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公开(公告)号:US20230304488A1
公开(公告)日:2023-09-28
申请号:US18018669
申请日:2021-07-28
Applicant: Genentech, Inc. , Hoffmann-la Roche Inc.
Inventor: Thomas Eisele , Pasquale CATALDO , Scott WIESER , Warren Dana AWEAU , Ruel G. GATDULA , Nicholas RUMMEL , Arthi NARAYANAN , Dennis FRANKMANN , Orhan CELIK , Mirko MARINGER , Murat COSKUN , Stephen Christopher SLONE , Henzel DALMACIO , Dominik MARKS , Edward CHAN , Dustin Daniel Scott , Michael Asal
IPC: F04B43/08
CPC classification number: F04B43/08
Abstract: Provided herein is a tube rolling apparatus. The apparatus includes a first arm, a first roller rotatable around a first axis, a second arm, a second roller rotatable around a second axis, and optionally an advancing unit coupled to the first roller and configured to rotate the first roller around the first axis. Related systems and methods are also provided.
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公开(公告)号:US20240293829A1
公开(公告)日:2024-09-05
申请号:US18431838
申请日:2024-02-02
Applicant: Genentech, Inc.
Inventor: Nicholas RUMMEL , Patrick Daniel AHYOW
Abstract: Provided herein are systems, devices and methods for harvesting biological cells with a centrifuge. A biological cell harvesting centrifuge apparatus may be provided with a rectangularly shaped base and 21 laterally spaced apart upright supports. Each upright support may extend vertically upward from the base and have a hollow core. Each upright support may be configured to slidably receive and support either one, two or four vertical edges of either one, two or four 15 mL micro bioreactor vessels. The 21 upright supports may be arranged in a 3×7 array such that they form a 2×6 array of receptacles configured to slidably receive and support 12 of the bioreactor vessels. The upright supports may be configured to support at least 80% of the vertical edges of the bioreactor vessels.
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公开(公告)号:US20240084240A1
公开(公告)日:2024-03-14
申请号:US18464131
申请日:2023-09-08
Applicant: GENENTECH, INC.
Inventor: Arthi NARAYANAN , Aditya Avdhut WALVEKAR , Georo L. ZHOU , Nicholas RUMMEL , Zheng LI , Steven J. MEIER
Abstract: A method, system, and non-transitory computer readable medium for predicting cell viability of a cell culture in a bioreactor during a biomolecule manufacturing process are disclosed. In various embodiments, at least three manufacturing process parameters related to the process for manufacturing molecules are input into a machine learning model that is trained to predict cell viabilities. The trained machine learning model may then analyze the at least three manufacturing process parameters to generate an indicator of cell viability of the cell culture.
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公开(公告)号:US20240302395A1
公开(公告)日:2024-09-12
申请号:US18410827
申请日:2024-01-11
Applicant: Genentech, Inc.
Inventor: Nicholas RUMMEL , James DVORNICKY
CPC classification number: G01N35/026 , G01N35/1011 , G01N35/1067 , G01N2035/0418 , G01N2035/0436
Abstract: Provided herein are systems, devices and methods for retaining chromatographic minicolumns in a holding fixture. A retaining apparatus may be provided with a pair of laterally spaced apart upright supports and a horizontal beam spanning between the upright supports to hold them in the laterally spaced apart relationship. The apparatus may be configured to contact a holder plate only along peripheral edges of the holder plate. The apparatus may be configured to slide along the holder plate after the minicolumns have been inserted therein, thereby retaining the minicolumns in the holder plate but allowing access to the minicolumns through vertical holes in the horizontal beam.
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公开(公告)号:US20240084241A1
公开(公告)日:2024-03-14
申请号:US18464135
申请日:2023-09-08
Applicant: GENENTECH, INC.
Inventor: Arthi NARAYANAN , Aditya Avdhut WALVEKAR , Georo L. ZHOU , Nicholas RUMMEL , Zheng LI , Steven J. MEIER
Abstract: A method, system, and non-transitory computer readable medium for predicting a glycan distribution of one or more glycans attached to molecules during a biomolecules manufacturing process are disclosed. In various embodiments, at least three manufacturing process parameters related to the process for manufacturing the molecules are input into a probabilistic graphical model that is trained to predict glycan distribution. The trained probabilistic graphical model may then analyze the at least three manufacturing process parameters to predict the distribution of the glycans that are attached to the molecules.
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