Longitudinal intelligence
Baseline, change and personal trajectory.
The miRoncol intelligence platform
Not one test. One platform built to expand.
miRoncol connects biological samples, broad and focused measurement, AI-assisted pattern recognition and longitudinal data. The same intelligence engine is designed to support carefully validated applications across multiple chronic disease domains.
The platform thesis is not that every signal becomes a test. It is that one governed measurement and intelligence foundation can support many carefully validated questions.
Platform architecture
One engine · six extensions
SHARED CORE
microRNA intelligence
AI · DATA · MODELS
Multi-disease research
Four major chronic disease domains.
Biological samples
Blood today. Saliva and urine research.
miCheckup oncology
Early cancer detection built on published research.
Laboratory pathways
Accredited, quality-controlled delivery.
NGS + targeted PCR
Broad discovery and focused assays.
Not one test. A connected platform.
One intelligence engine. Built to expand across samples, diseases and time.
The platform connects biological inputs, laboratory measurement, computational interpretation, personal history and focused applications. Each layer has a different job. Together they create an intelligence infrastructure designed to expand responsibly.
Biological samples
Blood is the current foundation. Saliva, urine and other sample types may be investigated where application-specific science supports them.
Broad and focused measurement
NGS preserves a wide view of the measured microRNA panel. Targeted PCR provides efficient measurement when a defined signature has been supported.
microRNA intelligence engine
AI-assisted models evaluate relationships across multiple signals, quality controls and biological context rather than relying on one isolated marker.
Healthspan Intelligence Profile
A measurement captures the present. Continuing measurement can establish a personal baseline, reveal sustained change and show trajectory around an intervention.
Validated applications
Supported signatures may move into disease-specific assays, clinical research pathways and focused tests. miCheckup oncology is the first application.
DELIVERY FOUNDATIONThe platform operates inside a governed laboratory and clinical pathway.
Accredited laboratory pathwaysQuality-controlled measurement and reproducible workflows.
Governance + clinical contextConsent, data quality, intended use and responsible interpretation.
Broad platform does not mean broad claims. Every disease area, sample type, analytical model and intended use requires its own evidence and validation.
How platform value deepens
The intelligence grows in three directions.
This is the strategic difference between a single-purpose test and a platform: the same core capabilities can generate deeper context, broader research utility and additional focused applications.
A measurement becomes a history.
Repeated profiles can establish an individual range, reveal sustained change and place an intervention or treatment on a meaningful timeline.
BASELINE → CHANGE → INTERVENTION → RESPONSEPreserved data supports new questions.
As scientific understanding and analytical models develop, appropriately governed earlier profiles may be revisited to investigate newly relevant patterns.
MEASURE ONCE → ANALYZE RESPONSIBLY → REVISITOne core can support focused tests.
Shared measurement, quality and analytical infrastructure can inform distinct applications. Each one advances only with its own evidence.
SHARED CORE → VALIDATED SIGNATURE → FOCUSED ASSAYA widening analytical lens
Capture with today’s tools. Return with tomorrow’s questions.
Comprehensive measurement preserves optionality. The value is not predicting every future discovery. It is retaining a sufficiently broad record so relevant earlier patterns are not automatically lost.
The data can stay the same while the analytical field of view improves.
This is why broad NGS measurement can be valuable in research and longitudinal programs: a narrow assay answers a defined question, while a broad profile preserves room for questions that have not yet been resolved.
Capture a broad microRNA profile
Establish a measured record using the scientific and technical standards available today.
Research identifies a new pattern
A pathway, signature or analytical relationship becomes more scientifically relevant.
Ask when that pattern emerged
Where consent, data quality and comparability permit, earlier profiles can be examined with the updated question.
Translate only after validation
A supported signature may inform a defined, application-specific assay rather than remain a broad research signal.
The ability to revisit historical profiles depends on consent, data retention, measurement quality, batch comparability, analytical validity and the requirements of the particular research or clinical application.
Longitudinal intelligence
The record changes what a future measurement can mean.
A current result can still be informative without a baseline. But starting while healthy adds something population comparison cannot provide: the person’s own prior state.
Healthspan Intelligence Profile
A conceptual measurement history showing how baseline, change and intervention gain meaning as a connected sequence.
Healthy baseline
Capture a broad profile before symptoms appear.
Personal range
Confirm which patterns appear stable for this individual.
Sustained change
A repeated upstream pattern moves beyond the established range.
Intervention
Treatment or another intervention now has temporal context.
Inflection
The upstream pattern changes direction after the event.
Follow-up
Later measures investigate whether downstream biology follows.
Flexible measurement strategy
NGS preserves the field. PCR concentrates the view.
The two technologies serve different roles. NGS supports broad discovery and longitudinal optionality; targeted PCR supports efficient measurement of an established signature.
Broad measurementNGS
Preserve possibilities.
Use next-generation sequencing when the question benefits from a wide microRNA field of view.
- Captures a broad measured panel
- Supports discovery and longitudinal research
- Allows appropriate reanalysis as research develops
- Requires greater analytical and cost infrastructure
Focused measurementPCR
Provide focus.
Use targeted PCR when a defined set of microRNAs has been supported for a specific application.
- Measures a selected signature
- Supports focused monitoring or testing
- Can offer a more scalable and lower-cost path
- Requires application-specific assay validation
These are complementary, not competing, methods. The platform can use broad NGS measurement to learn and preserve optionality, then develop focused PCR assays where the evidence supports a narrower application.
Shared core, distinct applications
One intelligence foundation. Four major chronic disease domains.
The platform connects research across oncology, cardiovascular, neurodegenerative and metabolic disease. The evidence remains application-specific. Oncology is the published foundation and first focused application. The other domains remain research directions.
Shared intelligence core
MicroRNA measurement, data quality, AI-assisted pattern analysis and longitudinal context.
Oncology
The first peer-reviewed publication of a miRNA-based multi-cancer early detection model, translated into the miCheckup Early Cancer Detection Test.
See miCheckupCardiovascular
Regulatory patterns connected to vascular biology, cardiac stress and inflammation.
Neurodegenerative
Patterns under investigation in neurological decline and neuroinflammatory biology.
Metabolic
Regulatory pathways connected to insulin response, energy balance and metabolic dysfunction.
Research directions are not presented as validated products. Each domain requires its own cohorts, analytical validation, clinical evidence and intended-use pathway.
Platform discipline
A data platform must earn trust.
Technical possibility is only part of the platform. Responsible progress also requires governed data use, transparent evidence and application-specific validation.
Consent and defined use
Collect and use biological data within clear research, clinical and participant permissions.
Quality before quantity
Preserved data is valuable only when sample handling, measurement quality and analytical comparability are sufficient.
Evidence before assertion
Separate exploratory patterns from validated signatures and validated signatures from approved clinical uses.
Clinical context remains human
Computational intelligence should support responsible medical interpretation, not replace physician-led diagnosis and care.
Explore the foundation
The platform creates the field of view. The science determines what it can support.
Go deeper into microRNA biology and published evidence, or see miRoncol’s first focused application.