grant

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

Organization CELLCHORUS INC.Location Houston, UNITED STATESPosted 8 Aug 2024Deadline 31 Jul 2027
NIHUS FederalResearch GrantFY2025AI model trainingAI trainingAcuteAntibodiesApoptosisApoptosis PathwayArtificial intelligence model trainingAssayBehaviorBioassayBiological AssayCell BodyCell CommunicationCell Culture TechniquesCell DeathCell InteractionCell LocomotionCell MigrationCell MovementCell ShapeCell SurvivalCell ViabilityCell divisionCell-to-Cell InteractionCellsCellular MigrationCellular MotilityCellular immunotherapyCessation of lifeClassificationClonal ExpansionCo-cultureCocultivationCocultureCoculture TechniquesComputational ScienceComputer Vision SystemsComputer softwareComputersConvNetData SetDeathDetectionDevelopmentEffector CellElementsEventFailureFluorescenceFrequenciesGoalsHourImageImage AnalysesImage AnalysisImmuneImmune mediated therapyImmunesImmunologically Directed TherapyImmunotherapyLabelLaboratoriesLocationLysosomesM PhaseMeasurementMemoryMethodsMitochondriaMitosisMitosis StageMitoticModelingMotilityMovementNetwork-basedNuclearOrganellesPatternPeer ReviewPerformancePhasePhase-Contrast MicroscopyPhototoxicityProgrammed Cell DeathProteinsPublicationsReporterRetrievalRoboticsScientific PublicationSoftwareSpeedSystemSystematicsTechniquesTechnologyTestingTimeTrainingTumor CellUpdateValidationVariantVariationVideo RecordingVideorecordingVisualVisualizationWorkanalysis pipelineartificial intelligence trainingbody movementcell culturecell culturescell imagingcell killingcell motilitycell typecell-based immunotherapycellular imagingcluster computingcomputer visionconvolutional networkconvolutional neural netsconvolutional neural networkcopingdata griddata pipelinedata to traindatagriddataset to traindeep learning based neural networkdeep learning neural networkdeep neural netdeep neural networkdevelopmentaldistributed computingexperimentexperimental researchexperimental studyexperimentsfield based datafield learningfield studyfield testfluorescence imagingfluorescent imaginghuman-in-the-loopimage evaluationimage interpretationimagingimmune cell therapyimmune therapeutic approachimmune therapeutic interventionsimmune therapeutic regimensimmune therapeutic strategyimmune therapyimmune-based therapiesimmune-based treatmentsimmuno therapyin vitro Assayinstrumentationinterestmicroscope imagingmicroscopic imagingmicroscopy imagingmitochondrialnanonano litrenanoliternanolitrenecrocytosisneoplastic cellneural networknovelprematureprematurityprototyperestorationsingle cell analysissoftware systemsspatial and temporalspatial temporalspatiotemporalsuccesstask analysistooltraining datatranscriptome profilingtranscriptomic profilingusabilityvalidationsvideo recording system
Sign up free to applyApply link · pipeline · email alerts
— or —

Get email alerts for similar roles

Weekly digest · no password needed · unsubscribe any time

Full Description

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.

Grant Number: 4R42TR005299-02
NIH Institute/Center: NIH

Principal Investigator: Rebecca Berdeaux

Sign up free to get the apply link, save to pipeline, and set email alerts.

Sign up free →

Agency Plan

7-day free trial

Unlock procurement & grants

Upgrade to access active tenders from World Bank, UNDP, ADB and more — with email alerts and pipeline tracking.

$29.99 / month

  • 🔔Email alerts for new matching tenders
  • 🗂️Track tenders in your pipeline
  • 💰Filter by contract value
  • 📥Export results to CSV
  • 📌Save searches with one click
Start 7-day free trial →