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

IPC: C12M1/36 ,  G06N3/08

CPC classification number: C12M41/48 ,  G06N3/08

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.

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.

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

IPC: C12M1/36 ,  G16B40/20

CPC classification number: C12M41/48 ,  G16B40/20

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.