APPARATUS FOR CONTROLLING A PROCESS AND ACCOMPANYING CONTROL METHOD

Abstract

For the improved autonomous control of a process (2) using an apparatus (1) via setting of at least one action parameter (3) controlling the process (2), it is provided that via a measuring instrument (17), preferably a spectrometer (18) integrated into the apparatus (1), a process response (4), which the process (2) transfers in reaction to an adjustment of the at least one action parameter (3) to its immediate environment, is measured and evaluated in a computer-implemented manner, preferably using an artificial intelligence, and that based on this evaluation, the at least one action parameter (3) is automatically readjusted. This approach is applicable to biological, chemical and physical processes.

Claims

1. A method for controlling an apparatus (1), in which a process (2) takes place that is carried out by a biological system (34) or a non-biological system, and the process (2) is controlled by setting at least one action parameter (3), the method comprising: measuring a process response (4) of the process (2) on the at least one action parameter (3); evaluating the process response (4) with a computer-implemented evaluation (6) using a preset target value (5); and adjusting at least one set value of the at least one action parameter (3) in a computer-implemented manner based on the evaluation (6).

2. The method as claimed in claim 1, wherein at least one of: the predetermined target value (5) is a reference response (5) for the process response (4), and the adjusting is for aligning the process response (4) with the predetermined target value (5); or process (2) takes place in a sample (12) that comprises a culture medium (13) and the process response (4) is measured in the culture medium (13).

3. The method as claimed in claim 1, further comprising measuring the process response (4) of the process (2) on a medium (13) that surrounds elements (14) of the system (34) on which the process (2) is based, and the system (34) is embedded in the medium (13) which forms a culture medium (13).

4. The method as claimed in claim 3, further comprising measuring at least one measurement parameter (8) of the process response (4) in an immediate environment of the elements (14) of the biological system (34) on which the process (2) is based, without direct measurement of the elements (14) of the biological system (34).

5. The method as claimed in claim 1, wherein by measuring the process response (4), at least one of a consumption or a production of at least one material is acquired by the process (2), at least indirectly, and wherein at least one of: the process (2) is influenced by setting the at least one action parameter (3); or by measuring the process response (4), an activity of the system (34) including at least one of (i) a thermogenesis (production of heat by metabolic activity), (ii) a chemo- or biogenesis (production of chemical substances or biological organisms by metabolic activity), (iii) a photogenesis (production of light by metabolic activity), an energy consumption, or (iv) a material consumption or a material production, is acquired.

6. The method as claimed in claim 1, wherein the process (2) changes at least one environmental factor, including at least one of a material composition, a temperature, a pH, a permittivity, an electrical conductivity, an optical transmission or reflection behavior, or an environmental factor of a culture medium (13) in which the biological system (34) is cultured, and the method further comprises measuring the at least one environmental factor as at least one measurement parameter (8) of the process response (4).

7. The method as claimed in claim 1, further comprising acquiring at least one measurement parameter (8a) of the process response (4) using a spectrometric measurement.

8. The method as claimed claim 1, wherein the adjusting of the respective set value of the at least one action parameter (3) is computer-implemented via an artificial intelligence (AI).

9. The method as claimed in the claim 8, wherein the AI uses data sets comprising a respective measured process response (4) and an accompanying set of action parameter values producing said process response (4) in order to at least one of prepare or optimize a prediction model for the system response (4), and the AI, with the help of the prediction model, generating virtual system responses in reaction to respective virtual sets of action parameter values, and validating said virtual system responses using real tests.

10. The method as claimed in claim 1, wherein at least one optimized set value for the at least one action parameter (3) is independently learned in a computer-implemented manner by the apparatus (1) based on several evaluations (6) derived by the apparatus (1) from respective ones of the process responses (4), in each case in reaction to set values of the at least one action parameter (3) specified by the apparatus (1).

11. The method as claimed in claim 1, wherein in addition to the process response (4), the method further comprises measuring a process status, and a first measurement parameter (8) is measured by the process response (4) and a second measurement parameter (8) is measured by the process status.

12. The method as claimed in claim 1, further comprising measuring at least two measurement parameters (8) and using one of the two measurement parameters (8) in order to verify an evaluation carried out using the other measurement parameter (8).

13. The method as claimed in claim 1, further comprising measuring at least two measurement parameters (8), and the measurement parameters (8a, 8b, 8c) are selected from the following group of measurement parameters (8): optical measurement variables including at least one of an absorption spectrum, an emitted light intensity, or a fluorescence; electrical variables, including at least one of an electrical conductivity or permeability; thermal variables, including a self-heating of a biological sample; or pH values.

14. The method as claimed claim 13, further comprising evaluating each of the measurement parameters (8), using a respective preset target value (5a, 5b) using a respective computer-implemented evaluation (6a, 6b), and adjusting at least one set value of the at least one action parameter (3) in a computer-implemented manner based on the evaluations (6a, 6b).

15. The method as claimed in claim 1, further comprising using a first measurement parameter (8a) to at least one of verify or adjust an evaluation criterion which is used to generate an evaluation (6b) of a second measurement parameter (8b), via a method of self-supervised learning, in which the first measurement parameter (8a) is taken as a basic truth in order to improve the evaluation of the second measurement parameter (8b).

16. The method as claimed in claim 15, wherein at least one of the measurement parameters (8a, 8b, 8c) is an overall measurement parameter (8) that is influenceable by all elements (14) of the biological system (34), and at least one of (a) the overall measurement parameter (8) is acquired without direct measurement of the elements (14) of the biological system (34), or (b) at least one of the acquired measurement parameters (8a, 8b, 8c) is a local measurement parameter that is only influenceable by individual ones of the elements (14) of the biological system (34), and the local measurement parameter is acquired by direct measurement of the individual elements (14) of the biological system (34).

17. An apparatus (1) for the autonomous control of a process (2), comprising: a process chamber (15) for accommodating a biological, chemical or physical system, in which the process (2) takes place, a controller (16) configured to set at least one action parameter (3) in order to control the process (2) using the action parameter (3), and at least one measuring device (17) for measuring a process response (4) of the process (2), which takes place in reaction to an adjustment of the at least one action parameter (3).

18. The apparatus (1) as claimed in the claim 17, wherein the apparatus is configured to control a biological process (2), and at least one of (a) the at least one of the measuring device (17) is configured to acquire an overall measurement parameter (8) of the process response (4), which is changeable or is changed by all elements (14) of the biological system (34) on which the process (2) is based, or (b) the at least one of the measuring device (17) is configured to acquire the overall measurement parameter (8) and is arranged such that the measurement of the process response (4) takes place at least partially at a measuring point (20) that is kept free from the elements (14) of the biological system (34).

19. The apparatus (1) as claimed in claim 18, further comprising a microfluidic device (21) for supplying the system (34) with a medium, and at least one of (a) the microfluidic device (21) comprises a microfluidically active separating structure (22) with which the elements (14) of the biological system (34) are maintained at a distance from the measuring point (20) at which the process response (4) is acquired via the at least one measuring device (17), or (b) the at least one measuring means (17) is at least partially integrated into the microfluidic device (21) and the measuring point (20) is therefore unchangeable with respect to the separating structure (22).

20. The apparatus (1) as claimed in claim 17, further comprising at least one actuator (23) configured to change the at least one action parameter (3), and the at least one actuator (23) is regulatable by the controller (16), the controller (16) is configured to adjust at least one set value of the at least one action parameter (3) in a computer-implemented manner by an evaluation (6) of the process response (4) in order to align the process response (4) with a preset target value (5).

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In the following description of various preferred embodiments of the invention, elements that are consistent in their function are given consistent reference numbers, even when they are of deviating configuration or form. The example presented relates to the control of a biological process. However, based on the explanations, the method according to the invention and the accompanying device can also be applied by a person skilled in the art to chemical or physical systems and processes.

[0086] The FIGURE shows the following:

[0087] FIG. 1 a schematic overview of an apparatus according to the invention for controlling a biological process that takes place in the apparatus.

DETAILED DESCRIPTION

[0088] FIG. 1 shows an apparatus designated 1 as a whole, by means of which a biological process 2, which takes place in the apparatus 1, can be controlled autonomously, i.e. without external human intervention. The apparatus 1 comprises a culturing chamber 15 in the form of a microfluidic chamber through which a culture medium 13 can be guided that nourishes a biological system 34, which is cultured in the culturing chamber 15. The biological system 34 can consist in particular of elements 14 or comprise such elements, wherein the elements are cells 14 and/or microorganisms 14. The biological process 2 thus takes place in the microfluidic biological sample 12, which is formed by the biological system 34 and the culture medium 13 in the culturing chamber 15.

[0089] The apparatus 1 further comprises a reservoir 27 in which multiple substances 26 are stored, which can be fed via the supply line 24 shown (which comprises multiple separate lines) into the culturing chamber 15 in order to thus influence the biological process 2 taking place there as a respective action parameter 3a. Here, the actual action parameter 3a constitutes the flow rate at which a specified substance 26 is fed into the culturing chamber 15. This means that there are several action parameters 3a, each of which characterizes a flow rate of one of the substances 26 from the reservoir 27 to the culturing chamber 15.

[0090] In order to set this action parameter 3a, the apparatus 1 comprises at least one actuator 23 in the form of a valve 29 that is connected to a controller 16 via a data line 30. The controller 16 can thus access the adjustable valve 29 in a controlling manner and thus regulate or set the flow rate, i.e. the action parameter 3a.

[0091] The apparatus 1 further comprises a further actuator 23 in the form of a heating element 28 with which an overall temperature prevailing in the culturing chamber 15 can be changed. The temperature in the culturing chamber 15 can be monitored by the controller 16 by means of the temperature sensor 10 shown, which is connected via a data line 30 to the controller 16. Furthermore, the controller 16 can also exert a controlling action on the heating element 28 via the data line 30 shown (by specifying an electrical heating current) and thus set a heating power as a further action parameter 3b, which can be supplied to the culturing chamber 15 and thus the biological process 2 by means of the heating element 28.

[0092] The apparatus 1 further comprises a camera 19 as a measuring means 17, with which microscopic images of the biological sample, in particular the biological system 34, such as cells of a cell culture 33 that grow in the culturing chamber 15 can be recorded.

[0093] Via the drainage line 25, the culture medium 13 can be discharged at regular intervals and transported to the measuring point 20 shown. A further measuring means 17 in the form of a spectrometer 18 is connected at the measuring point 20 via a glass fiber 32 and can thus spectroscopically measure the culture medium 13 at the measuring point 20. A microfluidically active separating structure 11 in the form of a filter ensures that the elements of the biological system 34, which are cultured in the culturing chamber 15, are kept distant from the measuring point 20 so that the spectrometric measurement carried out with the spectrometer 18 takes place under exclusion of the biological system 34, wherein for this purpose only the culture medium 13, but not the elements 14 contained therein of the biological system 34, are illuminated. In other applications, the filter can also be removed so that the spectrometer 18 then conducts spectral measurements of both the culture medium 13 and the elements 14 contained therein. In this manner, for example, an OD600 measurement could be carried out (see further above).

[0094] After the culture medium 13 has passed the measuring point 20, it flows via the further drainage line 25 into a collection container 22.

[0095] As indicated by the dotted line in FIG. 1, a part of the apparatus 1 is configured as a microfluidic device 21. This serves on the one hand to supply the biological system 34 with the culture medium 13; on the other hand, to record microscopic images with the camera 19 and finally the spectrometric measurement explained above. For this purpose, the glass fiber 32 is integrated into the microfluidic device 21, while the actual measurement assembly of the spectrometer 18 is arranged outside a housing 31 of the apparatus 1 that accommodates the other components of the apparatus 1.

[0096] The spectrometer 18 is also controlled and read by the controller 16. By means of the spectrometric measurement, it is also possible to carry out indirect acquisition of the chemical substances or biological organisms produced by the biological process 2 (which is known as chemo- or biogenesis).

[0097] By means of the spectrometric measurement, it is therefore possible to carry out indirect acquisition of both a consumption of specified substances and the production of specified substances by the biological process 2. This acquisition takes place precisely during the biological process 2 and while—by setting of the action parameters 3—the biological process 2 is being influenced.

[0098] The controller 16 of the apparatus 1 is now configured for setting the two action parameters 3a, 3b, i.e. the flow rate 3a at which the substance 26 reaches the culturing chamber 15 and the heating power 3b that is supplied by means of the heating element 28 to the culturing chamber 15 and thus the biological process 2. By means of setting the action parameters 3, the controller 16 influences conditions that influence the biological process 2, which allows the biological process 2 to be controlled.

[0099] The controller 16 (which can be a microcontroller) further comprises a memory 9, in which a preset target value 5 is stored in the form of a target spectrum.

[0100] In reaction to the action parameters 3a, 3b set by the controller 16, the biological process 2 changes, thus causing a metabolic activity of the microorganisms 14 to change. On the one hand, this leads to an increase in metabolic consumption; on the other hand, however, the microorganisms 14 also produce metabolic products, which they release into the culture medium 13. In other words, the biological process 2, or the biological system 34 responsible for this process, depending on the action parameters 3a, 3b set, responds with a particular process response 4, which the biological process 2 transfers in reaction to an adjustment of at least one of the two action parameters 3a, 3b to its immediate environment, i.e. the culture medium 13.

[0101] On the one hand, this process response 4 is spectrometrically measured by the controller 16 by means of the spectrometer 18, wherein the spectrum measured at the measuring point 20 of the culture medium 13 is stored as a measurement parameter 8a of the process response 4 in an internal memory 9 of the controller 16.

[0102] By means of the temperature sensor 10, the controller 16 can further measure a temperature increase of the biological sample 12, which is formed in the culturing chamber 15 by the culture medium 13 and the biological system 34, as a second measurement parameter 8b of the process response 4. This temperature increase 8b is also stored in the memory 9 as a further measurement parameter 8 and thus as a further component of the process response 4. Here, the temperature increase is measured at points in time when no heating power is being supplied, so that the temperature increase 8b can be fed back to the biological process 2, i.e. is produced thereby (thermogenesis). This second measurement parameter 8b is also stored in the memory 9 and can thus be further processed by the controller 16.

[0103] Moreover, by means of the biological process 2, which is fueled by the biological system 34 and takes place in the culturing chamber 15, numerous environmental factors are changed, i.e. for example the material composition of the culture medium 13, its temperature, its pH, the electrical conductivity of the culture medium 13 and also its optical transmission behavior. In general, all of these environmental factors can be measured according to the method according to the invention as individual measurement parameters 8 of the process response 4 of the biological process 2 in order in this manner to acquire respective changes in these environmental factors in reaction to the respective adjustment of one of the action parameters 3.

[0104] In a following step, the controller 16 compares the two measured measurement parameters 8a, 8b with a respective preset target value 5, i.e. in one case a target spectrum 5a (as a first target variable) and in one case a target value for the temperature increase 5b (as a second target variable). After this, each of the two measurement parameters 8a and 8b acquired as a process response 4 is evaluated by the controller 16 in a computer-implemented manner based on the respective preset target value 5a, 5b by means of a respective evaluation 6a, 6b. The controller 16 then adjusts either the action parameter 3a or the action parameter 3b, or however both action parameters 3a, 3b in a computer-implemented manner based on these two evaluations 6a, 6b.

[0105] This adjustment of the action parameters 3a, 3b takes place with the goal of bringing the measured process response 4 closer to the preset target values stored in the memory 9 as reference responses, i.e. with the goal of controlling the biological process 2 in such a way that a desired temperature increase and a specified spectrum are obtained as a process response 4. In contrast to the regulation of the overall temperature in the culturing chamber 13 by means of the heating element 28, in this case, for example, there is no measurement of how a supplied heating power changes the temperature in the culturing chamber 15; rather, the temperature sensor 10 is used to acquire the amount of heat produced by the metabolic activity of the biological system 34 as a part of the process response 4, which is known by the term thermogenesis.

[0106] It is obvious that this approach can for example also be expanded to the detection of a photogenesis, i.e. the production of light by a metabolic activity of the biological system 34, wherein the light produced by the biological process 2 would then be measured by means of a photosensitive sensor. This also differs for example from the measurement of a light intensity that is supplied by means of a light source—for example as a further possible action parameter 3—to the culturing chamber 15, for example in order to induce photosynthesis in said chamber by means of microorganisms 14.

[0107] The controller 16, which can be configured as a microcontroller, learns the adjustment to be carried out of set values of the two action parameters 3b and 3c by means of an artificial intelligence, which is implemented in the form of an artificial neural network (ANN). In other words, the adjustment of the action parameter 3 and the evaluation of the respective measured measurement parameters 8a, 8b are based on a machine learning method.

[0108] The machine learning makes it possible for the controller 16 to learn independently and in a computer-implemented manner, based on multiple evaluations 6, how the individual action parameters 3 are set such that the measured process response 4 is brought closer and closer to a desired process response 4, which describes a status of the biological process 2 that is to be achieved by control by means of the apparatus 1.

[0109] It thus becomes clear from these explanations that the controller 16, by means of the temperature sensor 10 and the spectrometer 18, measures two measurement parameters 8, i.e. the measured spectrum 8a and an endogenous temperature increase 8b within the biological sample 12, then evaluates the process response 4 composed of these two measurement parameters 8a, 8b by means of a respective evaluation 6a, 6b in a computer-implemented manner, and subsequently adjusts the respective set values of the action parameters 3a, 3b in a computer-implemented manner based on the evaluation 6.

[0110] The adjustment of the action parameters 3a now takes place in that on the one hand, the controller 16, by controlling the valve 29, controls the amount of material 26 that is removed from the reservoir 27 and fed to the biological process 2 in the culture medium 13. On the other hand, the controller 16 can set the action parameter 3b, i.e. the heating power, by sending a larger or smaller amount of control current to the heating element 28, so that the element supplies more or less heat to the culturing chamber 15. This means that the controller 16 can use the temperature sensor 10 once as a measuring means 17 in order to measure the measurement parameter 8b of the thermogenesis generated by the biological process 2. On the other hand, however, the controller 16 can also use the temperature sensor 10 to regulate the heating power 3b generated by means of the heating element 28. In particular, it is obvious that the temperature sensor 10 can be used alternatingly for these two tasks, for example at predetermined time intervals of the process control.

[0111] As has already been discussed, the evaluation of the process response 4 is carried out on the basis of respective preset target values 5a, 5b for the individual measurement parameters 8 of the process response 4. The two measurement parameters 8a and 8b discussed so far, i.e. the measured spectrum 8a and the endogenous temperature increase 8b in the biological sample 12, can be understood in each case as overall measurement parameters, as they are influenced by all of the microorganisms 14 contained in the culture medium 13. Here, at least the spectrum 8a is acquired as an overall measurement parameter without a direct measurement of the microorganisms 14.

[0112] By means of the camera 19 shown, a further measurement parameter 8 can also be acquired. This parameter can in particular also be a measurement parameter 8 of a status of the biological process such as the number of cells 8c that can be acquired within a predetermined viewing window of the microfluidic device 21 by means of an image processing of the camera 19 at a specified point in time. In a variant, moreover, the invention precisely now proposes that such a measurement parameter be evaluated via a process status on the basis of a preset target value 5 and that the adjustment, based on this evaluation, then be carried out by at least one of the above-discussed action parameters 3.

[0113] Moreover, the parameter 8c can be understood as a local parameter, as it is only influenceable by individual elements of the biological system 34. For example, the increase in microorganisms 14 outside of the viewing window has no influence whatsoever on the measurement of the number 8c of cells within the viewing window. This local measurement parameter 8c further differs from the two other measurement parameters 8a and 8b in that it is acquired by means of a direct measurement of individual elements of the biological system 34, i.e. by an image processing of microscopic images of these elements recorded with the camera 19.

[0114] As the measured spectrum and the microscopic images are simultaneously acquired and thus describe a current status of the biological process 2 in each case, the measured spectrum can be used as a first measurement parameter 8a of the acquired process response 4 to correspondingly adjust an evaluation criterion that is used to generate an evaluation 6c of the number of cells per microscopic image, which is used as a further measurement parameter 8c, such that a meaningful evaluation of the recorded microscopic images can take place. In other words, it is thus proposed, in particular by using a method of self-supervised learning, that the recorded spectrum 8a be considered a basic truth, and that the learned evaluation 6a of the spectrum (which takes place using the target spectrum stored in the memory 9) be used in order to improve the evaluation 6c of the number 8c of cells in the individual microscopic images. To put it simply, the apparatus thus independently learns the number of cells in a specified status of the biological process 2 that can reasonably be expected or are achievable, specifically based on the learned evaluation of the measured spectrum 8a, which allows a conclusion to be drawn with respect to the current status of the biological system 34/of the biological process 2.

[0115] Conversely, however, the microscopic images, more specifically the measurement parameter of a specified cell density derived therefrom, can also be used to train an AI to correctly (i.e. meaningfully) evaluate recorded spectra 8a. Generally speaking, it can thus be provided in particular that a measurement parameter which describes a status of the biological process 2 is used by an, in particular the above-mentioned, AI to learn an evaluation 6a of a measurement parameter 8a of the process response 4.

[0116] In summary, it is provided that, for improved autonomous control of a process 2 by means of an apparatus 1 by setting at least one action parameter 3 that controls the process 2, using a measuring means 17, preferably a spectrometer 18 integrated into the apparatus 1, a process response 4 which the process 2 transfers to its immediate environment in reaction to an adjustment of the at least one action parameter 3 is measured and evaluated in a computer-implemented manner, preferably using an artificial intelligence, and that based on this evaluation, the at least one action parameter 3 is automatically readjusted by the apparatus 1, for example in order to guide the process 2 in a desired direction. This approach is applicable to biological, chemical and physical processes.

LIST OF REFERENCE NUMBERS

[0117] 1 Apparatus (e.g. configured as an incubator) [0118] 2 Biological/chemical/physical process (which takes place in 1, more precisely in 15) [0119] 3 Action parameter (for controlling 2) [0120] 4 Process response (of 2) [0121] 5 Preset target value (target) [0122] 6 Evaluation (of 4) [0123] 7 Control variable (for influencing 3) [0124] 8 Measurement parameter (as a part of 4) [0125] 9 Memory [0126] 10 Temperature sensor [0127] 11 Separating structure (e.g. membrane, filter, through-flow opening) [0128] 12 Sample (particularly biological sample) [0129] 13 Medium, in particular culture medium [0130] 14 Elements of 34 (e.g. cells, microorganisms, bacteria, algae, etc.) [0131] 15 Process chamber (particularly culturing chamber for culturing a biological sample) [0132] 16 Controller [0133] 17 Measuring means [0134] 18 Spectrometer [0135] 19 Camera [0136] 20 Measuring point [0137] 21 Microfluidic device (e.g. microfluidic chip) [0138] 22 Collection container [0139] 23 Actuator [0140] 24 Supply line [0141] 25 Drainage line [0142] 26 Material [0143] 27 Reservoir (for 26) [0144] 28 Heating element [0145] 29 Valve [0146] 30 Data line [0147] 31 Housing [0148] 32 Glass fiber [0149] 33 Cell culture [0150] 34 System (particularly biological system)