Abstract: A device assembly for controlling an integrated continuous pharmaceutical or biopharmaceutical manufacturing process including a first process equipment for performing a first process step; a second process equipment for performing a second process step subsequent to the first process step; a single measuring unit for measurement of a set of signals of a liquid process medium at a single location, the measured signals depending on first and second parameters; and an evaluation and control unit for evaluating the measured signals to determine values of the first and second parameters. The evaluation and control unit determines first and second corrective feedback based on the values of the first and second parameters, respectively. The evaluation and control unit controls the first process step by providing the first corrective feedback to the first process equipment and controls the second process step by providing the second corrective feedback to the second process equipment.

Abstract: Various embodiments relate to a digital control unit of a bioprocess arrangement for controlling a bioprocess, wherein the digital control unit comprises a local data storage and a local processor unit, wherein the digital control unit comprises a bioprocess interface for sending and receiving bioprocess control data, wherein the digital control unit is configured to execute a bioprocess control routine via the local processor unit to control the bioprocess, wherein in the bioprocess control routine, the digital control unit generates bioprocess data from the actuator data and/or the sensor data and/or the user control command data. It is proposed that the digital control unit is configured to execute a signing routine via the local processor unit and that in the signing routine, the digital control unit digitally signs documentation data, derived from the bioprocess data, by generating a digital signature.

Abstract: A method for conducting a bioprocess with a digital control unit of a bioprocess arrangement, wherein the digital control unit comprises a local data storage and a local processor unit, wherein bioprocess data are generated by the digital control unit. It is proposed, that in a data safety routine, a documentation routine and a signing routine are executed, that in the documentation routine, documentation data are generated from the bioprocess data and that in the signing routine, a cryptographic private key is extracted from private key data and the documentation data are digitally signed with the cryptographic private key by generating a digital signature and that the documentation routine is executed continuously during the bioprocess and that the signing routine is executed discontinuously during the bioprocess in several signing cycles according to a signing strategy, which defines trigger events for initiating the signing routine.

Abstract: A method for conducting a bioprocess with a digital control unit of a bioprocess arrangement, wherein the digital control unit comprises a local data storage and a local processor unit, wherein the digital control unit comprises a bioprocess interface for sending and receiving bioprocess control data, wherein bioprocess data are generated by the digital control unit, wherein a bioprocess control routine is executed by the local processor unit to control the bioprocess, wherein in the bioprocess control routine, the bioprocess data are generated by the digital control unit from actuator data and/or sensor data and/or user control command data. It is proposed that a signing routine is initiated by the local processor unit in the data safety routine to be executed by an external signing unit(s).

Abstract: A computer implemented method for detecting foam on the surface of a liquid medium contained in a vessel is described. The method including the steps of receiving a sample image of at least a portion of the vessel comprising the liquid-gas interface and classifying the sample image between a first class and at least one second class, associated with different amounts of foam on the surface of the liquid. The classifying is performed by a deep neural network classifier that has been trained using a plurality of training images of at least a portion of a vessel comprising a liquid-gas interface. The plurality of training images may comprise at least some images that differ from each other by one or more of: the location of the liquid-gas interface on the image, the polar and/or azimuthal angle at which the liquid-gas interface is viewed on the image, and the light intensity or colour temperature of the one or more light sources that illuminated the imaged portion of the vessel when the image was acquired.