公开(公告)号：US20220336042A1

公开(公告)日：2022-10-20

申请号：US17640771

申请日：2020-09-29

Applicant: Cytiva Sweden AB

Inventor： Tobias Soderman ,  Olof Karlsson ,  Magnus Raberg ,  Andreas Borgstrom

IPC: G16B15/00 ,  G16B40/20 ,  G01N21/552 ,  G01N21/27 ,  G06N3/08

Abstract: Disclosed is a method for classifying monitoring results from an analytical sensor system (20) arranged to monitor molecular interactions at a sensing surface, wherein detection curves representing progress of the molecular interactions with time are produced. The method comprises steps of: acquiring (100) a set of detection curves, fitting (101) a first mathemati- cal model to the set of detection curves; calculating (102) a set of features from the set of detection curves and fitted mathematical model; based on the calculated set of features, classifying (103) each detection curve into qual- ity classification group; and based on the classification determining which detection curves to use in kinetic analysis of the monitored molecular inter- actions.

公开(公告)号：US20220259532A1

公开(公告)日：2022-08-18

申请号：US17618352

申请日：2020-06-23

Applicant: Cytiva Sweden AB

Inventor： Magnus Raberg ,  Tobias Soderman ,  Andreas Borgstrom ,  Helena Ohrvik

IPC: C12M1/36 ,  G05B17/02

Abstract: The present invention relates to a computer implemented method performed by a controller (C) configured to control a bioprocess comprised in a bioreactor (BR), the method comprising obtaining (410) measurement results by performing spectroscopy of a bioprocessing fluid (FL) comprised in the bioreactor (BR), generating bioprocessing parameters using the measurement results, one or more bioprocessing target parameters and one or more trained models, and, controlling the bioprocess using the generated bioprocessing parameters. The method wherein the one or more trained models are neural networks, wherein the measurement results comprise a spectrum, wherein the spectrum is split to a number N parts used to calculate N average values, wherein the N average values and the corresponding values of bioprocessing parameters are used § as features in the neural network.