INFOTECH SOFT, INC. — Department of Health and Human Services SBIR Phase I: NCI
INFOTECH SOFT, INC. — SBIR Phase I award from Department of Health and Human Services.
Phase I SBIR feasibility signal
- Phase I awards fund proof-of-concept work. For capture teams, they mark early interest from Department of Health and Human Services in a technical approach.
- Watch for Phase II follow-ons from the same firm/topic family — that conversion path is where budgets and transition pressure rise.
- Obligated amount $223,808. Cross-check similar awards in the same agency and technology tags for going-rate context.
- Topic code NCI links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $223,808
- Agency
- Department of Health and Human Services · National Institutes of Health
- Program / Phase
- SBIR · Phase I
- Topic
- NCI
- NAICS
- —
- Place of performance
- FL
- Period
- —
Description
Cancer studies increasingly include medical imaging and measurements from multiple omics techniques The main impetus for data integration is that through these integrated data sets an improved understanding of the underlying biology is obtained to be better able to predict a phenotype and to gain further insight into mechanistic aspects of the system at the molecular level In this project we propose to develop innovative technologies to integrate metabolite data with multi omic metabolomics proteomics and transcriptomics and cancer imaging data to enable the detection of subtler and more complex associations among variables with the medical imaging and the metabolome providing phenotypic measurements to which we can anchor the global measurements of the transcriptome and proteome The proposed Multi omics and Imaging Data Analysis System MIDAS will provide for the ingestion annotation quality control and analysis of in vivo imaging data combined with ex vivo omics data to advance research in cancer MIDAS is aimed at helping the cancer and overall public health research communities advance faster towards the larger goal of precision medicine through valid and reliable data harmonization of metabolomics transcriptomics proteomics radiomics and other imaging data