For Anna Jeter, the story behind AOA Dx’s promising ovarian cancer diagnostic begins with a misconception. Despite serving more than half the population, women’s health continues to be viewed by many investors as a niche category—an assumption Jeter believes has contributed to decades of underinvestment in some of medicine’s most pressing unmet needs.
“Whenever you speak to investors about women’s health, there’s this perception that it’s somehow a smaller market,” Jeter, co-founder and chief regulatory officer of AOA Dx, told Inside Precision Medicine. “Women represent 51% of the population, but historically women’s health has been treated as a specialty category rather than a major healthcare market.”
That perception has shaped innovation patterns across healthcare, particularly in diagnostics. Despite advances in genomics, liquid biopsy, and AI in oncology, ovarian cancer detection has stagnated. The biomarker Cancer Antigen 125 (CA-125), introduced in 1987, remains the primary blood-based tool used to evaluate women presenting with symptoms suggestive of ovarian malignancy.
“There have been very few advancements in ovarian cancer,” Jeter said. “The standard of care today is still largely based on technology that became available almost 40 years ago.”
Early detection could have massive, life-changing consequences, as ovarian cancer is often highly treatable when diagnosed early. More than 90% of women survive when the disease is identified at stage 1, yet nearly 80% of cases are diagnosed only after the cancer has progressed to advanced stages.
After more than 15 years of developing diagnostics companies centered around women’s health, Jeter, Oriana Papin-Zoghbi, and Alex Fischer decided to take action and co-founded AOA Dx. Through an early partnership with McGill University, the team began investigating whether emerging advances in multi-omics could uncover biological signals that existing ovarian cancer diagnostics were missing.
AOA Dx recently announced that its investigational blood test, AKRIVIS GD, achieved 92% sensitivity for Stage I and II ovarian cancer detection in symptomatic women—nearly double the sensitivity historically associated with CA-125 alone.
Yet Jeter argues the most important aspect of the findings is not the performance metric itself, but what enabled it: the successful translation of lipid biomarkers into a clinical oncology assay. “We are now looking at lipids as very specific biomarkers, which have made a major impact on our ability to detect ovarian cancer significantly earlier,” she said. “And we believe this approach can be translated into other cancers in the future.”
In fact, it may even go beyond that, as the most notable multi-omic approaches using lipidomics and proteins, such as recent work for stratifying Alzheimer’s disease subtypes, are still in early research phases.
Blood-based tests beyond DNA
The announcement, which was recently made at the 2026 American Society of Clinical Oncology (ASCO) annual meeting, reflects a growing shift within cancer diagnostics away from single-analyte approaches and toward integrated biological modeling. Over the past decade, liquid biopsy innovation has largely centered on circulating tumor DNA (ctDNA), driven by advances in next-generation sequencing and the promise of minimally invasive genomic profiling. However, ctDNA performance has varied substantially across tumor types and disease stages, particularly in malignancies characterized by low tumor shedding during early progression.
Jeter contends that ovarian cancer exemplifies these limitations. “Certain cancers shed ctDNA very effectively into circulation, and in those cases the technology performs very well,” Jeter said. “But in other cancers, either the shedding is insufficient for the sensitivity required at early stages, or the specificity profile becomes challenging. That has led to a broader realization across the field that a single biological layer cannot fully capture disease progression.”
Increasingly, oncology researchers are converging around multi-omic frameworks that integrate orthogonal biological signals, including proteomic, metabolic, genomic, and transcriptomic features. Within that context, lipid metabolism has emerged as an area of renewed interest.
Lipid signaling, long associated primarily with cardiovascular disease and metabolic disorders, now plays a deeply intertwined role in oncogenesis. Alterations in lipid metabolism contribute to membrane remodeling, inflammatory signaling, tumor proliferation, immune modulation, and metastatic adaptation. Tumors frequently undergo profound metabolic reprogramming early in disease development, creating detectable shifts in circulating lipid and metabolite profiles before conventional biomarkers become clinically informative.
“What we have learned is that lipid metabolism appears to be highly active in the earliest stages of disease,” Jeter said. “That biology has been described in the literature for some time. The challenge has been translating those discoveries into a clinical-grade diagnostic assay.”
That translation problem is nontrivial. Lipids present substantial analytical complexity due to structural diversity, isomeric overlap, and variability in sample handling and quantitation. Discovery-level lipidomics frequently produces promising signals that prove difficult to standardize under regulated clinical laboratory conditions. AOA Dx’s central claim is that it has successfully navigated that transition.
The company’s platform integrates targeted lipidomic and metabolomic profiling using high-resolution mass spectrometry with protein biomarker analysis via immunoassays. Machine-learning models are then applied to derive composite signatures associated with ovarian malignancy.
New clinical biomarker class
According to the company, the assay was developed through biomarker discovery efforts involving more than 2,200 patient samples across multiple cohorts and demographic populations.
Importantly, the ASCO dataset focused specifically on the intended-use population: symptomatic women presenting in routine clinical settings with nonspecific but concerning symptoms such as abdominal pain, bloating, urinary changes, or altered bowel habits.
That population reflects a longstanding clinical challenge in gynecologic oncology. Although the majority of ovarian cancer patients report symptoms beginning relatively early in disease progression, those symptoms are often diffuse and overlap extensively with benign gastrointestinal or genitourinary conditions. As a result, diagnostic delays remain common, with patients frequently cycling through multiple evaluations before referral to gynecologic oncology.
“About 85–95% of women begin experiencing symptoms as early as stage 1,” Jeter noted. “But the symptoms are nonspecific enough that providers often do not initially suspect ovarian cancer.”
As a result, nearly 80% of ovarian cancers are still diagnosed at advanced stages, despite the dramatic survival differential associated with early intervention. When detected at stage 1 or 2, five-year survival rates exceed 90%. Once metastatic dissemination occurs, however, outcomes deteriorate sharply.
The company’s results suggest that multi-omic integration may provide clinically meaningful improvements over historical CA-125 performance, particularly in early-stage disease where existing diagnostic sensitivity has remained inadequate. According to AOA Dx, AKRIVIS GD achieved nearly double the early-stage sensitivity historically associated with CA-125 alone.
The broader implication is not simply improved biomarker performance but a reframing of how cancer detection may evolve over the next decade. Rather than relying on single molecular features, next-generation diagnostics are increasingly attempting to model disease as a systems-level biological phenomenon.
“There’s a growing recognition that different biological pathways become informative at different stages of disease progression,” Jeter explained. “Some protein markers rise later. Some genomic signals are difficult to detect early. By integrating lipidomic, metabolomic, and proteomic information simultaneously, we’re able to observe the disease from multiple biological angles.”
The company describes this infrastructure as a broader discovery engine known as GlycoLocate, which is designed to interrogate thousands of lipid and metabolite signatures across multiple disease states. Ovarian cancer represents the company’s first targeted clinical application, but executives indicate the platform is already being expanded into additional oncology indications, particularly within women’s health.
The women’s health investment gap
AOA Dx’s emergence also reflects a broader maturation within women’s health biotechnology, a sector that historically struggled to attract sustained institutional investment despite its substantial market opportunity.
Jeter has spoken openly about what she views as a longstanding disconnect between investor perception and commercial reality in women’s health innovation. Earlier this year, she presented an investment analysis at the 2026 JP Morgan Healthcare Conference examining historical returns within the category.
“Women’s health has traditionally been viewed as a niche market, despite women representing more than half the population,” she said. “Part of the issue is that many successful companies serving women have not historically been classified as women’s health investments, so the return profile of the sector has been systematically underestimated.”
That dynamic may now be shifting as women’s health increasingly intersects with other high-growth sectors, including artificial intelligence, precision medicine, molecular diagnostics, and computational biology. AOA Dx itself sits squarely at that convergence point, combining AI-driven biomarker modeling with high-complexity laboratory diagnostics and oncology applications.
The company is now advancing AKRIVIS GD toward validation studies and an early-access launch program. Equally important will be demonstrating clinical utility and securing reimbursement pathways, both of which remain major barriers for emerging diagnostics platforms. “It’s one thing to develop a test,” Jeter said. “It’s another thing entirely to ensure that patients can actually access it through reimbursement and coverage.”
To support commercialization efforts, AOA Dx has expanded its leadership team with executives experienced in diagnostic platform deployment and LC-MS assay translation, including chief product officer, Chris Roberts, and senior director of biomarker and analytical development, Cory Bystrom, PhD.
Whether lipidomics ultimately becomes a foundational pillar of oncology diagnostics remains uncertain. However, the field appears to be entering a transitional period in which metabolic biology is moving from peripheral exploratory science toward regulated clinical application.
For AOA Dx, the ambition extends beyond ovarian cancer itself. The company sees lipid-based multi-omics as an entirely new diagnostic layer capable of complementing—and in some settings potentially surpassing—the limitations of genomics-only approaches. “What I often say,” Jeter reflected, “is that the situation feels very similar to where next-generation sequencing was 10 or 15 years ago.”
If the company’s early data continues to hold in larger validation cohorts, AOA Dx may not simply be introducing another ovarian cancer assay. It may help to define the next biological frontier of liquid biopsy diagnostics.
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