™ Breast NEO test report provides both risk category group (low, intermediate, high) as well as calibrated individualized probability of pathologic complete response for even greater granularity of predictions.

NEO showed good calibration with no statistically significant bias (Spiegelhalter's z-test; p=0.77) across all subtypes. 2

Learn more about our technology

Make the most informed call for your patients.

How likely is treatment before surgery to eliminate cancer?

Personalized insight to guide your first treatment choice

Female doctor showing information on a tablet to a woman patient in a consultation.

If you’ve been diagnosed with breast cancer, your doctor may recommend treatment before surgery, called neoadjuvant therapy. It can be an important step, but it’s often hard to know upfront how well it will work.

Ataraxis Breast NEO uses the biopsy slides already collected during your care, plus routine clinical information, to estimate how your cancer is likely to respond. No new procedures are needed.

Our test can be used for early-stage breast cancer across:

All molecular subtypes, regardless of ER, PR, or HER2 status
Premenopausal women and postmenopausal women
Regardless of cancer presence in lymph nodes

I might want this test if...

My doctor is recommending treatment before surgery, and I want to know my chances of a complete response.

I’m choosing between different pre-surgery treatment plans and want guidance tailored to me.

Keeping or clearing cancer from the lymph nodes is a key concern in my treatment plan.

I’m hoping for breast-conserving surgery, and want to know if treatment is likely to shrink the tumor enough.

I'm in a gray area under standard guidelines, and want a more personalized answer.

I want to avoid unnecessary treatment and side effects if the expected benefit is low.

How do we predict likelihood of achieving pCR?

Data you already have

Our platform uses the existing H&E-stained biopsy or resection slide collected during diagnosis, along with standard clinical variables such as:

Tumor size and nodal status
ER, PR, and HER2 status
Age and histologic subtype

Multimodal AI Analysis

Predictive Output

The test provides a continuous probability (%) of achieving a pathologic complete response (pCR) with neoadjuvant therapy.

It reports one predictive score: Overall pCR likelihood.

How to interpret results:

High likelihood of pCR: Patient is likely to respond to standard neoadjuvant therapy → supports confidence in the treatment plan.
Low likelihood of pCR: Suggests consideration of alternative neoadjuvant regimens or an upfront surgery approach.

Ataraxis Breast NEO was trained and evaluated on ~2500 patients from US and abroad

~1,000 patients

Training

~1,500 patients

Evaluation

What does pCR mean and why is it so important?

Achieving pCR means that after neoadjuvant therapy, no cancer is found in the breast or lymph nodes at surgery. Patients who achieve pCR usually have:

A much lower risk of the cancer returning

Some of the best long-term outcomes

Knowing your chance of pCR upfront can help you and your doctor choose the treatment plan that fits you best.

Two circular illustrations comparing tissue before and after treatment; before treatment shows clustered blue active cancer cells among red cells, after treatment shows only red cells with a checkmark, indicating no cancer found and successful treatment.

Learn more about our technology

Could this test guide your care?
Let's talk.

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AI-Powered Precision for Neoadjuvant Therapy Planning

Ataraxis™ Breast NEO

Overall pCR likelihood: deeper predictive insight for neoadjuvant decision-making

How do we predict likelihood of achieving pCR?

Ataraxis Breast NEO was trained and evaluated on ~2500 patients from US and abroad

Neo categories help to classify patients into groups based on pCR likelihood

NEO identifies which clinically node-positive patients will achieve nodal clearence (ypN0) after neoadjuvant therapy

NEO categories help to classify patients into groups based on pCR likelihood

Learn more about our technology

Make the most informed call for your patients.

How likely is treatment before surgery to eliminate cancer?

Personalized insight to guide your first treatment choice

I might want this test if...

How do we predict likelihood of achieving pCR?

Ataraxis Breast NEO was trained and evaluated on ~2500 patients from US and abroad

What does pCR mean and why is it so important?

Learn more about our technology

Could this test guide your care? Let's talk.

Could this test guide your care?
Let's talk.