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:
May. 27, 2025

Filed:

Feb. 14, 2020
Applicant:

Just-evotec Biologics, Inc., Seattle, WA (US);

Inventors:

Jeremy Martin Shaver, Lake Forest Park, WA (US);

Tileli Amimeur, Seattle, WA (US);

Randal Robert Ketchem, Shalimar, FL (US);

Michael W. Vandiver, Chesterfield, MO (US);

Brian W. Horman, Bellevue, WA (US);

Fernando Garcia Morales, Seattle, WA (US);

Assignee:

Just-Evotec Biologics, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
C12M 1/00 (2006.01); C07K 1/16 (2006.01); C12M 1/12 (2006.01); C12P 21/00 (2006.01);
U.S. Cl.
CPC ...
C12M 47/10 (2013.01); C07K 1/16 (2013.01); C12M 29/04 (2013.01); C12M 29/10 (2013.01); C12M 37/00 (2013.01); C12M 47/12 (2013.01); C12P 21/00 (2013.01);
Abstract

The concepts described herein are directed to implementations of production facilities that can produce molecules used to treat biological conditions, such as biotherapeutics. The biotherapeutics can include various molecules, such as proteins, enzymes, and antibodies. The production facilities can include a number of separate modular cleanrooms that comprise particular pieces of equipment to perform one or more aspects of the processes used to manufacture biotherapeutics. The modular cleanrooms are arranged such that material that is produced by the equipment of one modular cleanroom can be transferred to another modular cleanroom for additional processing. Additionally, systems and processes are described to generate models using machine learning techniques, where the models can be used to predict productivity and/or efficiency metrics for production lines of biotherapeutics. Further, models can be generated to control the operation of pieces of equipment included in the production lines.


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