SBIR/STTR Research Award

LF-TIMING: Large-scale label-free profiling of cell-cell interactions

Award identifier 1fbf8095ff8b86cb7a81f7b887b033557d92bc5e07d8ac3c4f2597cd549ca0d4Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,128,853

Program and phase

STTR · Phase II

Award year

2025

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
CELLCHORUS INC
Proposal award date
2025-08-01
Contract end date
2027-07-31
UEI
LUF6ANBGK7F4
Solicitation number
PA23-232
Topic code
100

Research abstract

7. Project Summary/Abstract There is a compelling need for technologies that can quantitatively profile cell-cell interactions on a large scale, especially the interactions of immune cells with tumor cells and quantify detailed measurements of crucial events including cell-cell contact patterns, contact frequencies, contact durations, cell death, interaction-related movement patterns especially pursuit, avoidance, arrest, movement failures, and target cell killing behaviors, cell division, and others. The TIMING™ (Time-lapse Imaging Microscopy In Nanowell Grids) assay is a powerful and versatile high-throughput in vitro assay that meets this need. In its current form, TIMING assay analysis software relies on multi-channel fluorescent imaging to identify cell type and location. This imposes an inherent limitation, as even the best available high-throughput time-lapse imaging instrumentation has 4 – 5 fluorescent channels of which 2 – 3 channels must be devoted to labeling effector and target cells, leaving only 1 – 2 channels for the customer to incorporate antibodies or probes of investigational interest. There is a compelling need to free up fluorescence channels so the customer can incorporate 3 – 4 investigational probes concurrently. This will greatly enhance the value of the TIMING assay for the customer by allowing them to study the localization and dynamics of multiple investigational probes concurrently in their spatiotemporal context. Achieving this goal requires computer vision methods capable of accurately and reliably analyzing label-free phase-contrast video recordings to detect, segment, and classify cells, track their movements, detect key events like cell death and mitosis, and profile cell-cell interactions while coping with focus loss. This will not only free up multiple fluorescent channels but also reduce the phototoxicity, enabling cell co-cultures to be imaged over longer durations and at higher frame rates. Finally, there is a need for the video array analysis to be completed while the cells are still live (~ 2 hours maximum), to identify crucial cells of interest (e.g., exceptionally motile serial killers) for robotic retrieval and downstream processing, including clonal expansion and transcriptomic profiling. The goal of this project is to develop LF-TIMING (Label Free TIMING), an integrated computer vision system that meets the above-mentioned needs, leveraging advances in deep neural network-based cell segmentation, tracking, classification, and focus restoration methods.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

8 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $5,813,959. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Health and Human Services

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