Caris Life Sciences Launches Caris MI Clarity, the First and Only AI-Powered Test to Predict Both Early and Late Distant Recurrence Risk in Breast Cancer at the Time of Diagnosis

Rhea-AI Summary

Caris Life Sciences (NASDAQ: CAI) launched Caris MI Clarity, an AI-powered prognostic test that predicts both early (0–5 years) and late (5–15 years) distant recurrence risk for postmenopausal patients with HR-positive/HER2-negative, node-negative early-stage breast cancer at diagnosis. Results are typically returned within 3 business days. The model was trained on Caris' multimodal dataset and validated using samples from national trials including TAILORx and NSABP B-42. The test uses digitized H&E slides plus clinical inputs and does not require genomic sequencing, enabling scalability from routine pathology specimens.

Positive

• Predicts early and late distant recurrence from a single test at diagnosis
• 3 business day turnaround time compared with historical multi-week timelines
• Validated using samples from TAILORx and NSABP B-42 (ECOG-ACRIN/NRG Oncology)
• No sequencing required—uses digitized H&E slides and clinical inputs for accessibility

Negative

• No numeric performance metrics (sensitivity, specificity, hazard ratios) disclosed in the announcement
• No regulatory approval or coverage details stated, which may affect clinical adoption
• Intended population is limited to postmenopausal HR-positive/HER2-negative, node-negative patients

News Market Reaction – CAI

+1.39%

+1.39% Session close to close

In the May 5 session, CAI gained 1.39%, reflecting a mild positive market reaction.

Data tracked by StockTitan Argus on the day of publication.

Market Context

This announcement introduces Caris MI Clarity, an AI‑powered test delivering breast cancer distant‑r...

Analysis

This announcement introduces Caris MI Clarity, an AI‑powered test delivering breast cancer distant‑recurrence risk within 3 business days, stratified over 0–5 and 5–15 year windows. It extends Caris’ AI strategy seen in recent GBM, NSCLC, ovarian and pancreatic signatures. Investors may watch how broadly clinicians adopt this pathology‑based approach, how it integrates with existing tools, and how upcoming events, including scheduled financial results, update the overall growth narrative.

Key Figures

Result turnaround time: 3 business days Early recurrence window: 0–5 years Late recurrence window: 5–15 years +2 more

5 metrics

Result turnaround time 3 business days Time to deliver Caris MI Clarity test results

Early recurrence window 0–5 years Time horizon for early distant recurrence risk in MI Clarity

Late recurrence window 5–15 years Time horizon for late distant recurrence risk in MI Clarity

Risk categories Low / High Stratification for early and late distant recurrence risk

Data scale Tens of thousands of samples Breast cancer cases used to train MI Clarity models

Previous AI Reports

5 past events · Latest: Apr 29 (Positive)

Same Type Pattern 5 events

Date	Event	Sentiment	24h Move	Catalyst
Apr 29	AI validation study	Positive	-3.6%	Peer‑reviewed validation of AI signature for MGMT methylation and TMZ benefit in GBM.
Apr 08	AI NSCLC signature	Positive	+4.0%	Launch of AI signature guiding chemo addition decisions in PD‑L1 ≥50% NSCLC.
Mar 26	AI brain metastasis risk	Positive	-1.2%	New AI signatures predicting brain metastases risk in breast cancer and NSCLC.
Mar 16	AI ovarian resistance	Positive	+3.5%	AI signature predicting early platinum resistance in high‑grade serous ovarian cancer.
Mar 09	AI pancreatic therapy	Positive	+2.2%	AI signature to guide first‑line regimen selection and de‑escalation in PDAC.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

Recent AI‑tagged releases generally drew modest reactions, with a mix of positive and negative price moves despite consistently positive clinical/AI content.

Recent Company History

Over the last two months, Caris released multiple AI‑driven oncology insights across glioblastoma, NSCLC, breast, ovarian and pancreatic cancers. Prior AI news on March 9, March 16, March 26 and April 8 highlighted new multimodal signatures leveraging WES/WTS and large clinico‑genomic datasets. The latest April 29 glioblastoma study provided peer‑reviewed validation but saw a negative price reaction. Today’s AI‑based breast cancer recurrence test launch extends this same AI precision‑oncology theme into risk prediction at diagnosis.

Key Terms

hr-positive/her2-negative, node-negative, hematoxylin and eosin (h&e), distant recurrence, +4 more

8 terms

hr-positive/her2-negative medical

"postmenopausal patients with HR-positive/HER2-negative, node-negative early-stage breast cancer"

A tumor classification meaning the cancer has hormone receptors (it grows in response to estrogen or progesterone) but does not have excess HER2 protein that some cancers use to grow. For investors, this matters because it determines which treatments are likely to work—typically hormone-blocking drugs rather than HER2-targeted therapies—so it shapes drug sales potential, clinical trial design and the competitive landscape for therapies, like knowing which key will open the lock.

node-negative medical

"HR-positive/HER2-negative, node-negative early-stage breast cancer at the time of diagnosis"

Node-negative describes a cancer diagnosis in which nearby lymph nodes show no evidence of tumor cells. For investors, this matters because node-negative status often indicates an earlier-stage disease with a better prognosis, different treatment options, and can affect the size and urgency of the market for diagnostics, drugs, or devices tied to that condition—similar to finding damage confined to one room rather than spread through a house.

hematoxylin and eosin (h&e) medical

"digitized hematoxylin and eosin (H&E) slides for key markers of recurrence"

A standard laboratory staining method used on tissue samples to reveal cell and tissue structure under a microscope: hematoxylin colors cell nuclei blue and eosin colors other tissue parts pink, creating contrast much like coloring a map to make roads and landmarks easy to see. Investors should care because H&E is the routine test pathologists use to diagnose disease, judge treatment effects in clinical trials, and confirm biopsy-based endpoints, so its findings can directly influence trial outcomes, regulatory decisions, and a medical product’s commercial prospects.

distant recurrence medical

"insight into both early and late distant recurrence risk for postmenopausal patients"

Distant recurrence is when a disease such as cancer comes back in a part of the body far from where it first appeared, meaning new tumors appear in separate organs or tissues. For investors, distant recurrence matters because it is a key measure of how well a therapy prevents spread, affects clinical trial success, regulatory decisions, long-term market potential and forecasts; think of it like weeds reappearing in a different corner of a garden despite local treatment.

computational pathology technical

"using computational pathology and AI-driven machine learning"

Computational pathology uses software, machine learning and image analysis to turn microscope slides and digital tissue scans into measurable data and diagnostic insights, acting like a digital assistant for pathologists. It matters to investors because it can speed and standardize diagnoses, uncover patterns humans might miss, improve selection and monitoring in drug trials, and create new software, service or device revenue streams that can lower costs and change how hospitals and labs allocate spending.

whole-slide pathology images medical

"model analyzes digitized H&E whole-slide pathology images together with clinical inputs"

Whole-slide pathology images are high-resolution digital scans of entire glass microscope slides that capture tissue samples used to diagnose disease; think of photographing a full map rather than a few snapshots. They matter to investors because they enable scalable storage, remote review, and computer-assisted analysis—opening markets for digital diagnostics, software tools, and cloud services while potentially speeding diagnosis and reducing costs for healthcare providers.

genomic sequencing medical

"prognostic insight without requiring genomic sequencing"

Genomic sequencing is the process of reading the exact order of the DNA building blocks that make up an organism’s complete genetic instruction manual, like decoding every letter in a very long book. For investors, it matters because that decoded information drives new diagnostics, targeted drugs, and personalized treatments, shaping which biotech products reach the market, how companies compete, and the size and timing of potential revenues or partnerships.

ai-driven machine learning technical

"using computational pathology and AI-driven machine learning"

AI-driven machine learning uses computer systems that automatically find patterns in large datasets and improve their predictions or decisions over time without being explicitly reprogrammed. Think of it like a digital assistant that learns from experience to automate tasks, spot trends or forecast outcomes. Investors watch for this because it can lower costs, create new revenue streams or disrupt competitors, but its value depends on data quality, implementation and regulatory limits.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Caris MI Clarity leverages AI to transform how recurrence risk is understood and applied in postmenopausal patients with HR-positive/HER2-negative, node-negative early-stage breast cancer

IRVING, Texas, May 5, 2026 /PRNewswire/ -- Caris Life Sciences® (NASDAQ: CAI), a leading patient-centric next-generation AI TechBio company and precision medicine pioneer, today announced the launch of Caris MI Clarity™, the first prognostic test designed to deliver insight into both early and late distant recurrence risk for postmenopausal patients with HR-positive/HER2-negative, node-negative early-stage breast cancer at the time of diagnosis. Results are typically provided to the ordering physician within 3 business days of receiving the tissue sample, compared to a few weeks for historical tests.

The test was developed by leveraging Caris' proprietary multi-modal dataset, which contains tens of thousands of breast cancer samples, to train a series of models to analyze genetic features from digitized hematoxylin and eosin (H&E) slides for key markers of recurrence.  These features were then used to train and evaluate a model to assess both early and late recurrence risk.  The model was validated through a multi-year public-private research partnership with ECOG-ACRIN Cancer Research Group, utilizing samples and associated data from well-characterized national clinical trials, including ECOG-ACRIN's TAILORx and NSABP B-42 conducted by NRG Oncology. The model's focus on distant recurrence directly addresses the outcomes most closely associated with breast cancer mortality and long-term patient management.

For patients with early-stage breast cancer, accurately assessing the risk of distant recurrence is essential, as distant recurrence is the primary driver of mortality and a key factor in systemic treatment decisions. Distant recurrence risk is not static, but evolves over time, shaped by tumor biology, disease subtype, and treatment. In HR-positive disease, risk can persist for many years. Notably, the biological factors that drive distant recurrence in the first five years differ from those that contribute to recurrence five to fifteen years after diagnosis and a patient's early and late risks often do not align.

"Breast cancer clinicians have long been forced to make some of the most consequential treatment decisions with an incomplete picture of how recurrence risk changes over time," said George W. Sledge, Jr., MD, Chief Medical Officer at Caris. "Caris MI Clarity is designed to bring early and late distant recurrence risk together in a single test at diagnosis, when treatment decisions matter most. By leveraging AI on routine pathology and clinical data, Caris MI Clarity has the potential to fundamentally improve how we personalize care for postmenopausal patients with HR-positive/HER2-negative, node-negative breast cancer."

Current risk assessment tools provide valuable but partial insight, often focusing on only one phase of distant recurrence risk. As a result, clinicians frequently evaluate early and late distant recurrence risk separately, relying on different tools and datasets. This fragmented approach adds complexity to treatment planning and increases the challenge of balancing overtreatment, which can expose patients to unnecessary toxicity, with undertreatment, which may miss opportunities to meaningfully reduce distant recurrence risk, particularly in HR-positive disease, where risk can remain clinically relevant long after initial therapy.

The Caris MI Clarity model analyzes digitized H&E whole-slide pathology images together with clinical inputs using computational pathology and AI-driven machine learning. By identifying subtle histologic and clinical patterns associated with distant recurrence, Caris MI Clarity generates clinically relevant prognostic insight without requiring genomic sequencing. The test leverages standard pathology specimens that are already collected as part of routine care, ensuring accessibility and scalability without additional tissue requirements.

Caris MI Clarity provides distinct risk stratification into Low- or High-risk categories for both early (0–5 years) and late (5–15 years) distant recurrence, enabling clinicians to understand how distant recurrence risk may unfold over time from a single test performed at diagnosis.

The launch of Caris MI Clarity underscores Caris Life Sciences' continued expansion into advanced AI-driven, multimodal risk assessment. By integrating pathology and clinical data, Caris leverages its proprietary multi-modal dataset to advance a more comprehensive approach to understanding cancer biology and patient risk across the continuum of disease.

About Caris Life Sciences
Caris Life Sciences® (Caris) is a leading, patient-centric, next-generation AI TechBio company and precision medicine pioneer actively developing and commercializing innovative solutions to transform healthcare. Through comprehensive molecular profiling (Whole Genome, Whole Exome and Whole Transcriptome Sequencing), advanced AI and machine learning, Caris has created the large-scale, multimodal clinico-genomic database and computing capability needed to analyze and further unravel the molecular complexity of disease. This convergence of next-generation sequencing, AI and machine learning technologies and high-performance computing provides a differentiated platform for developing the latest generation of advanced precision medicine diagnostic solutions for early detection, diagnosis, monitoring, therapy selection and drug development.  

Caris was founded with a vision to realize the potential of precision medicine to improve the human condition. Headquartered in Irving, Texas, Caris has offices in Phoenix, New York, Cambridge (MA), Tokyo, Japan and Basel, Switzerland. Caris or its distributor partners provide services in the U.S. and other international markets.  

Forward Looking Statements 
This press release contains forward-looking statements within the meaning of the federal securities laws. All statements other than statements of historical facts contained in this press release are forward-looking statements, including statements regarding our business, solutions, plans, objectives, goals, industry trends, financial outlook and guidance. In some cases forward-looking statements can be identified by words such as "may," "will," "should," "would," "expect," "plan," "anticipate," "could," "intend," "target," "project," "contemplate," "believe," "estimate," "predict," "potential" or "continue" or similar expressions.   

You should not rely upon forward-looking statements as predictions of future events. Although we believe that the expectations reflected in these forward-looking statements are reasonable based on information currently available to us, we cannot guarantee that the future results, discoveries, levels of activity, performance or events and circumstances reflected in forward-looking statements will be achieved or occur. Forward-looking statements involve known and unknown risks and uncertainties, some of which are beyond our control. Risks and uncertainties that could cause our actual results to differ materially from those indicated or implied by the forward-looking statements in this press release include, among other things: developments in the precision medicine industry; our future financial performance, results of operations or other operational results or metrics; development, analytical and clinical validation, timing and performance of future solutions by us and our competitors; commercial market acceptance for our solutions, including acceptance of preventive as well as diagnostic testing paradigms, and our ability to meet resulting demand; the rapidly evolving competitive environment in which we operate; third-party payer reimbursement and coverage decisions related to our solutions; risks related to data management, storage, and processing capabilities and our ability to integrate and deploy artificial intelligence and advanced data analytics technologies; our ability to protect and enhance our intellectual property; regulatory requirements, decisions or approvals (including the timing and conditions thereof) related to our solutions; reliance on third-party suppliers; risks related to data security, patient privacy, and compliance with healthcare data protection regulations as well as potential cybersecurity threats to our data platforms; our compliance with laws and regulations; the outcome of government investigations and litigation; risks related to our indebtedness; and our ability to hire and retain key personnel as well as risks, uncertainties, and other factors described in the section titled "Risk Factors" and elsewhere in our Annual Report on Form 10-K filed with the Securities and Exchange Commission (SEC) on March 3, 2026, and in our other filings we make with the SEC from time to time. We undertake no obligation to update any forward-looking statements to reflect changes in events, circumstances or our beliefs after the date of this press release, except as required by law. 

Caris Life Sciences Media:  
Corporate Communications
CorpComm@CarisLS.com
214.294.5606 

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SOURCE Caris Life Sciences

FAQ

What is Caris MI Clarity and who is it for (CAI)?

Caris MI Clarity is an AI-driven prognostic test for postmenopausal patients with HR-positive/HER2-negative, node-negative early breast cancer. According to the company, it predicts both early (0–5 years) and late (5–15 years) distant recurrence risk from routine pathology.

How long does Caris MI Clarity (CAI) take to return results?

Results are typically provided within 3 business days after the lab receives tissue. According to the company, this is faster than historical tests that often take several weeks, improving information timing for treatment decisions.

Does Caris MI Clarity (CAI) require genomic sequencing?

No, the test does not require genomic sequencing; it analyzes digitized H&E slides plus clinical inputs. According to the company, this enables use of standard pathology specimens and supports broader accessibility and scalability.

What evidence supports Caris MI Clarity (CAI) performance?

The model was validated using samples and data from national clinical trials, including TAILORx and NSABP B-42. According to the company, validation occurred through a multi-year public-private research partnership with ECOG-ACRIN/NRG Oncology.

Will Caris MI Clarity (CAI) change treatment planning for breast cancer?

The test is designed to inform systemic treatment decisions by showing early and late distant recurrence risk from diagnosis. According to the company, providing both time-based risk categories may help clinicians balance overtreatment and undertreatment.