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December 6, 2023

Exai Bio’s RNA- and AI-based Liquid Biopsy Platform Detects Early Stage Breast Cancer with High Accuracy, Overcoming Many Limitations of DNA-based Approaches

New data presented at the San Antonio Breast Cancer Symposium demonstrates strong detection performance of stage I breast cancer and ductal carcinoma in situ

Palo Alto, CA — Exai Bio today announced new data demonstrating that its novel RNA-based and AI-driven liquid biopsy platform can detect breast cancer at the earliest stages and the smallest tumor sizes, including ductal carcinoma in situ (DCIS), using a standard blood sample. In a new early detection study building upon prior data, stage I breast cancer sensitivity was 87% and tumor size T1a-b (10 mm or smaller) sensitivity was 81%, both at 90% specificity. Overall sensitivity across all invasive breast cancer stages was 88% at 90% specificity, far exceeding any DNA-based liquid biopsy performance. Exai additionally reported sensitivity of 78% for DCIS at 90% specificity. These results will be presented at a poster session today at the San Antonio Breast Cancer Symposium (SABCS) 2023 meeting.

Earlier detection of breast cancer is crucial for improved patient outcomes but cannot always be achieved through mammography, a modality which has well-established limitations. Confounding issues such as breast density, which masks the appearance of tumors and affects more than 40% of women, small tumor sizes, and imaging anomalies can result in false negatives and delayed diagnosis. In addition to mitigating these risk factors and technical issues, a blood test will also offer improved access and an increase in the number of women who receive screening each year. The data released today further support the potential of the Exai platform to complement mammography and enable earlier detection of breast cancer for more women.

“A routine blood test could meaningfully improve breast cancer screening and be a powerful complementary solution to mammography, especially for the millions of women with dense breast tissue,” stated Pat Arensdorf, Chief Executive Officer of Exai Bio. “Exai’s platform has demonstrated high accuracy in this expanded dataset by detecting the smallest tumors and earliest stages of disease, once again overcoming performance barriers that limit utility DNA-based liquid biopsy approaches.”

Exai’s platform uses RNA sequencing to identify a novel category of cancer-associated, small non-coding RNAs, termed orphan non-coding RNAs (oncRNAs). OncRNAs are actively secreted from living cancer cells and are stable and abundant in the blood of cancer patients. Exai has created a catalog of hundreds of thousands of oncRNAs and thousands of patient oncRNA profiles, spanning all major cancer types. When combined with proprietary artificial intelligence technology, the Exai platform has multiple technical and operational advantages over tests that focus on circulating tumor DNA. These include superior sensitivity and specificity, as well as the ability to reveal dynamic changes in the biology of a patient’s tumor over time.

Exai’s universal platform can be used across multiple cancer care settings such as screening and early detection, monitoring, molecular residual disease and therapy selection.

SABCS Poster Details

Poster Title: Cell-free orphan noncoding RNAs and AI enable early detection of invasive breast cancer and ductal carcinoma in situ

Poster ID: POS-13-08

Abstract Number: #1578895

Session Title: Spotlight Session: Poster Session 2

Authors: N. Tbeileh, T. Cavazos, M. Karimzadeh, Jeffrey Wang, A. Huang, T. Lam, S. Kilinc, Jieyang Wang, X. Zhao, A. Pohl, H. Li, L. Fish, K. Chau, M. Francis, L. Schwartzberg, P. Arensdorf, H. Goodarzi, F. Hormozdiari, B. Alipanahi

About Exai Bio

Exai Bio is a next-generation liquid biopsy company. Its mission is to enable a world where cancer can be detected early, diagnosed accurately, treated in a personalized and targeted way, and ultimately cured. The company’s proprietary RNA- and AI-based liquid biopsy technology delivers clinical insights into cancer biology to enable the earliest, most accurate diagnosis of cancer. For more information, please visit us on and follow us on Twitter and LinkedIn.

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