Itsunto offers a data integration platform that merges high‑dimensional genomic data with phenotypic, laboratory, and longitudinal clinical records into a single, auditable workflow. The system enforces provenance, version control, and role‑based access while providing interfaces and APIs that support tumor boards, clinical genetics teams, and translational research, and it can be extended with modular decision‑support components.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare providers and researchers must interpret fragmented genomic, molecular, and clinical datasets that reside in disparate systems, making it difficult to assemble a complete, traceable view of a patient’s condition and to base decisions on reliable evidence.
Solution
Itsunto delivers a data integration platform that consolidates high‑dimensional genomic information with phenotypic, laboratory, and longitudinal clinical records into a single, coherent workflow. The system enforces explicit provenance and versioning so every transformation, filter, or annotation is auditable. By anchoring the integration on genomics, the platform establishes a robust schema that can be extended to broader clinical domains. Integrated data are presented through interfaces that mirror multidisciplinary review processes, enabling clinicians and researchers to evaluate evidence, discuss uncertainties, and reach defensible conclusions. The platform also supports downstream decision‑support modules that surface relevant evidence while preserving clinician responsibility. Deployments are structured as focused, contract‑based collaborations that align the solution with the client’s data governance and compliance requirements.
Target Audience
Itsunto serves molecular tumor boards, clinical genetics teams, and translational research groups within health systems that require integrated, traceable genomic and clinical data for patient care and research.
Features
- Ontology‑driven data model that maps molecular variants to phenotypic and clinical attributes across heterogeneous sources.
- Automatic capture of data lineage and version control for every ingestion, transformation, and annotation step.
- Configurable pipelines for variant filtering, annotation, and contextual enrichment using up‑to‑date knowledge bases.
- User interface designed for tumor boards and translational research teams, displaying integrated evidence with drill‑down provenance.
- Export and interoperability layer supporting standard health‑IT protocols (e.g., FHIR) and secure API access.
- Role‑based access controls and audit logs to meet regulatory and institutional compliance.
- Modular decision‑support components that surface uncertainty metrics and evidence citations without automating final decisions.
- Deployment framework for contract‑based engagements, allowing customized data governance and integration scope.