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Replicating Human Tissue Complexity for High Throughput Testing


TECHNOLOGY AREA(S): Bio Medical, Chem Bio Defense

OBJECTIVE: This SBIR would enhance detection of pathogens from complex samples by developing a high-throughput, low-cost, physiologically realistic model system that demonstrates human tissue hierarchy and cellular heterogeneity and, critically, is compatible with high-speed microfluidics.


Warfighters are travelers, continually exposed to new environments and new pathogens. These new pathogens are increasingly likely to emerge and spread due to changes in the environment, rising global population, and the ready availability of global travel. This necessitates new and improved high-throughput tools that can identify new threats, reveal how they are pathogenic, and screen potential treatments.

Current model systems that can examine the interactions between host and pathogen are limited either by the time required to return an answer or by the level of complexity inherent in the system. For instance, while tissue culture cells have a relatively low cost and a high speed turn-around, they do not replicate host complexity. Animal models clearly demonstrate physiologically relevant responses to a pathogen, but also require significant time, money, and often extensive adaptation or modification to recapitulate human disease, further increasing costs and delay. Recent efforts using organized and differentiated human cells to represent a human, such as organoids and organ-on-a-chip technologies, show promise in bridging these gaps. Yet, to be useful in detecting novel pathogens, they still require much greater throughput and significantly lower costs. DARPA seeks technologies that eliminate the bottleneck in determining the pathogenicity of unknown bacteria by achieving the complexity of an in vivo model while matching the speed and throughput of microfluidics based assays.

To ensure relevance to pathogen detection, the technology should:

  • Be based on human cells and tissues
  • Preserve cellular diversity and hierarchy
  • Demonstrate differential responses to pathogens similar to in vivo models, producing more information than tissue culture cells.

Of particular interest would be a system that captures the genetic diversity of a population, in contrast to the constrained diversity of immortalized cell lines. Additionally, technology developed through this SBIR should be high-throughput, capable of testing at least 1,000 pathogen/host interactions in a day, have the capability to replicate tissue-level responses, and be miniaturized for high-throughput platform assays. The technology should be available “on demand” by reconstitution from frozen stocks of cells. Lastly, technology should be transferrable to new users and adaptable to the high throughput technologies associated with pathogen and drug screening


Phase I should develop technology that replicates the host's response to at least two pathogenic and two non-pathogenic organisms. System complexity should exceed that of tissue culture and represent pathogenicity comparable to in vivo models. Lastly, proposers must identify concepts and methods to scale-up for high-throughput testing, and provide a plan for practical deployment of the proposed technology.


  • Month 1: Report comparing the developing technology to both a relevant tissue culture cell model and actual or reported human and in vivo model phenotypes using ≥3 tissue relevant bacterial pathogenic species.
  • Month 3: Report of studies to identify and define differential markers of host susceptibility consistent with establishing performance goals.
  • Month 4: Demonstrate and report a prototype assay that can differentiate pathogenic from non-pathogenic bacteria with quantification of the error rate, signal, and noise.
  • Month 5: Interim report comparing response to pathogen between cells before and after freeze-thaw.
  • Month 6: Final Phase I report summarizing approach; comparison of how technology's response replicates host complexity significantly as compared to tissue culture cells; comparison with other state-of-the-art methodology; quantification of accuracy; quantification of robustness to errors, noise and model or assessment of the limits required to meet performance goals.


Phase II will focus on advancing the technology's performance—increasing the breadth of host/pathogen markers, demonstrating rapid technology deployment upon receipt, and scaling the technology for commercialization. The result of this SBIR will be a prototype that could be readily tested for high-throughput analysis and for ease of operation by a separate lab. Proposers should demonstrate commercial merit and feasibility of the technology to be disseminated to downstream users.

The ultimate system must demonstrate the capability to identify host responses to pathogens with a testing throughput of at least 1,000 pathogens/day. Additionally, the technology must demonstrate the capacity to be rapidly brought online from either frozen or other preservation methods to processing at least 5,000 pathogens in a week.

Phase II option year would involve work with academic or commercial partners to demonstrate the technology.


  • Month 2: New Capabilities Report, that identifies additions and modifications that will be researched, developed, and customized for incorporation in the pilot demonstration.
  • Month 4: Interim decision report on marker technology describing relative strengths and weaknesses of selected reporters, and results of tests demonstrating their capacity to meet the throughput goals.
  • Month 12: Demonstrate and deliver a report for a prototype system that can identify at least 3 host/pathogen responses relevant to niche finding, immune system evasion, or the degradation of membranes and that is compatible with high-throughput sample processing and decision making for at least 3 pathogens relevant to the target tissue.
  • Month 15: Report describing the examination of additional tissue types for technology expansion including examination of cellular diversity and hierarchy and comparison of the ability to differentiate pathogen vs. non pathogen.
  • Month 18: Report on demonstration of the technology with models of at least 3 more relevant tissue types derived from at least 3 more genetically distinct tissues.
  • Month 24: Demonstrate and deliver a report for a prototype system that can identify at least 10 responses of the host cells to a pathogen. The approach should becompatible with high-throughput sample processing, should demonstrate a range of responses, and should stem from interactions with at least 3 pathogens relevant to the target tissue.

Phase II OptionPhase II option year would focus on improving performance by working with academic or commercial partners to increase the number of tissues that can be deployed, and the speed with which they can by employed. The technology should also be refined and scaled for commercialization.

  • Month 30: Report on successful demonstration of the technology by a team without prior experience with the technology. A successful demonstration would identify a biological interaction revealed by the multicellular construct that is not seen in individual cells or in cultures of immortalized cells.
  • Month 36: Report on successful demonstration of the technology by a team without prior experience with the technology. A successful demonstration would identify at least 3 different biological interactions revealed by the multicellular construct that is not seen in individual cells or in cultures of immortalized cells. The test must be performed on the prototype device using components delivered and stored in a manner consistent with future commercialization, such as being thawed from stock that had been frozen and shipped.

PHASE III: Potential customers include government agencies with interests in high-throughput pathogen detection as well as other government and non-government partners working in areas from basic research to clinical applications. Technology developed may be transitioned directly as tools or advanced therapies, or licensed as intellectual property to speed development of advanced therapies by others.

KEYWORDS: High-throughput; Pathogen-detection; Tissue complexity; Cellular hierarchy; Alternative in vivo models


[1] Simian, M., and Bissell, M. Organoids: A historical perspective of thinking in three dimensions. Journal of Cell Biology. (2017) 216(1): 31-40. DOI:10.1083/jcb.201610056

[2] Fatehullah, A., Tan, H.S., and Barker, N. Organoids as an in vitro model of human development and disease. Nature Cell Biology. (2016) 18(3): 246-254. DOI:10.1038/ncb3312

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