WO2022248935 - MACHINE LEARNING-BASED QUALITY CONTROL OF A CULTURE FOR BIOPRODUCTION
National phase entry:
Publication Number
WO/2022/248935
Publication Date
01.12.2022
International Application No.
PCT/IB2022/000291
International Filing Date
27.05.2022
Title **
[English]
MACHINE LEARNING-BASED QUALITY CONTROL OF A CULTURE FOR BIOPRODUCTION
[French]
CONTRÔLE QUALITÉ BASÉ SUR APPRENTISSAGE AUTOMATIQUE D'UNE CULTURE POUR BIOPRODUCTION
Applicants **
LYNCEUS SAS
Inventors
MONTONE, Guglielmo
LIMAL, Severin
Priority Data
17/826,682
27.05.2022
US
63/193,675
27.05.2021
US
Application details
| Total Number of Claims/PCT | * |
| Number of Independent Claims | * |
| Number of Priorities | * |
| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
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International Searching Authority |
EPO
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| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| * | |
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| Translation |
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* The data is based on automatic recognition. Please verify and amend if necessary.
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2165 | |
| EPO | Filing, Examination, Granting | 9703 | |
| Japan | Filing, Examination, Granting | 2264 | |
| South Korea | Filing, Examination, Granting | 2276 | |
| USA | Filing, Examination, Granting | 4740 |
Total:
21,148
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
Real-time quality control of a culture for bioproduction is facilitated using machine learning. In this approach, real-time process data for a set of parameters for a current production run is received. Based on this process data, a prediction is made using an instance of a machine learning model that has been trained on process data from past production or development runs. The instance is uniquely associated to a particular culture day and thus independent of any other instance of the machine learning model (for other culture days). Based on the prediction, a quality control recommendation for the current production run is then made. Several different types of predictions are enabled, and various different recommendations are provided based on the predictions.[French]
Un contrôle qualité en temps réel d'une culture pour bioproduction est facilitée par apprentissage automatique. Dans cette approche, des données de processus en temps réel pour un ensemble de paramètres pour un cycle de production actuel sont reçues. Sur la base de ces données de processus, une prédiction est effectuée à l'aide d'une instance d'un modèle d'apprentissage automatique qui a été entraîné sur des données de processus issues de cycles de production ou de développement antérieurs. L'instance est associée de manière unique à un jour de culture particulier et donc indépendante de toute autre instance du modèle d'apprentissage automatique (pour d'autres jours de culture). Sur la base de la prédiction, une recommandation de contrôle qualité pour le cycle de production actuel est ensuite effectuée. Plusieurs types différents de prédictions sont activés, et diverses recommandations différentes sont fournies sur la base des prédictions.