The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 25, 2020

Filed:

Mar. 18, 2011
Applicants:

Yuriy Alexandrov, Cardiff, GB;

Albert Francis Santos, Cardiff, GB;

Inventors:

Yuriy Alexandrov, Cardiff, GB;

Albert Francis Santos, Cardiff, GB;

Assignee:

GE Healthcare UK Limited, Little Chalfont, GB;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
C12M 1/36 (2006.01); C12M 3/00 (2006.01);
U.S. Cl.
CPC ...
C12M 41/48 (2013.01); C12M 21/08 (2013.01);
Abstract

In one aspect the present invention relates to a systemfor automated extraction of multi-cellular physiological parameters. The systemcomprises a morphogenesis modulefor growing a plurality of cells, a monitoring unitfor monitoring the plurality of cells, a controllerfor controlling the morphogenesis moduleand the monitoring unitto grow the plurality of cells and analyse the growth of the plurality of cells in order to determine the multi-cellular physiological parameters, the controller () further comprising a process modelling unit () for determining inter-cellular interactions in response to various process conditions. The multi-cellular physiological parameters may provide an optimised protocol for growing various tissue types. A further aspect of the present invention provides a methodfor automated extraction of multi-cellular physiological parameters. The methodcomprises growinga plurality of cells, monitoringthe plurality of cells, and analysingthe growth of the plurality of cells in order to determinethe multi-cellular physiological parameters, and adaptively modifying a process model to provide a learning algorithm for determining an optimised tissue growth protocol. The cells may, for example, include pluripotent stem cells, or derived differentiated cells.


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