Platforms and systems for automated cell culture
Inventors
Wagner, Matthias • Aivio, Suvi • AMENDUNI, Mariangela • PILSMAKER, Catherine • Pereira, Arnaldo • ZUTSHI, Ananya • TOURE, Anthia • Nagle, Steven • Whiting, Ozge • Harb, George • Sullivan, Matthew • BERLIN-UDI, Maya • Morgan, Stefanie • SEAY, Nick • Lee, Sang • LURO, Scott
Assignees
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Publication Number
US-12195765-B2
Publication Date
2025-01-14
Expiration Date
Abstract
Disclosed herein are platforms, systems, and methods including a cell culture system that includes a cell culture container comprising a cell culture, the cell culture receiving input cells, a cell imaging subsystem configured to acquire images of the cell culture, a computing subsystem configured to perform a cell culture process on the cell culture according to the images acquired by the cell imaging subsystem, and a cell editing subsystem configured to edit the cell culture to produce output cell products according to the cell culture process.
Core Innovation
The invention relates to producing an induced pluripotent stem cell (iPSC) product by culturing a plurality of iPSC candidate cells in a closed cell culture container such that a plurality of iPSC candidate cell colonies emerge. Time-series image data of the plurality of iPSC candidate cell colonies is acquired using an image sensor and processed by a computer processor using one or more trained machine learning models to predict clonal quality of the plurality of iPSC candidate cell colonies.
Based on the predicted clonal quality, at least one iPSC candidate cell colony is selected for expansion. A cell editing subsystem manages the plurality of iPSC candidate cell colonies based at least in part on the acquired time-series image data, including performing selective removal of at least a portion of an iPSC candidate cell colony based at least in part on whether the iPSC candidate cell colony will collide with another iPSC candidate cell colony.
Non-selected iPSC candidate cell colonies are removed from the closed cell culture container, and the selected at least one iPSC candidate cell colony is expanded into the iPSC product. The platform integrates automated label-free imaging, computational prediction, and image-guided, spatially precise editing while operating in a closed configuration.
Claims Coverage
The independent claims cover a closed-loop workflow for iPSC product generation comprising closed culturing, time-series imaging, trained machine learning prediction of clonal quality, collision-based selective removal and colony management by a cell editing subsystem, and selection and expansion of selected colonies with removal of non-selected colonies. Across the independent claims, five inventive features are recited.
Closed culturing in a closed cell culture container with iPSC colony emergence
Culturing a plurality of iPSC candidate cells in a closed cell culture container wherein a plurality of iPSC candidate cell colonies emerge from the plurality of iPSC candidate cells.
Time-series image acquisition for iPSC candidate cell colonies
Acquiring, using an image sensor, time-series image data of the plurality of iPSC candidate cell colonies.
Machine learning prediction of clonal quality from time-series images
Processing, by a computer processor, the acquired time-series image data using one or more trained machine learning models to predict clonal quality of the plurality of iPSC candidate cell colonies.
Collision-based selective removal and colony management by a cell editing subsystem
Managing, by a cell editing subsystem, the plurality of iPSC candidate cell colonies based at least in part on the acquired time-series image data, wherein managing the plurality of iPSC candidate cell colonies comprises performing selective removal of at least a portion of an iPSC candidate cell colony based at least in part on whether the iPSC candidate cell colony will collide with another iPSC candidate cell colony.
Selection for expansion and removal of non-selected colonies
Selecting at least one of the plurality of iPSC candidate cell colonies for expansion based at least in part on the predicted clonal quality; removing the non-selected iPSC candidate cell colonies from the closed cell culture container; and expanding the selected at least one iPSC candidate cell colony into the iPSC product.
Together, the independent claims require a closed cell culture container producing iPSC candidate colonies, time-series imaging, trained machine learning prediction of clonal quality, collision-based selective removal by a cell editing subsystem, and selection of one or more colonies for expansion into an iPSC product while removing non-selected colonies.
Stated Advantages
Enables producing an iPSC product by selecting colonies based on predicted clonal quality.
Uses selective removal based on whether colonies will collide, which supports managing colonies prior to expansion.
Provides a system architecture that combines closed culturing, time-series imaging, machine-learning prediction, and a cell editing subsystem for colony management and non-selected removal.
Documented Applications
Producing an induced pluripotent stem cell (iPSC) product from iPSC candidate cells using a closed cell culture container with time-series imaging, machine-learning-based clonal quality prediction, and selective removal of non-selected colonies.
Producing a clonal or monoclonal iPSC product by selecting at least one iPSC candidate cell colony as a clonal colony, as described in dependent claim refinements summarized in the provided content.
Managing and removing iPSC candidate cell colonies using collision-based selective removal criteria while expanding selected colonies into the iPSC product.
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