Technology Development Theme Areas

The IMAT Program is aimed at stimulating and accelerating the development, integration, maturation, and dissemination of the most novel and highly innovative technologies in support of cancer research, detection, and diagnosis. Since 1998, the IMAT Program has accelerated the development of various tools, platforms, and associated methods that have direct relevance to cancer research and, ultimately, to clinical oncological practice.

The IMAT program supports highly-innovative technology development research to address the following areas:

  1. Molecular & cellular analysis for cancer research and clinical care
  2. Cancer-relevant biospecimen science

Regardless of the theme area to which an applicant may apply, the following are general attributes applicable to all IMAT technologies:

  • The proposed technology application may be targeted for the needs of basic, translational, and/or clinical cancer research. All proposed applications, however, must offer the potential for substantial improvements over conventional approaches and/or add qualitatively new research capabilities not provided by current technologies (see Section IV.6, “Other Submission Requirements and Information”)
  • “Technologies” proposed for development may include hardware, tools, instrumentation, devices, and associated techniques and/or methods. Note, however, that several specific technology types and application categories are not eligible (see the “exclusion list” at the end of this section of the FOA).
  • Applications may be intended for molecular and cellular analyses in one or more various models, including: (a) subcellular systems; (b) cultured cells; (c) animal models (human cancers in situ); and/or (d) human biospecimens. Note, however, specific exceptions that are not eligible (see “exclusion list” at the end of this section of the FOA)
  • Generally desirable attributes of all proposed applications include: (a) multiplexing (multiple parallel sample processing and/or multiparametric parallel analyses); (b) improved high throughput capability; (c) cost reduction; and/or (d) improved sensitivity, specificity, and/or selectivity.