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Technologies and Software to Support Integrative Cancer Biology Research



The goal of this Funding Opportunity Announcement (FOA) is to support the development as commercial products of software, computational/mathematical methods, and laboratory technologies that will facilitate, accelerate, and/or enhance integrative cancer biology research. This FOA encourages Small Business Innovation Research (SBIR) grant applications from small business concerns (SBCs) that address this goal.


Integrative cancer biology focuses on the analysis of cancer as a complex biological system, uniting experimental and computational approaches to understanding cancer by leveraging existing high-throughput data, generating specific quantitative supplemental data, and creating new software tools and computational methods necessary to construct and validate predictive in silico models of cancer processes. Central to the integrative cancer biology approach is the construction and validation of sophisticated predictive computational models of cancer processes. These models require the input and integration of large quantities of heterogeneous data ranging from molecular/cellular data to clinical information.

Large amounts of molecular data are generated through a variety of endeavors and the data handling software and computational modeling methods for utilizing these data sets are under development. However, significant gaps remain in our ability to effectively model and understand complex cancer processes. New and/or improved software tools, computational methods, and laboratory technologies are necessary to bridge these gaps and enhance ongoing integrative biology efforts. Software capable of integrating a wide range of disparate data sources and computational or mathematical methods and tools for connecting or merging models and creating bridges between models of different biological scale are needed for a better understanding of the processes underlying the initiation and development of cancer. In addition, technologies are needed to generate supporting data that enable these models to accurately represent the biology they model. Understanding and quantifying multi-component, interactive processes at the sub-cellular, cellular, tissue, and organ levels can be limiting. Quantitative methods and technologies to measure cell-cell interactions and properties of the tumor microenvironment are needed. This initiative will support the development of these enabling software packages, modeling methods, and technologies.

For the purposes of this FOA, the term technology encompasses methods and tools that enable integrative cancer biology research.

Specific Objectives

Applications submitted in response to this FOA must focus on developing commercial products (software and technologies) designed to facilitate integrative cancer biology research, including, but not limited to, challenges in data collection, quantitation, integration, and/or modeling in the following areas:

  • Integrating data from disparate sources to enable enhanced models of cancer processes;
  • Measuring and analyzing cell-cell and cell-matrix interactions that are critical to the functioning of the tumor microenvironment;
  • Measuring and quantifying cell proliferation and cell motility in relation to cancer pathology;
  • Enhancing user-interfaces to data environments and associated computational models;
  • Measuring, quantifying metabolic interactions, computing the flow of substrates, and/or assessing the intermediate metabolic products related to cancer biology and pathology;
  • Monitoring the functioning of supramolecular machines, such as the replisome, spliceosome, molecular motor assemblies in cell division and motility, and those related to DNA repair, as they are altered in cancer;
  • Enabling data and computational or mathematical model visualization;
  • Elucidating and quantifying signaling networks and the regulatory dynamics of cellular processes such as cell cycle and apoptosis, and responses to environmental stress, as they relate to cancer;
  • Monitoring, visualizing, and quantifying temporal processes such as cancer initiation and progression at the single cell level;
  • Quantifying transcriptional, translational, and/or epigenetic control systems involved in cancer processes;
  • Identifying, isolating, and maintaining tumor stem cells and cells capable of asymmetric division;
  • Monitoring interactions of stem cells or cells undergoing asymmetric division with cells in the stem cell niche;
  • Merging computational models that model the same or overlapping sets of data or similar cancer processes developed from different data sources; and
  • Enhancing/facilitating access to existing computational models.

Note: This FOA is not intended to support the development of products (technologies or software) for data mining, drug discovery, correlative science, and/or discovery science not specifically designed to support an integrative biology approach.

Consideration should be given to the commercial potential of software and technology products chosen for development in applications submitted under this FOA.

Small business applicants interested in the development of technologies and software to support integrative cancer biology are encouraged to consider a concurrent initiative entitled Technology Development for the Detection and Evaluation of Chemical and Biological Carcinogens (SBIR [R43/R44] (PA-09-187).

Small business applicants interested in the development of innovative technologies for assaying carcinogenesis-relevant molecules are encouraged to consider a related initiative entitled Technology for the Detection and Characterization of Low Abundance Proteins, Peptides, or micro RNAs (SBIR) [R43/R44] (PA-09-189).

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