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NIH Commits $3M to Fund Human BioMolecular Atlas Program

NEW YORK (GenomeWeb) — The National Institutes of Health announced today that it has earmarked $3 million in fiscal 2019 to fund a series of projects developing new technologies for its Human BioMolecular Atlas Program (HuBMAP).

Unveiled in September, the HuBMAP program is an open, global framework supporting efforts to build a map of cells within the adult human body. The NIH previously committed an initial $54 million to a handful of institutes that will act as centers for technology development; tissue mapping; and data integration, visualization, and engagement.

The newly available funding comes as part of HuBMAP's so-called rapid technology integration (RTI) initiative and will fund groups that will focus on enhancing, validating, and integrating emerging new technologies for inclusion in the consortium.

"The vision for the RTI projects is that they will nimbly integrate new technologies into the HuBMAP so that the consortium can proactively adapt to the changing landscape and accelerate realization of its goals," the NIH said. "All technologies are expected to significantly enhance understanding of the spatial distribution of a large number of biomolecules in the intra-, inter-, and extra-cellular spaces of non-diseased human tissues."

While these technologies do not need to be completely novel, the NIH said they are expected to add significant value and be successfully implemented within three years. They should also have established proof of principle for technical feasibility using mammalian tissue and be validated in a lab setting, the agency added.

Examples of technologies appropriate for this funding opportunity include, but are not limited to, tools for rapid, high-resolution, in situ sequencing and analysis of a wide panel of nucleic acids derived from multiple tissues; assays for identification of different functional states of biomolecules, including post-transcriptional modification, post-translational modification, and proteoforms; and data visualization methods for atlas comparison and analysis.

The NIH expects to fund four to eight awards under the funding opportunity. Additional details can be found here.