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Technologies of Interest

The Diagnostic Biomarkers and Technologies Branch (DBTB)  of the Cancer Diagnosis Program (CDP) supports a range of initiatives along the pipeline of technology development, from initial research projects and proof of principle studies to technology validation and demonstration of potential research and clinical application. Supported studies may also adapt or modify existing or emerging technologies to achieve their aims.

The following technologies are of particular interest to the branch, as they have potential applications in the analysis of human tumor samples. If you have a potential project that involves one or more of these technologies, check out the current funding opportunities or reach out to a program official in DBTB whose interests align most closely with your project to discuss the most appropriate funding mechanism for your application.

Genomic Technologies

DNA-based technologies

  • Detection and analysis of mutation and gene rearrangement
  • Comparative genomic hybridization (CGH)
  • High throughput genomic/genetic analysis for detecting epigenetic modifications of DNA

RNA-based technologies

  • Analysis of gene expression such as cDNA and oligo microarrays
  • RNA interference (RNAi)
  • Analysis of alternative splicing of mRNAs

Other genomic technologies

  • Macromolecular sample preparation
  • Nucleic acid amplification, sequencing, separation, capture, labeling and imaging in vitro and in tissue specimens.
  • Technologies for detecting or characterizing circulating tumor cells (CTC), dormant cancer cells, and other rare cells
  • Single-cell genomics and transcriptomics technologies

Proteomic and Metabolomic Technologies

Technologies for the comprehensive and/or quantitative separation and analysis of proteins, small molecules, carbohydrates and lipids

  • 2Dgel/Mass spectrometry systems
  • Chromatography
  • Electrophoresis separation
  • Bead technologies

Additional technologies of interest

  • Technologies to identify affinity ligands using antibodies, protein-protein interactions, combinatorial chemistry, aptamers, or phage display
  • High throughput metabolomic and protein array technologies
  • Technologies for labeling and imaging proteins and small molecules in vitro and in tissue specimens

Bioinformatics and Artificial Intelligence

  • Informatics systems for collection and management of data from comprehensive molecular analysis technologies
  • Software and statistical methods for analysis of data from comprehensive molecular analysis technologies
  • Applications of AI and machine learning to enhance the analysis, interpretation, and integration of molecular data for improved diagnostics and decision-making
  • Development of Explainable, Interpretable, & Trustworthy AI models to identify and validate novel cancer biomarkers
  • Predictive modeling and decision-support systems for personalized cancer treatment

Devices

  • Micro-technology, nanotechnology or Micro-Electro-Mechanical Systems (MEMS), lab-on-a-chip, microfabrication, on-chip separation and detection, point-of-care technologies, microfluidics, signal amplification, and systems for comprehensive molecular analysis
  • Technologies for automated sample preparation and other automated, high-throughput systems.
  • Integration of technologies into detection, analysis, and/or diagnostic systems
  • Point-of-care technologies for use in remote locations and low resource settings
  • Implantable devices for real-time monitoring of treatment response and drug delivery systems
  • Advanced diagnostic devices integrating AI for improved accuracy and efficiency in clinical settings

Imaging and Spatial Analysis Technologies

Technologies to enhance in vitro visualization, characterization, and spatial mapping of tumors and their microenvironments

  • Miniaturized and portable imaging devices for point-of-care cancer diagnostics
  • Integration of imaging technologies with molecular analysis tools (e.g., combining imaging with mass spectrometry or proteomics)
  • Development of AI-driven algorithms to process imaging data for automated detection, segmentation, and characterization of tumor features
  • Tools for ultra-high-resolution mapping of tumor substructures
  • Multi-scale imaging systems integrating single-cell and tissue-level resolution
  • Development of microfabricated imaging sensors for high-throughput and high-sensitivity diagnostics
  • Modular imaging devices for customizable research applications
  • Systems that combine imaging with real-time data processing for clinical decision-making
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