PREDICTION OF DISTRIBUTION OF GLYCANS ATTACHED TO MOLECULES MANUFACTURED IN A CELL CULTURE
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 fo...
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creator | WALVEKAR, Aditya Avdhut RUMMEL, Nicholas MEIER, Steven J ZHOU, Georo L NARAYANAN, Arthi LI, Zheng |
description | 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.
Un système, un procédé et un support lisible par ordinateur non transitoire pour prédire une distribution de glycane d'un ou de plusieurs glycanes fixés à des molécules pendant un processus de fabrication de biomolécules sont divulgués. Dans divers modes de réalisation, au moins trois paramètres de processus de fabrication associés au procédé de fabrication des molécules sont entrés dans un modèle graphique probabiliste qui est entraîné pour prédire la distribution de glycane. Le modèle graphique probabiliste entraîné peut ensuite analyser les au moins trois paramètres de processus de fabrication pour prédire la distribution des glycanes qui sont fixés aux molécules. |
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Un système, un procédé et un support lisible par ordinateur non transitoire pour prédire une distribution de glycane d'un ou de plusieurs glycanes fixés à des molécules pendant un processus de fabrication de biomolécules sont divulgués. Dans divers modes de réalisation, au moins trois paramètres de processus de fabrication associés au procédé de fabrication des molécules sont entrés dans un modèle graphique probabiliste qui est entraîné pour prédire la distribution de glycane. Le modèle graphique probabiliste entraîné peut ensuite analyser les au moins trois paramètres de processus de fabrication pour prédire la distribution des glycanes qui sont fixés aux molécules.</description><language>eng ; fre</language><subject>APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY ; BEER ; BIOCHEMISTRY ; CALCULATING ; CHEMISTRY ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ENZYMOLOGY ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; METALLURGY ; MICROBIOLOGY ; MUTATION OR GENETIC ENGINEERING ; PHYSICS ; SPIRITS ; VINEGAR ; WINE</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240314&DB=EPODOC&CC=WO&NR=2024055009A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,778,883,25547,76298</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240314&DB=EPODOC&CC=WO&NR=2024055009A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WALVEKAR, Aditya Avdhut</creatorcontrib><creatorcontrib>RUMMEL, Nicholas</creatorcontrib><creatorcontrib>MEIER, Steven J</creatorcontrib><creatorcontrib>ZHOU, Georo L</creatorcontrib><creatorcontrib>NARAYANAN, Arthi</creatorcontrib><creatorcontrib>LI, Zheng</creatorcontrib><title>PREDICTION OF DISTRIBUTION OF GLYCANS ATTACHED TO MOLECULES MANUFACTURED IN A CELL CULTURE</title><description>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.
Un système, un procédé et un support lisible par ordinateur non transitoire pour prédire une distribution de glycane d'un ou de plusieurs glycanes fixés à des molécules pendant un processus de fabrication de biomolécules sont divulgués. Dans divers modes de réalisation, au moins trois paramètres de processus de fabrication associés au procédé de fabrication des molécules sont entrés dans un modèle graphique probabiliste qui est entraîné pour prédire la distribution de glycane. Le modèle graphique probabiliste entraîné peut ensuite analyser les au moins trois paramètres de processus de fabrication pour prédire la distribution des glycanes qui sont fixés aux molécules.</description><subject>APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY</subject><subject>BEER</subject><subject>BIOCHEMISTRY</subject><subject>CALCULATING</subject><subject>CHEMISTRY</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ENZYMOLOGY</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>METALLURGY</subject><subject>MICROBIOLOGY</subject><subject>MUTATION OR GENETIC ENGINEERING</subject><subject>PHYSICS</subject><subject>SPIRITS</subject><subject>VINEGAR</subject><subject>WINE</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZIgKCHJ18XQO8fT3U_B3U3DxDA4J8nQKhfHdfSKdHf2CFRxDQhydPVxdFEL8FXz9fVydQ31cgxV8Hf1C3RydQ0KBZih4-ik4Kji7-vgoACVBQjwMrGmJOcWpvFCam0HZzTXE2UM3tSA_PrW4IDE5NS-1JD7c38jAyMTA1NTAwNLR0Jg4VQAYBjKY</recordid><startdate>20240314</startdate><enddate>20240314</enddate><creator>WALVEKAR, Aditya Avdhut</creator><creator>RUMMEL, Nicholas</creator><creator>MEIER, Steven J</creator><creator>ZHOU, Georo L</creator><creator>NARAYANAN, Arthi</creator><creator>LI, Zheng</creator><scope>EVB</scope></search><sort><creationdate>20240314</creationdate><title>PREDICTION OF DISTRIBUTION OF GLYCANS ATTACHED TO MOLECULES MANUFACTURED IN A CELL CULTURE</title><author>WALVEKAR, Aditya Avdhut ; RUMMEL, Nicholas ; MEIER, Steven J ; ZHOU, Georo L ; NARAYANAN, Arthi ; LI, Zheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_WO2024055009A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre</language><creationdate>2024</creationdate><topic>APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY</topic><topic>BEER</topic><topic>BIOCHEMISTRY</topic><topic>CALCULATING</topic><topic>CHEMISTRY</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ENZYMOLOGY</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>METALLURGY</topic><topic>MICROBIOLOGY</topic><topic>MUTATION OR GENETIC ENGINEERING</topic><topic>PHYSICS</topic><topic>SPIRITS</topic><topic>VINEGAR</topic><topic>WINE</topic><toplevel>online_resources</toplevel><creatorcontrib>WALVEKAR, Aditya Avdhut</creatorcontrib><creatorcontrib>RUMMEL, Nicholas</creatorcontrib><creatorcontrib>MEIER, Steven J</creatorcontrib><creatorcontrib>ZHOU, Georo L</creatorcontrib><creatorcontrib>NARAYANAN, Arthi</creatorcontrib><creatorcontrib>LI, Zheng</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WALVEKAR, Aditya Avdhut</au><au>RUMMEL, Nicholas</au><au>MEIER, Steven J</au><au>ZHOU, Georo L</au><au>NARAYANAN, Arthi</au><au>LI, Zheng</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>PREDICTION OF DISTRIBUTION OF GLYCANS ATTACHED TO MOLECULES MANUFACTURED IN A CELL CULTURE</title><date>2024-03-14</date><risdate>2024</risdate><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.
Un système, un procédé et un support lisible par ordinateur non transitoire pour prédire une distribution de glycane d'un ou de plusieurs glycanes fixés à des molécules pendant un processus de fabrication de biomolécules sont divulgués. Dans divers modes de réalisation, au moins trois paramètres de processus de fabrication associés au procédé de fabrication des molécules sont entrés dans un modèle graphique probabiliste qui est entraîné pour prédire la distribution de glycane. Le modèle graphique probabiliste entraîné peut ensuite analyser les au moins trois paramètres de processus de fabrication pour prédire la distribution des glycanes qui sont fixés aux molécules.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY BEER BIOCHEMISTRY CALCULATING CHEMISTRY COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ENZYMOLOGY INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS METALLURGY MICROBIOLOGY MUTATION OR GENETIC ENGINEERING PHYSICS SPIRITS VINEGAR WINE |
title | PREDICTION OF DISTRIBUTION OF GLYCANS ATTACHED TO MOLECULES MANUFACTURED IN A CELL CULTURE |
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