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1. US20220208297 - PREDICTING CELL CULTURE PERFORMANCE IN BIOREACTORS

Office
United States of America
Application Number 17599656
Application Date 27.03.2020
Publication Number 20220208297
Publication Date 30.06.2022
Publication Kind A1
IPC
G16B 5/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
5ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G16B 35/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
35ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
G06T 7/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
7Image analysis
C12M 1/36
CCHEMISTRY; METALLURGY
12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
MAPPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY
1Apparatus for enzymology or microbiology
36including condition or time responsive control, e.g. automatically controlled fermentors
CPC
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G16B 5/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
5ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 35/00
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
35ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
G06T 2207/30024
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
30Subject of image; Context of image processing
30004Biomedical image processing
30024Cell structures in vitro; Tissue sections in vitro
C12M 41/48
CCHEMISTRY; METALLURGY
12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
MAPPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
41Means for regulation, monitoring, measurement or control, e.g. flow regulation
48Automatic or computerized control
G06T 2207/10004
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
2207Indexing scheme for image analysis or image enhancement
10Image acquisition modality
10004Still image; Photographic image
Applicants AMGEN INC.
Inventors William Leigh Johnson
Martin Rodrigo Carcamo Behrens
Title
(EN) PREDICTING CELL CULTURE PERFORMANCE IN BIOREACTORS
Abstract
(EN)

A computational method of modeling a bioreactor combines mechanistic models of kinetics of metabolic fluxes and flux balance analysis to predict cell culture performance. The mechanistic models include effects of process variables descriptive of extracellular environment, e.g., temperature, acidity, osmolarity, and/or metabolite concentrations. The method constrains flux rates based on the mechanistic models and computes the flux rates in view of suitable metabolic objectives. The method simulates time evolution of process variables of the bioreactor based on user input and computes performance metrics to display to the user, to control a bioreactor, and/or to train an artificial intelligence model of a bioreactor.


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