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HHS SBIR PA-13-140


The NIH Common Fund is a framework to enhance cooperative activities among the NIH Office of the Director and all the NIH Institutes and Centers (for further information, see This Funding Opportunity Announcement (FOA) is released in affiliation with the NIH Common Fund, however, the participating Institutes and Centers (ICs) are participating independently and funding decisions will be made within each participating IC, not by the NIH Common Fund.  As a result, relevance to the mission of the participating ICs is important and will impact funding decisions.

This FOA encourages Small Business Innovation Research (SBIR) grant applications from small business concerns (SBCs) that focus on the development of tools or techniques, that have commercial potential. Although applications will not be restricted to a particular type of technology, NIH is especially interested in applications to develop next-generation tools that distinguish heterogeneous states among cells in situ. Applications should define the current state of technology as a benchmark against which the new tool(s) will be measured and should propose proof-of-concept testing of the tool(s) in a complex biological tissue or living organism. The new tools to be developed in the application should provide substantially increased sensitivity, selectivity, spatiotemporal resolution, scalability or non-destructive analysis of multiple global or functional measures of single cells. These novel technologies will aid in obtaining a fine-grained, integrative and dynamic view of heterogeneous cellular states/classes and will provide innovative platforms to transform research into the cellular basis of diseases.


This initiative is affiliated with the Single Cell Analysis Program (SCAP) through the NIH Common Fund (See, which supports cross-cutting programs that are expected to have exceptionally high impact.

Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells, it is possible to resolve rare cells, transient cell states, and understand the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate the move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized.

The SCAP focuses on supporting work which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. To robustly and systematically describe cell level heterogeneity, projects are expected to take a multiplexed approach with minimal perturbation, which can be applied reproducibly to any complex tissue. Technologies and methods must also be capable of capturing spatiotemporal information to understand the organization, evolution and response of cell states as part of a functional population. In addition, the SCAP emphasizes the application of these technologies to in situ populations of cells from multicellular organisms to link cell state measurements with complex, functional tissues which can inform our understanding of disease processes.  Here, NIH seeks input from the small business community to provide highly innovative tools that will assist with these goals.   Commercialization of these technologies will make them broadly available to the scientific community and accelerate progress in this important emerging field of single call analysis. 


This FOA encourages applications to develop next-generation, innovative technologies to better define cell heterogeneity in situ. These techniques should provide new analytical measures and manipulations of cellular contents, structure and activity significantly beyond those currently available at the single cell level. Of particular interest are first-in-class and/or cross-cutting techniques. The goal of this FOA is to accelerate development of promising concepts by focusing on overcoming technical challenges, building prototype systems and testing performance on a population of cells in situ (e.g., explant, whole organism), and further advancing the development of these technologies toward commercialization. This FOA seeks to support innovative projects that will result in robust tools and approaches widely adoptable and usable by the research community through the marketplace. Toward this end, applications that draw upon diverse expertise from both within and outside (e.g., engineering, physics, chemistry) of biology are of particular interest. To the extent that it is useful in combining different types of expertise, applications with multiple principal investigators are encouraged (See

Applications can propose high-risk/high-impact technologies; examples can include, but are not limited to:

Devices to perform novel global (i.e., "-omic") and/or functional analyses of a wide variety of cell types in situ without destruction or prior perturbation of cells.

Combinations of tools for multiplex analysis and/or manipulation of single cells in situ to maximize data content over many parameters (e.g., gene expression, electrochemical dynamics, signal secretion/reception/transduction, cell adhesive properties, cytoarchitectonic or migratory changes).

Tools that provide significant advances in sensitivity, selectivity or spatiotemporal resolution of molecules/structures/activities within single cells and between ostensibly similar cells in situ.

Automated and scalable assays for high-throughput analysis of single cells in situ, including scalability of measured parameters in parallel, cell numbers and/or speed of processing.

Systems-level single cell dataset analysis or modeling, including computational approaches, in the context of tissues or whole organisms.

Research designs should focus on tool development, but tools should be designed within the context of the types of studies to ultimately be performed in heterogeneous biological systems, such as:

Identification of spatiotemporal transitions in cellular states (e.g., progenitor lineage determination, cellular aging)

Detection of rare cells in a population (e.g., stem cells, tumor-initiating or metastatic cells, drug resistant cells)

Elucidation of the molecular signatures or functional consequences of stochastic variation in cellular states (e.g., genomic stability, clonal selection and evolution, asymmetric division, cell specification)

Characterization of heterogeneous cell responses to environmental changes (e.g., homeostatic perturbation, modulation of niche/microenvironment, morphogens or cell-to-cell signaling, toxicological exposure, experience-dependent plasticity, host cell responses to infectious, immunological or allergic challenges).

Any proposed biological assay(s) should be chosen strictly for utility (rather than biological novelty) in proof-of-concept testing of the innovative technique.

All applications must explicitly address considerations detailed in Section IV.2 – Application and Submission Information.

It is important to emphasize that the topics listed above are only meant to be illustrative, and not meant to be a comprehensive list of appropriate topics, nor exclusive of other appropriate topics. Applications may propose projects that are highly innovative or that are enhancements of current approaches. In either case, studies must significantly advance the current state of the art of single cell analysis and have commercial potential.  Submitted applications must be aligned with the research priorities of at least one of the participating ICs. Potential applicants are strongly encouraged to contact Scientific/Research Contact(s) before submitting an application. 

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