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AssigneeInsitro, Inc.
InventorsHervé MARIE-NELLY, Jeevaa VELAYUTHAM, Zachary PHILLIPS, Shengjiang TU
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The present disclosure relates generally to an autonomous cell imaging and modeling platform, and more specifically to machine-learning techniques for using microscopy imaging data to continuously study live biological cells. The autonomous cell imaging and modeling platform can be applied to evaluate various cellular processes, such as cellular differentiation, optimization of cell culture (e.g., in-plate cytometry), disease modeling, histopathology imaging, and genetic and chemical screening, using a dynamic universal imaging system. In some embodiments, the platform comprises a set of label-free computational imaging techniques, self-supervised learning models, and robotic devices configured in an autonomous imaging system to study positional and morphological characteristics in particular cellular substructures of a cell culture in an efficient and non-destructive manner over time.
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A system for identifying one or more cell culture conditions for progressing one or more live biological cells towards a desired cell state, the system comprising:
A non-transitory computer-readable storage medium storing one or more programs for identifying one or more cell culture conditions for progressing one or more live biological cells towards a desired cell state, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device having a display, cause the electronic device to perform operations comprising:
A method for identifying one or more cell culture conditions for progressing one or more live biological cells towards a desired cell state, comprising:
Dependencies are inferred from the claim text.