Studies presented at the AACR Annual Meeting 2026 evaluate the clinical readiness of a liquid biopsy platform for symptomatic women.
AOA Dx presented new data at the American Association for Cancer Research (AACR) Annual Meeting 2026 supporting a noninvasive, blood-based test for the early detection of ovarian cancer. The studies focus on the clinical application of the AKRIVIS GD Test System for women experiencing signs and symptoms of the disease.
Ovarian cancer is often diagnosed at late stages because symptoms are frequently vague and overlap with other conditions. The diagnostic platform utilizes liquid chromatography-mass spectrometry (LC-MS) and machine learning to analyze biological changes across metabolites, lipids, and proteins in the blood.
“The women who need this test are in clinics right now, symptomatic, concerned, and waiting for answers that existing tools weren’t built to give them,” says Oriana Papin-Zoghbi, CEO of AOA Dx, in a release. “We have built a platform that meets that moment. The data we are presenting at AACR are a direct reflection of our deliberate, differentiated approach: clinical-grade LC-MS infrastructure purpose-built for multi-omic cancer diagnostics, combined with machine learning that reads across biological systems the way cancer actually behaves.”
Translating Lipidomics to Clinical Use
The first study, titled “Translating to Targeted: Bridging Discovery Lipidomics to Multi-Omic Clinical Diagnostic Application in Ovarian Cancer Detection,” detailed the translation of discovery-based lipidomics into a targeted LC-MS assay.
In an independent cohort of clinical controls, the test achieved an area under the curve of 0.92. The research describes a framework for translating molecular pathways involved in lipid and metabolite metabolism within the tumor microenvironment into a diagnostic tool. According to the company, the study demonstrated that biological signals are interconnected and early-stage detection performance is maintained in complex clinical environments.
Metabolomic Consistency Across Populations
A second study analyzed 944 blood samples from symptomatic patients in the US and United Kingdom. This research identified reproducible metabolic pathway dysregulation across both independent populations.
The findings suggest that the biological signals identified by the platform are consistent markers of disease rather than artifacts of a single dataset. This study represents the largest serum metabolomics profiling of a symptomatic ovarian cancer population conducted to date.
“The data we are presenting are so exciting because we observe the same metabolic and lipid signals emerge consistently across large, independent patient cohorts,” says Abigail McElhinny, chief scientific officer of AOA Dx, in a release. “One poster highlights reproducible metabolomic pathways observed across hundreds of ovarian cancer samples within a complex set of symptomatic controls, while the other poster shows how those biomarker discovery findings can be translated into a targeted blood-based assay.”
Clinical Performance and Future Access
Previously published data for the AKRIVIS GD system demonstrated 94.8% sensitivity for early-stage ovarian cancer and 94.4% sensitivity across all stages and subtypes. The company is currently preparing for an early access program for the test system.
In addition to the poster presentations, a peer-reviewed article regarding the use of lipidomics and protein biomarkers for ovarian cancer detection was selected by AACR journal editors for a featured collection on prevention and early detection.
To support the path toward commercial scale, AOA Dx recently added Chris Roberts as chief product officer and Cory Bystrom as senior director of biomarker and analytical development. Roberts brings experience in diagnostic platform development, while Bystrom specializes in the translation of LC-MS diagnostics from discovery to clinical deployment.
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