bioAffinity Technologies vs Freenome
If your failure mode is treating these as competing early detection tests, start by noticing they screen different cancers. bioAffinity's CyPath Lung analyzes a sputum sample to help a physician decide about a small indeterminate lung nodule; Freenome's SimpleScreen CRC is a blood test for average risk colorectal screening. A clinician rarely chooses between them, so the sharper comparison is regulatory posture and evidence. Freenome sits at the higher bar: a Premarket Approval application under FDA review with a decision anticipated in 2026, a pivotal study published in JAMA, and inclusion in the American Cancer Society's updated colorectal guideline. bioAffinity is a laboratory developed test through its own CLIA lab with strong reported accuracy but company published evidence and no disclosed FDA pathway. One is a regulated screening play; the other is a lab offered decision aid.
- The right tool for the specific question CyPath Lung answers: a physician assessing a high risk patient with a small indeterminate pulmonary nodule under 20 millimeters, where reported performance is 92 percent sensitivity and a 99 percent negative predictive value.
- Available now as a laboratory developed test through the company's own CLIA lab, reimbursed by Medicare and private carriers, without waiting on a premarket decision.
- Honestly scoped as an aid alongside other clinical findings rather than a sole diagnostic or a population screen, which is the correct framing for a nodule workup.
- The stronger regulatory and evidence position: a Premarket Approval application under FDA review with a 2026 decision anticipated, a pivotal PREEMPT CRC study published in JAMA, and independent inclusion in the American Cancer Society colorectal screening guideline.
- A blood draw for average risk colorectal screening, a far larger and better defined population than a nodule decision aid, with 85 percent reported sensitivity for colorectal cancer at 90 percent specificity.
- Unusually candid scope: the company states plainly that no single technology detects every cancer, the right posture for a category prone to overclaiming.
Side-by-Side
| Axis | B bioAffinity Technologies |
F Freenome |
|---|---|---|
| AI Centrality | ||
| Autonomy and Oversight Model | — | — |
| Model and Technology Transparency | — | — |
| Clinical and Operational Evidence | ||
| AI Safety and PHI Stewardship | — | — |
| HIPAA and BAA Posture | — | — |
| Security Certifications and Trust Center | — | — |
| FDA and Regulatory Status | ||
| AI Governance and Bias Disclosure | — | — |
| EHR and Interoperability Depth | — | — |
| Deployment Model and Data Residency | — | — |
| Commercial Transparency | ||
| Setting and Specialty Coverage |
These screen different cancers by different sample types, so the comparison is about regulatory route and evidence, not head to head accuracy. Freenome's evidence is peer reviewed and independently recognized, but its PMA is still under review and not approved, and under an exclusive license Exact Sciences holds US commercial rights, so a buyer's counterparty may not be Freenome. bioAffinity's accuracy figures come from a trial whose cohort size is not stated in retrieved materials and are supported largely by company case studies and conference posters, with no active FDA pathway disclosed. Both are wet lab assays with a machine learning classifier layered over sample chemistry, graded B on AI centrality for the same reason as GRAIL: the chemistry is as load bearing as the model.