A research lab For One.
Built around your biology, your options, and you. And what comes next.
Why we started
Because special cases deserve more than averages.
We started Omanta to give complex patients the depth, continuity, and scientific attention their unique case demands.
The Omanta process
A full PhD-level scientific research team for every case.
-
Your case team
PhD scientists are selected for the biology and questions unique to your case.
-
Every piece of evidence
We collect and organize your records, imaging, pathology, molecular data, and the research that already exists.
-
Close the diagnostic gaps
We identify what is missing and work with your clinical team to coordinate additional diagnostic testing.
-
Biology into direction
We connect your disease biology to the strongest evidence and define the most promising next steps.
-
Science into care
We work alongside your physicians so the research can inform real clinical decisions.
From complex biology to clear direction.
Omanta goes beyond routine clinical diagnostics, using cutting-edge molecular technologies to build a detailed molecular profile of the disease.
Illustrative interface · no patient data
Data overview
Whole exome
RNA sequencing
(TPM)
Copy number
variation
Tumor mutational
burden
01 · DNA · Nucleus
Read the genome.
We examine genomic variation that may help explain the biology of the disease.
- Whole-genome sequencing
- Whole-exome sequencing
- Copy-number variation
- Tumor mutational burden
Illustrative capabilities; test selection is case-specific.
02 · RNA · Cytoplasm
See what the tumor is expressing.
RNA analysis shows which programs are active, in which cells, and where they appear within tissue.
- Bulk RNA sequencing
- Short-read RNA sequencing
- Long-read RNA sequencing
- Single-cell RNA sequencing
- Spatial transcriptomics
Illustrative capabilities; test selection is case-specific.
03 · Protein · Cell surface and tissue
Map the functional protein landscape.
Protein-level analysis adds spatial and functional context to what the genome and transcriptome suggest.
- Immunohistochemistry (IHC)
- Multiplex immunofluorescence
- Spatial proteomics
- Mass-spectrometry proteomics
Illustrative capabilities; test selection is case-specific.
Case-to-cohort analysis
One case, understood in population context.
We cross-reference the patient’s molecular profile against Omanta’s internal dataset to understand how each signal compares with the broader population.
Advanced bioinformatics connects those patterns with biomedical research and relevant clinical trials so the findings can be interpreted in context.
Illustrative comparison against a 5,000-sample reference cohort. No patient data is shown.
Population expression
Patient-to-population comparison
Reference cohort · n=5,000
Selected signals
Molecular feature positions
- EGFR
- ERBB2
- STK11
- PD-L1
Interpretation context
Three connected evidence layers
-
Internal reference dataset Population comparison
-
Biomedical research Mechanistic interpretation
-
Clinical trials Potential relevance
Therapeutic evidence modeling
Assess potential benefit and risk together.
Omanta cross-references the patient’s genomics with its structured evidence dataset to evaluate how each therapeutic strategy may fit the biology and support a modeled view of potential response.
Published efficacy, safety, and side-effect evidence is organized point by point to surface potential risks, monitoring considerations, and uncertainty for the clinical team.
Illustrative research interpretation. Not a prediction of response or a treatment recommendation.
Therapeutic evidence view
Patient-specific strategy assessment
Illustrative model · no patient data
Potential efficacy context
Genomic alignment × evidence depth
Safety evidence profile
Side-effect signal landscape
Patient genomics
Molecular alignment Case-specific alterations, pathways, and biological contextInternal evidence dataset
Point-level literature Efficacy, safety, adverse effects, and reported uncertaintyIntegrated assessment
Potential and risk in context A structured scientific view for discussion with the clinical teamLiving therapeutic roadmap
Plan for what is next, before it is needed.
The roadmap sequences lower-risk, lower-burden options and more intensive contingencies across the patient journey, from no evidence of disease to aggressive disease.
Each horizon is informed by the prior risk and benefit assessment, then revisited as the biology, evidence, feasibility, and patient goals change.
Illustrative planning framework only. Relative risk depends on the therapy, patient, clinical setting, and timing. The clinical team directs care.
Therapeutic planning over time
One roadmap. Multiple future states.
Illustrative strategy · no patient data
Near term
Ready now Monitor, preserve options, and define triggersMedium term
Prepared contingencies Early molecular change and local progressionLong term
Emerging and individualized Options for aggressive disease- Clinical surveillance
- Preserve future research options
- Confirm biological change
- Reassess lower-burden strategies
- Local-control strategies
- Combination contingencies
- Systemic and investigational paths
- N-of-1 development when appropriate
Biology
Disease state and molecular change The roadmap responds when the case changesEvidence
New data, literature, and trials Emerging knowledge can reorder future optionsPracticality
Feasibility, goals, and care context Scientific possibilities are assessed with the clinical teamExplore the full analysis
One scientific advocate. Start to finish.
Someone is there to answer questions, surface the questions no one has asked yet, and translate complexity without losing the science.
Think: a research counsel for your case.
Your clinical team
Brings deep knowledge of your care and history.
Shared decisions
Together, we align on evidence and the best path forward.
Your Omanta research team
Brings deep expertise in your disease biology and the science.