Personalized oncology
Two AI-powered pipelines - genomic analysis and personalized vaccines. For rare cancer patients with no trials, and common cancer patients who've exhausted standard of care while waiting on trial enrollment or FDA approval. Both paths end in a single patient IND - a trial of one.
From genomic sequencing to actionable treatment recommendations across all Rx categories.
Tissue sequencing and biomarker profiling
Compare against standard of care and ongoing therapies
Personalized Rx scoring
On-label, off-label, clinical trials, or a single patient IND
Neoantigen-driven peptide and mRNA vaccines manufactured for the individual tumor profile.
Tumor and germline sequencing
Epitope selection via computational immunology
Peptide or mRNA synthesis at CDMO partner
Navigate gatekeeper access and administer
No clinical trials exist. Not enough patients (N) to ever run one. Pharma won't invest. These patients have zero evidence-based options and no path forward in the current system.
Long tail - hundreds of cancer types ignoredRecurrence after completing standard of care. The oncologist says "we've tried everything." Now they're waiting - for a trial slot, for FDA approval, for something. Ontrove fills that gap.
Moderna, BioNTech trials exist - but slots are limitedAfter genomic data and tissue are collected, the diagnosis context determines the primary pathway - but either is available on a patient-by-patient basis.
Has time for the vaccine manufacturing window. Routes primarily to the personalized vaccine pipeline.
Needs immediate options. Routes primarily to AI-powered analysis and targeted therapy.
Either path is available based on patient context - not a hard rule.
Every patient enters the same way. What splits them is time - whether there's a manufacturing window to spend, or a recurrence that needs an answer now.
How much time does this patient have?
CDMO partner
Gatekeeper access
R1On-labelR2Off-labelR3Clinical trialsR4Single patient INDn = 1R4 and V5 arrive at the same population - the one standard of care and trial infrastructure were never built to reach. A conventional trial needs a cohort. A single patient IND needs a patient.
LT1Rare cancers - no trials, no big N
LT2Common cancers - SOC exhausted, waiting
Aligned incentives. The patient initiates. The doctor orders. No SOC hospital sales layer in between.
Tempus, Caris, Foundation Medicine sell to hospitals, not to patients. Evidence goes to SOC systems. Many analyses never reach the people who need them.
Every pipeline except final therapeutics is scalable. The AI model handles analytical heavy lifting that would otherwise require a team of oncologists.