Method and system for determining anomalies in a bioprocess

Abstract

A computer implemented method for determining anomalies in a bioprocess in real-time, the method comprising: collecting, in real-time, process data for a current bioprocess, providing reference data relating to a reference bioprocess, the reference data corresponding to the process data; communicating to a user, in real-time, deviation and / or conformity between the current bioprocess and the reference bio process based on the process data and the reference data.

Description

[0001] METHOD AND SYSTEM FOR DETERMINING ANOMALIES IN A BIOPROCESS

[0002] TECHNICAL FIELD

[0003] The present invention relates to a method and a system for determining anomalies in a bioprocess in real-time. In a specific example, the bioprocess is a liquid chromatography process and the method allows a user to visually determine when the process deviates from what is expected.

[0004] BACKGROUND ART

[0005] Bioprocessing systems are widely used, e.g. to perform biomolecule / protein separation. An example of a bioprocessing system is a chromatography system. Chromatography is a well-known procedure for purifying protein samples. The sample may typically be provided in a fluid, e.g. deriving from a bioreactor. Other bioprocessing systems include filtration systems and bioreactors.

[0006] A bioprocessing system / device is generally used to provide a particular system functionality, e.g., the bioprocessing system / device may be used to produce and / or separate a desired substance, e.g., protein purification in a bioprocess such as chromatography or filtration or production through cell cultivation or oligo synthesis.

[0007] For many applications of such bioprocessing systems, it is necessary to repeat the same bioprocess in multiple runs, e.g. in series using the same system / device. However, for many different reasons, anomalies may occur within any given run, which result in differences in the bioprocess run-to-run. In many cases, the output of anomalous runs is unusable. Therefore, anomalous runs waste both time and resources. In many case, anomalous runs are identified only after they are completed, e.g. when the quality of the output is being checked.

[0008] Thus, there is a need for an improved method to identify anomalies as they occur, or soon as possible after they occur, in order to minimise waste. An objective of embodiments of the invention is to provide a solution which mitigates or solves the drawbacks or problems described above

[0009] SUMMARY OF THE INVENTION

[0010] According to an aspect of the disclosure there is provided a computer implemented method for determining anomalies in a bioprocess in real-time, the method comprising: collecting, in real-time, process data for a current bioprocess, providing reference data relating to a reference bioprocess, the reference data corresponding to the process data; communicating to a user, in real-time, deviation and / or conformity between the current bioprocess and the reference bio process based on the process data and the reference data. Accordingly, anomalies in a bioprocess can be identified in real-time, by the user of a bioprocess.

[0011] Optionally, the bioprocess is one of: a chromatography process, a bioreactor process, a filtration process and an oligo-synthesis process.

[0012] Optionally, the process data comprises one or more of: data derived from sensor parameter data, the sensor parameter data relating to measurements by one or more sensors of a bioprocess apparatus, operation mode data relating to one or more operation modes of one or more mechanical components of the bioprocess apparatus, and event data relating to the occurrence of one or more process events. Optionally, the process data further comprises sensor parameter data.

[0013] Optionally, when the bioprocess is chromatography, the sensor parameter data comprises data from one or more of: a pH sensor, a conductivity sensor, a UV sensor, a pressure sensor, a flow-rate sensor and a temperature sensor. Optionally, when the sensor is a UV sensor, data derived from the sensor parameter data comprises one or more of peak area (area under peak) derived from UV sensor data, retention time (Rt), peak height, peak width, peak asymmetry factor, peak resolution (Rs), retention factor (k’), selectivity (a), theoretical plate number (N), and height equivalence to a theoretical plate (HETP). Optionally, the operation mode data comprises data relating to one or more of: a valve unit, a splitter, an inlet valve, an outlet valve, and a pump.

[0014] Optionally, the event data comprises data relating to one or more of: the occurrence of a parameter reaching a threshold, the occurrence of one or more process steps and / or corresponding instructions to the bioprocess apparatus.

[0015] Optionally, the process data has a temporal relationship to the current bioprocess, and the temporal relationship between the process data and the bioprocess is based on either absolute time or relative time between different parts of the reference bioprocess.

[0016] Optionally, the process data comprises time series data.

[0017] Optionally, the reference data and process data are synchronised in time based on one more corresponding reference parts of the reference bioprocess and current bioprocess.

[0018] Optionally, communicating the deviation and / or conformity between the current bioprocess and the reference bioprocess comprises displaying the process data and the reference data together for visual comparison. Optionally, the process data and the reference data are displayed at least for a current time, and optionally additionally for a past time, and the reference data optionally additionally for a future time. Optionally, in the process data and the reference data are displayed graphically, numerically and / or textually.

[0019] Optionally, the method further comprises comparing the process data and the reference data to determine the deviation and / or conformity.

[0020] Optionally, communicating the deviation and / or conformity between the current bioprocess and the reference bioprocess comprises an alert alerting a user to the determined deviation and / or conformity, such as a visual alert or an audio alert.

[0021] Optionally, the reference data is based on previously collected process data for at least one previous bioprocess. Optionally, the reference data is based on a statistical combination of previously collected process data for a plurality of previous bioprocesses. Optionally, the reference data is generated by a mathematical model. Optionally, the mathematical model is trained to generate the reference data based on training data comprising collected data for a plurality of previous bioprocesses. Optionally, the mathematical model is a machine learning model.

[0022] Optionally, the reference data is modified, in real-time, during the current bioprocess, based on the collected process data.

[0023] Optionally, the method further comprises collecting the process data for at least one previous bioprocess. Optionally, the reference data is generated based on previously collected process data for the at least one previous bioprocess.

[0024] Optionally, the method further comprises generating the reference data.

[0025] According to a second aspect, there is provided a computer system for collecting process data for a bioprocess, the data collection device comprising: a data interface configured to connect with a bioprocess apparatus for carrying out a bioprocess and collect, in real-time, process data for a current bioprocess; one or more data processors; and a user interface; wherein the computer system is pre-provided with reference data relating to a reference bio process, the reference data corresponding to the process data; and the computer system is configured to communicate to a user, in real-time, via the user interface deviation and / or conformity between the current bioprocess and the reference bioprocess based on the process data and the reference data.

[0026] Optionally, the user interface comprises a display.

[0027] According to a third aspect, there is provided a computer programme product comprising instructions which, when executed by a computer, cause the computer to carry out the steps of the method of the first aspect.

[0028] According to a fourth aspect, there is provided data processing device comprising the means for carrying out the method of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Further features of the disclosure will be described below, by way of non-limiting examples and with reference to the accompanying drawings, in which:

[0030] Fig. 1 shows a chromatography system embodied as a chromatography apparatus according to one or more embodiments of the disclosure;

[0031] Fig. 2 is a flow chart showing an example bioprocess;

[0032] Fig. 3 shows an example bioprocess system;

[0033] Fig. 4a shows an example visual display view;

[0034] Fig. 4b shows another example visual display view;

[0035] Fig. 5 shows another example visual display view;

[0036] Fig. 6 shows another example visual display view; and Fig. 7 shows an example computer system.

[0037] DETAILED DESCRIPTION

[0038] An “or” in this description and the corresponding claims is to be understood as a mathematical OR which covers “and” and “or”, and is not to be understand as an XOR (exclusive OR). The indefinite article “a” in this disclosure and claims is not limited to “one” and can also be understood as “one or more”, i.e., plural.

[0039] The following describes embodiments of the invention based on a chromatography process. It should be understood that the invention is not limited to a chromatography process and the bioprocess may be different in other embodiments. For example, the bioprocess may be a bioreactor process or a filtration process. Each of these processes may use a different apparatus, with different components, and may collect different data.

[0040] Fig. 1 shows a chromatography system 100 embodied as a chromatography apparatus according to one or more embodiments of the disclosure.

[0041] The chromatography system 100 is configured to provide a desired system functionality, typically to receive input substances S input l, Sinput_2, Sinput_3 and produce one or more desired substances SDesiredl, §Desired2, SDesired3. In one example, the chromatography system 100 comprises a chromatography apparatus configured to separate a desired substance or sample Soesired from one or more input substances S input i - Sinput _N, e.g., different mixtures of the sample and other compositions.

[0042] The chromatography system 100 may comprise a selection of bioprocessing units, such as reservoirs 151, 152 ... -N, a column 141, a splitter 170, at least one UV sensor, a pH sensor 131 and a conductivity sensor 132. The chromatography system 100 in the form of a chromatography apparatus is described in further detail below.

[0043] The chromatography apparatus 100 may typically comprise at least one inlet 155. The inlet may optionally be coupled to one or more reservoirs 151, 152 ... -N configured to hold a fluid. It is understood that the chromatography apparatus 100 may comprise any number of reservoirs and corresponding inlets. The inlet 155 may e.g., be implemented as tubular elements such as a tube or hose. The chromatography apparatus 100 may further comprise a valve unit (not shown). The valve unit may be coupled to the reservoir(s) 151, 152 ... -N by the inlet 155 coupled to the fluid inlet 101. The valve unit may be configured to be coupled to a (e.g. a first) column 141 by a first pair of fluid ports 130, 140. The first column 141 may be comprised in the chromatography apparatus 100 or arranged external to the chromatography apparatus 100.

[0044] The chromatography apparatus 100 may typically comprise one or more pumps (not shown) for providing flow of liquids through the system. In some examples, at least one pump is arranged close to the at least one inlet 155 to draw liquid from the one or more reservoirs 151, 152 ... -N towards the valve unit.

[0045] The chromatography apparatus 100 may further comprise an intelligent packing fluid port or packing fluid port 150 configured to be coupled to a packing port of the column 141. The chromatography apparatus 100 may further comprise a waste fluid port 160 configured to be coupled to a waste reservoir or drain (not shown).

[0046] The chromatography apparatus 100 may further comprise or be operatively coupled to a control unit 110 which comprises circuitry, e.g., a processor and a memory. The memory may contain instructions executable by the processor, whereby said chromatography apparatus 100 is operative to perform any of the steps or methods described herein. The chromatography apparatus 100 may optionally comprise a splitter 170 coupled to an optional outlet valve 120. The splitter 170 may be configured to direct fluid to the outlet valve 120 or any other unit. Optionally the splitter 170 may be communicatively coupled to the control unit 110 and perform coupling of fluid in in response to a control signal from the control unit 110.

[0047] The chromatography apparatus 100 may further comprise an outlet valve 120 coupled to the splitter 170. The outlet valve 120 may have one or more outlets or outlet ports 121 -123 and is configured to provide the fluid provided by the splitter 170 to the one or more outlets 121 -123 in response to a control signal, e.g., received from the control unit 110.

[0048] The chromatography apparatus 100 may further comprise a pH sensor 131 and / or a conductivity sensor 132. The pH sensor 131 and a conductivity sensor 132 may be coupled to the splitter 170, as shown.

[0049] The pH sensor 131 may be communicatively coupled to the control unit 110 and configured for measuring the pH of the fluid provided to the splitter 170. One or more UV sensor(s) may also be provided to enable monitoring / detection of target protein products. The chromatography apparatus 100 may further comprise a conductivity sensor 132 communicatively coupled to the control unit 110 and configured for measuring the conductivity of the fluid provided by the splitter 170. The pH sensor 131 and / or the conductivity sensor 132 may further be configured to provide the measured pH and measured conductivity as control signals comprising measurement data to the control unit 110.

[0050] The chromatography apparatus 100 may further comprise one or more pressure sensors (not shown) to monitor fluid pressure in the system. In an example, two of these may be arranged upstream (before the column), to measure system inlet pressure, and downstream (after the column), to measure pressure drop across the column.

[0051] The chromatography apparatus 100 may further comprise one or more flow-rate sensors (not shown) to measure and regulate the flow rate of the mobile phase through the system. The chromatography apparatus 100 may further comprise one or more temperature sensors (not shown) to measure the temperature of the mobile phase through the system.

[0052] Mechanical components of the system, including the valve unit, the splitter 170, outlet valve 120, and one or more pumps, may comprise one or more sensors configured to sense an operation mode of the component. Some components may operate bimodally, e.g. on / off, open / closed. Other components may operate multimodally, e.g. where a valve is able to divert flow from two or more inlets and / or to two or more outlets.

[0053] Fig. 2 is a flow chart illustrating a typical chromatography process. In step SI, Method Settings, system settings for the process are set. In step S2, Equilibration, an equilibration buffer is pumped through the column at a predefined flow rate and the UV absorbance and pressure are monitored to ensure stable baseline conditions. In Step S3, Sample Application, a prepared sample is loaded onto the column using the system's sample pump. In step S4, Column Wash, the column is washed with the equilibration / binding buffer to remove unbound or weakly bound impurities. In step S5, Elution, the concentration of buffer is changed, either gradually or stepwise, to elute the bound molecules based on their binding strength and the eluted fractions are collected using the fraction collector. In step S6, Equilibration, the column is re-equilibrated with equilibration buffer to prepare it for the next run.

[0054] Fig. 3 shows an example chromatography system 300 comprising the chromatography apparatus 100 and a computer system 200. The computer system 200 is configured to receive process data from the chromatography apparatus 100, e.g. via the control unit 110. The computer system may comprise a data interface 201 configured to connect with the chromatography apparatus 100.

[0055] The process data provided to the computer system 200 may include any data provided by the various sensors of the chromatography apparatus 100, e.g. including the pH sensor 131, the conductivity sensor 132, the UV sensor(s), the pressure sensor(s), the flow-rate sensor(s) and the temperature sensor(s). Such process data may be provided in the form of a parameter for a given time, e.g. a continuous parameter which may take any value in a given range. Accordingly, such process data may be referred to as sensor parameter data. This sensor parameter data may be time-series data. The sensor parameter data need not be the raw sensor data, but may be calculated based on the raw data, e.g. as the raw data itself may be an electrical signal for example.

[0056] In some examples, additional data may be derived from the sensor parameter data, e.g. calculated based on the sensor parameter data. For example, liquid volume data may be derived from the flow-rate sensor data. For example, peak area (area under peak) may be derived from UV sensor data, as may retention time (Rt), peak height, peak width, peak asymmetry factor, peak resolution (Rs), retention factor (k’), selectivity (a), theoretical plate number (N), height equivalence to a theoretical plate (HETP) and others. Such data may be referred to as data derived from sensor parameter data. Such data may be calculated by the computer system 200 or the control unit 110.

[0057] The process data provided to the computer system may also include data provided by the mechanical components of the system, e.g. including the valve unit, the splitter 170, the inlet valve, the outlet valve 120, and the pump(s). Such process data may be provided in the form of the operational mode of a component and may comprise one or more of a plurality of discrete modes. Accordingly, such data may be referred to as operation mode data.

[0058] In some examples, the computer system 200 or control unit 110, may detect and optionally provide alerts for the occurrence of one of more events. These events may include various sensor parameter data, or data derived from sensor parameter data, reaching or crossing one or more predefined threshold values, e.g. an upper and / or lower threshold. Accordingly, the events may include the occurrence of a parameter reaching a threshold. The events may also include the occurrence of process steps, and / or corresponding instructions, e.g. from the control unit 110 or computer system 200. Accordingly, such data described in this paragraph may be collectively referred to as event data.

[0059] During a bioprocess, one or more different types of process data may be collected in real time for the bioprocess, referred to as a current bioprocess to distinguish from previous bioprocesses for example. The process data may have a temporal relationship to the current bioprocess. For example, for some types of process data, the process data is based on absolute time, e.g. sensor parameter data obtained in a time-series manner, or the time of an occurrence of an event. For example, for some types of process data, the process data is based on relative time between different parts of the reference liquid chromatography process, e.g. the time between the occurrence of two events.

[0060] Anomalies in the bioprocess may result in process data collected in real time for the current bioprocess diverging from what would typically be expected for the bioprocess. To provide a method for determining anomalies in a bioprocess in real-time, in addition to collecting process data, in real-time, for a current bioprocess, reference data is provided, relating to a reference bioprocess. The reference bioprocess may represent a real or theoretical bioprocess substantially free from anomalies.

[0061] The reference data corresponds to the process data. In other words, the process data and reference data comprise the same types of data such the process data and reference data are comparable to each other. In some examples, the reference data and process data may be synchronised in time based on one more corresponding reference parts of the reference bioprocess and current bioprocess. For example, the reference data and process data may be synchronised at a start of the bioprocess or the start of a particular step of the bioprocess. This may ensure better comparability between the reference data and process data.

[0062] Deviation and / or conformity between the current bioprocess and the reference bio process is then communicated to a user of the bioprocess, based on the process data and the reference data. Thus, anomalies in a bioprocess can be determined in real-time.

[0063] In some examples, the reference data may be based on previously collected process data for at least one (real) previous bioprocess. For example, the reference data may be process data collected during a previous bioprocess run for the same bioprocess. In some examples, the reference data may be based on a statistical combination of previously collected process data for a plurality of previous bioprocesses. For example, the reference data may be averaged over the plurality of previous bioprocesses. In such an example, the reference data may be generated by a mathematical model, based on the process data for a plurality of previous bioprocesses. In some examples, the reference data may be generated by a mathematical model trained to generate reference data based on training data comprising collected data for a plurality of previous bioprocesses. Such a mathematical model may be a machine learning model.

[0064] In some examples, the mathematical model may be trained on data relating to different runs of different bioprocesses of the same type (e.g. chromatography), e.g. the same type of bioprocesses following different bioprocess steps or the same type of bioprocesses having different method settings. The model may receive as input, information about, or identifying, the current bioprocess, e.g. including process steps to be performed, instructions for performing the bioprocess and / or settings for the bioprocess apparatus. Based on this input, the mathematical model may generate process data that models the current bioprocess. In other examples, the mathematical model may be specifically for the current bioprocess and be trained on data relating to different runs of essentially the same bioprocess, e.g. with following the same process steps.

[0065] In some examples, reference data may be at least partly based on data that is obtained outside the bioprocess, i.e. not from sensors of the bioprocess system on which the bioprocess was performed. For example, data imported by user input or analysis data from chromatography fractions after the bioprocess is performed and the referenced data may be at least partly based on such data.

[0066] In some examples, the reference data may be modified, in real-time, during the current bioprocess, based on the collected process data. For example, reference data for a future point time may be modified based on the collected process data. Thus, the reference data can take into account what has actually happened during the current bioprocess and more accurately predict what should be expected in the future. A mathematical model may be configured to modify the reference data in this way. The mathematical model may receive as input at least initial reference data and the process data and output modified reference data.

[0067] In some examples, the reference data may be stored in a memory of the computer system and retrieved for use prior to the above described method. In some cases, the reference data may be generated, e.g. based on stored data, prior to the above described method, e.g. as a preceding step. In some cases, for reference data based previously collected process data for a previous bioprocess, the method may include performing said previous bioprocesses and collecting said previous process data, which may then be stored in a memory.

[0068] In a preferred embodiment, communicating the deviation and / or conformity between the current bioprocess and the reference bioprocess may comprise displaying the process data and the reference data together for visual comparison, e.g. by a user of the computer system. Figs. 4 to 6 show three different examples of such an embodiment. The computer system 200 may therefore comprise a display for displaying the process data and the reference data.

[0069] As shown in Fig. 4a, the computer system display view 400 may display process data comprising sensor parameter data 401 of at least on type, e.g. UV data from UV sensor(s), conductivity data from conductivity sensor(s), PH data from PH sensor(s) and temperature data from temperature sensor(s) etc., in real time. The sensor parameter data 401 can be obtained from multiple sensors or one single instrument. The computer system display view 400 may additionally display corresponding reference data 402, for both a past time and a future time. Such data may be displayed graphically, e.g. as a graph. In the present example, chromatograms 401, 402 are displayed, e.g. corresponding to sensor parameter data from the UV sensor(s) 131 of the chromatography system 100. Additionally, further sensor parameter data from, e.g. the conductivity sensor 132, may be displayed in combination with the UV sensor data in the same display view with corresponding reference data 404, as shown in Fig. 4b. This data may be similarly displayed graphically, e.g. as a graph. Preferably, the x-axis of the graph(s) is time. The display views in Fig.4a and 4b only show examples of displaying sensor parameter data such as UV data and conductivity data separately or in combination, other sensor parameter data such as PH data and temperature data can also be shown in similar ways.

[0070] As shown, the computer system display view 400 may additionally display process data 405 and reference data 406 comprising operation mode data and / or event data. As shown, this data 405, 406 may be displayed both graphically to identify a time at which the operation mode or event occurs and using text and / or numbers to describe the operation mode or event. As shown, the operation mode data and / or event data may be provided as annotations on the graphs displaying the sensor parameter data. In some examples, numerical information may be shown graphically instead, e.g. as a bar.

[0071] In Fig. 4a and Fig.4b, data to the left of the dashed line is in the past and data to the right is future reference data.

[0072] In the example shown in Fig. 4a, the process data identifying an operation mode or event is marked as 405 placed above the x-axis while the corresponding reference data is marked as 406 placed below the X-axis. For example, event process and reference data identifying a process step, namely a “Injection” step, is identified by numeral 405b and 406b. Operation mode process and reference data identifying an operation mode, namely opening of an inlet valve, is identified by reference numerals 405a and 406a.

[0073] As shown in Fig. 5, the computer display view 500 may display a model or schematic image of the bioprocess 501, 502, e.g. the apparatus 100. This is another form of graphical display. As shown, the computer display view 500 may display two such images, one corresponding to the process data 501 and one corresponding to the reference data 502. The images 501, 502 may show the progress of the bioprocess, in real time, as it is performed. For example, the fluid may be shown moving through the bioprocess apparatus. Operation mode data may be shown graphically and by text or numbers, e.g. by highlighting and / or annotating corresponding components of the bioprocess apparatus 100. Further, as shown, sensor parameter data 503 may be displayed numerically. The dashed lines in Fig. 5 indicate the progress of the process and may move, e.g. from left to right, as the process proceeds.

[0074] As shown in Fig. 6, the computer display view 600 may display reference events, operation modes and / or sensor parameters, in a list. As shown, the computer display view 600 may display two such lists, one corresponding to the process data 601 and one corresponding to the reference data 602. The lists 601, 602 may show the progress of the bioprocess, in real time, as it is performed. As shown, corresponding event or operation mode data 601 may be displayed visually by highlighting the corresponding entry in the list when it occurs in time. In some examples, sensor parameter data 602 may be displayed as numerals, which may change in real-time. In other examples, sensor parameter data may be shown graphically, e.g. by a bar. Each of the examples in Figs. 4 to 6 may be used in any combination. It may also be possible for a user to switch between these different displays, e.g. via a user interface of the computer system 200.

[0075] Based on the visual display of the process data and the reference data, a user may visually compare the process data and the reference data to determine the deviation and / or conformity between the process data and the reference data.

[0076] In some examples, the process data and the computer system 200 may be configured to compare the process data and the reference data to determine the deviation and / or conformity between the process data and the reference data. In such an example, communicating the deviation and / or conformity between the current bioprocess and the reference bioprocess may comprise an alert alerting a user to the determined deviation and / or conformity, such as a visual alert or an audio alert. In some examples, the computer system may be configured to automatically pause the bioprocess when a deviation occurs, preferably deviation of a sufficient magnitude or importance. In some examples, the comparison may be performed by a machine learning model trained to determine deviation and or conformity, e.g. deviation of a sufficient magnitude or importance.

[0077] Fig. 7 shows the computer system 200, according to one or more embodiments of the present disclosure. The computer system 200may be in the form of e.g., a chromatography system, a computer, a server, an on-board computer, a stationary computing device, a laptop computer, a tablet computer, a handheld computer, a wrist-worn computer, a smart watch, a smartphone, or a smart TV. The computer system 200may comprise processing circuitry 712 communicatively coupled to a transceiver 704 configured for wired or wireless communication. The computer system 200 may further comprise at least one optional antenna (not shown in figure). The antenna may be coupled to the transceiver 704 and is configured to transmit and / or emit and / or receive wired or wireless signals in a communication network, such as Wi-Fi, Bluetooth, 3G, 4G, 5G etc. In one example, the processing circuitry 712 may be any of a selection of a processor and / or a central processing unit and / or processor modules and / or multiple processors configured to cooperate with each-other. Further, the computer system 200 may further comprise a memory 715. The memory 715 may e.g., comprise a selection of a hard RAM, disk drive, a flash drive or other removable or fixed media drive or any other suitable memory known in the art. The memory 715 may contain instructions executable by the processing circuitry to perform any of the steps or methods described herein. The processing circuitry 712 may be communicatively coupled to a selection of any of the transceiver 704 and the memory 715. The computer system 200 may be configured to send / receive control signals directly to any of the above-mentioned units or to external nodes or to send / receive control signals via a wired and / or wireless communications network.

[0078] The wired / wireless transceiver 704 and / or a wired / wireless communications network adapter may be configured to send and / or receive data values or parameters as a signal to or from the processing circuitry 712 to or from other external nodes.

[0079] In an embodiment, the transceiver 704 communicates directly to external nodes or via a wireless communications network.

[0080] In one or more embodiments the computer system 200 may further comprise an input device 717, configured to receive input or indications from a user and send a user input signal indicative of the user input or indications to the processing circuitry 712.

[0081] In one or more embodiments the computer system 200 may further comprise a display 718 configured to receive a display signal indicative of rendered objects, such as text or graphical user input objects, from the processing circuitry 712 and to display the received signal as objects, such as text or graphical user input objects.

[0082] In one embodiment the display 718 is integrated with the user input device 717 and is configured to receive a display signal indicative of rendered objects, such as text or graphical user input objects, from the processing circuitry 712 and to display the received signal as objects, such as text or graphical user input objects, and / or configured to receive input or indications from a user and send a user-input signal indicative of the user input or indications to the processing circuitry 712.

[0083] In a further embodiment, the computer system 200 may further comprise and / or be coupled to one or more additional sensors (not shown in the figure) configured to receive and / or obtain and / or measure physical properties pertaining to the computer and / or chromatography system and send one or more sensor signals indicative of the physical properties to the processing circuitry 712. In one or more embodiments, the processing circuitry 712 is further communicatively coupled to the input device 717 and / or the display 718 and / or the additional sensors.

[0084] In embodiments, the communications network communicate using wired or wireless communication techniques that may include at least one of a Local Area Network (LAN), Metropolitan Area Network (MAN), Global System for Mobile Network (GSM), Enhanced Data GSM Environment (EDGE), Universal Mobile Telecommunications System, Long term evolution, High Speed Downlink Packet Access (HSDPA), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth®, Zigbee®, Wi-Fi, Voice over Internet Protocol (VoIP), LTE Advanced, IEEE802.16m, WirelessMAN-Advanced, Evolved High-Speed Packet Access (HSPA+), 3GPP Long Term Evolution (LTE), Mobile WiMAX (IEEE 802.16e), Ultra Mobile Broadband (UMB) (formerly Evolution- Data Optimized (EV-DO) Rev. C), Fast Low-latency Access with Seamless Handoff Orthogonal Frequency Division Multiplexing (Flash-OFDM), High Capacity Spatial Division Multiple Access (iBurst®) and Mobile Broadband Wireless Access (MBWA) (IEEE 802.20) systems, High Performance Radio Metropolitan Area Network (HIPERMAN), Beam- Division Multiple Access (BDMA), World Interoperability for Microwave Access (WiMAX) and ultrasonic communication, etc., but is not limited thereto.

[0085] Moreover, it is realized by the skilled person that the computer system 200 may comprise the necessary communication capabilities in the form of e.g., functions, means, units, elements, etc., for performing the present solution. Examples of other such means, units, elements and functions are: processors, memory, buffers, control logic, encoders, decoders, rate matchers, de-rate matchers, mapping units, multipliers, decision units, selecting units, switches, interleavers, de-interleavers, modulators, demodulators, inputs, outputs, antennas, amplifiers, receiver units, transmitter units, DSPs, MSDs, TCM encoder, TCM decoder, power supply units, power feeders, communication interfaces, communication protocols, etc. which are suitably arranged together for performing the present solution.

[0086] Especially, the processing circuitry of the present disclosure may comprise one or more instances of a processor, processor modules and multiple processors configured to cooperate with each-other, Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, a Field-Programmable Gate Array (FPGA) or other processing logic that may interpret and execute instructions. The expression “processing circuitry” and / or “processing means” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones mentioned above. The processing means may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as processing control, user interface control, or the like.

[0087] In one embodiment, a computer is provided, wherein the computer is configured to perform any or all of the method steps of the method described herein.

[0088] In one embodiment, a chromatography apparatus and / or system is provided, the chromatography apparatus and / or system comprising all or a selection of the features of the computer described in relation to Fig. 7. The chromatography apparatus or system is configured to perform any or all of the method steps of the method described herein.

[0089] In one embodiment, a computer program is provided comprising computer-executable instructions for causing a computer, when the computer-executable instructions are executed on a processing unit comprised in the computer, to perform any of the method steps of the method described herein.

[0090] In one embodiment, a computer program product is provided comprising a computer- readable storage medium, the computer-readable storage medium having the computer program above embodied therein.

[0091] In one embodiment, a carrier containing the computer program above is provided, wherein the carrier is one of an electronic signal, optical signal, radio signal, or computer readable storage medium.

[0092] Various embodiments of the present invention can thus provide a method, computer or program wherein source data, target data and / or raw data is generated by or provided to a bioprocessing device / system that comprises one or more of: a chromatography device, a cell culture device, a filtration device and / or an oligo synthesis device.

[0093] Finally, it should be understood that the invention is not limited to the embodiments described above, but also relates to and incorporates all embodiments within the scope of the appended independent claims.

Claims

CLAIMS1. A computer implemented method for determining anomalies in a bioprocess in real-time, the method comprising: collecting, in real-time, process data for a current bioprocess, providing reference data relating to a reference bioprocess, the reference data corresponding to the process data; communicating to a user, in real-time, deviation and / or conformity between the current bioprocess and the reference bio process based on the process data and the reference data.

2. The method of claim 1, wherein the bioprocess is one of: a chromatography process, a bioreactor process, a filtration process and an oligo-synthesis process.

3. The method of any preceding claim, wherein the process data comprises one or more of: data derived from sensor parameter data, the sensor parameter data relating to measurements by one or more sensors of a bioprocess apparatus, operation mode data relating to one or more operation modes of one or more mechanical components of the bioprocess apparatus, and event data relating to the occurrence of one or more process events.

4. The method of claim 3, wherein the process data further comprises sensor parameter data.

5. The method of claim 3 or 4, wherein, when the bioprocess is chromatography, the sensor parameter data comprises data from one or more of: a pH sensor, a conductivity sensor, a UV sensor, a pressure sensor, a flow-rate sensor and a temperature sensor.

6. The method of claim 5, wherein, when the sensor is a UV sensor, data derived from the sensor parameter data comprises one or more of peak area (area under peak) derived from UV sensor data, retention time (Rt), peak height, peak width, peak asymmetry factor, peak resolution (Rs), retention factor (k’), selectivity (a), theoretical plate number (N), and height equivalence to a theoretical plate (HETP).

7. The method of any one of claims 3 to 6, wherein the operation mode data comprises data relating to one or more of: a valve unit, a splitter, an inlet valve, an outlet valve, and a pump.

8. The method of any one of claims 3 to 7, wherein the event data comprises data relating to one or more of: the occurrence of a parameter reaching a threshold, the occurrence of one or more process steps and / or corresponding instructions to the bioprocess apparatus.

9. The method of any preceding claim, wherein the process data has a temporal relationship to the current bioprocess, the temporal relationship between the process data and the bioprocess being based on either absolute time or relative time between different parts of the reference bioprocess.

10. The method of any preceding claim, wherein the process data comprises time series data.

11. The method of any preceding claim, wherein the reference data and process data are synchronised in time based on one more corresponding reference parts of the reference bioprocess and current bioprocess.

12. The method of any preceding claim, wherein communicating the deviation and / or conformity between the current bioprocess and the reference bioprocess comprises displaying the process data and the reference data together for visual comparison.

13. The method of claim 12, wherein the process data and the reference data are displayed at least for a current time, and optionally additionally for a past time, and the reference data optionally additionally for a future time.

14. The method of claim 12 or 13, wherein the process data and the reference data are displayed graphically, numerically and / or textually.

15. The method of any preceding claim, wherein the method further comprises comparing the process data and the reference data to determine the deviation and / or conformity.

16. The method of any preceding claim, wherein communicating the deviation and / or conformity between the current bioprocess and the reference bioprocess comprises an alert alerting a user to the determined deviation and / or conformity, such as a visual alert or an audio alert.

17. The method of any preceding claim, wherein the reference data is based on previously collected process data for at least one previous bioprocess.

18. The method of any of claims 1-16, wherein the reference data is based on a statistical combination of previously collected process data for a plurality of previous bioprocesses.

19. The method of any of claims 1-16, wherein the reference data is generated by a mathematical model.

20. The method of claim 19, wherein the mathematical model is trained to generate the reference data based on training data comprising collected data for a plurality of previous bioprocesses.

21. The method of claim 19 or 20, wherein the mathematical model is a machine learning model.

22. The method of any preceding claim, wherein the reference data is modified, in realtime, during the current bioprocess, based on the collected process data.

23. The method of any preceding claim, further comprising collecting the process data for at least one previous bioprocess.

24. The method of claim 23, wherein the reference data is generated based on previously collected process data for the at least one previous bioprocess.

25. The method of any preceding claim, further comprising generating the reference data.

26. A computer system for collecting process data for a bioprocess, the data collection device comprising: a data interface configured to connect with a bioprocess apparatus for carrying out a bioprocess and collect, in real-time, process data for a current bioprocess; one or more data processors; and a user interface; wherein the computer system is pre-provided with reference data relating to a reference bio process, the reference data corresponding to the process data; and the computer system is configured to communicate to a user, in real-time, via the user interface deviation and / or conformity between the current bioprocess and the reference bioprocess based on the process data and the reference data.

27. The computer system of claim 26, wherein the user interface comprises a display.

28. A computer programme product comprising instructions which, when executed by a computer, cause the computer to carry out the method of any of claims 1-25.

29. A data processing device comprising the means for carrying out the method of any of claims 1-25.

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