DE102013200822A1 - Parallel implementation of number of bio-experiments to identify optimal process parameters, comprises e.g. providing disposable bioreactors, setting first and second value, determining parameter vectors and determining result value - Google Patents

Abstract

Parallel implementation of a number of bio-experiments to identify optimal process parameters in a simultaneous minimization of a number of bio-experiments, comprises: e.g. providing a number of disposable bioreactors (102); setting a first value (104) and a second value; determining parameter vectors (106); assigning (110) each specific parameter vector from reduced parameter vector to each group of disposable bioreactors; providing the parameter vector component values in a control experiment unit; filling disposable bioreactors with raw materials; and determining a result value. Parallel implementation of a number of bio-experiments to identify optimal process parameters in a simultaneous minimization of a number of bio-experiments, comprises: providing a number of disposable bioreactors (102); setting a first value (104) and a second value for each one of parameters for performing the respective bio-experiments in disposable bioreactors; determining parameter vectors (106) whose components are respectively the predetermined first values and second values such that combinations of each of the first values and second values are respectively provided in a thus formed vectors of parameters, and the set of parameter vectors is a parameter vector group; reducing the number of parameter vectors (108) of the parameter vector set based on a comparison of each specific parameter vector with existing specific parameter vectors for each of which a measurement result of a system based on the specific parameter vector equivalent to bio-experiments exists, such that a reduced parameter vector group is formed from the total parameter vectors; assigning (110) each specific parameter vector from the reduced parameter vector to each group of disposable bioreactors; providing the parameter vector component values in a control experiment unit; filling of disposable bioreactors with raw materials for the bio-experiments; controlling by the experiment control unit which is specific for each disposable bioreactor values of the parameter vectors by detectors on each disposable bioreactor and actuators for the values of the parameter vectors; measuring the disposable bioreactor-specific measurement results of the bio-experiments; and determining a result value of the components of a specific parameter vector based on the measured bioreactor specific measurement results and the corresponding specific parameter vector values, and the existing specific parameter vectors and associated measurement results, such that a minimum number of experiments are needed for the determination of optimal specific process parameters. Independent claims are also included for: (1) a bio-experiment control system for parallel implementation of a number of organic experiments in many disposable bioreactors for the determination of optimal process parameters in a simultaneous minimization of the number of bio-experiments, comprising an interface component for receiving a first value and a second value, a combination module which is adapted for determination of specific parameter vectors whose components are respectively the predetermined first values and second values, reduction module that is adapted for reducing the number of vectors of parameters of the parameter vector group, an assignment module adapted to assign a respective specific parameter vector from the reduced parameter vector group to disposable bioreactor, a transmission module, which is adapted to provide the parameter vector component values based on results of the allocation module to a experiment control unit, a control module adapted to control the specific values for each disposable bioreactor of parameter vectors by the experiment control unit, a measurement module that is adapted for measuring disposable bioreactor-specific measurement results of the bio-experiments, and a calculation module adapted for determining a result value of the components of a specific parameter vector based on the measured bioreactor specific measurement results and the corresponding specific parameter vector values, and the existing parameter vectors and associated measurement results; (2) a computer system comprising the bio-experiment control system (400) for parallel implementation of a number of bio-experiments; and (3) a data processing program for controlling a parallel implementation of a number of bio-experiments, comprising software code portions capable of implementing the above method when the computer program is run on a data processing system; and (4) a computer program product for controlling a parallel implementation of bio-experiments stored on a computer-readable medium, comprising computer-processable program means for causing a computer to perform the above method when the program means are executed on the computer.

Description

The invention relates to a method for carrying out a plurality of bioexperiments in parallel, to a bioexperiment control system for carrying out a plurality of bioexperiments in parallel, and to a computer system.

Today, bioreactors are used in many areas of pharmacy and experimental biochemistry, providing an experimental environment for bioprocessing applications that allow biotechnological processes in a given material system to be designed, developed and tested for microbiological processes, and for transferring the process to a technical scale enable time-saving and effective. For this purpose, one-way bioreactors are increasingly being used, which have the advantage that they do not have to be completely cleaned after each test run. Bioreactors for experimental environments are usually much smaller in size than bioreactors for productive use. In any case, use on a laboratory scale requires many small, easy-to-use bioreactors, which make a high number of experiments easily feasible. Due to an increasing number of influenceable process parameters, the number of necessary experiments also increases disproportionately, so that even with the use of disposable bioreactors considerable costs and a lot of time - despite a use of "single-use bioreactors" - arise To determine the best possible set of process parameters, which is determined by predefined results of the bioreactions.

The invention is therefore based on the technical task of providing an easy-to-handle, universal and cost-effective process for bioexperiments, which manages with a small number of experiments in order to determine an optimized set of process parameters, so that these are based on large-scale Have plants transferred. This applies in particular to the development of discontinuous and continuous biotechnological processes.

The aim of such bioexperiments may be to increase the biomass concentration or product formation in the bioreactor as well as to integrate and couple work-up steps in or to the bioreactor. The biotechnological processes may take place under aerobic or anaerobic conditions, sterile or non-sterile, in one or more stages of the process. The bioprocess engineering design of the bioreactor ensures a uniform distribution of cells and nutrients over the entire cultivation volume, adequate supply of biomass with nutrients, the removal or supply of heat, the dissipation of energy, high transport coefficients, variation of liquid phase mixing, defined guiding of material flows , etc., so that a safe scale-up of the bioprocess is possible.

Brief description of the invention

The above object is solved by the subject matters of the independent claims. Advantageous embodiments of the present invention are described by the dependent claims.

According to a first aspect of the invention, a method is presented for performing a plurality of bioexperiments in parallel to determine optimal process parameters while simultaneously minimizing a number of bioexperiments. The method comprises providing a plurality of disposable bioreactors, setting a first value and a second value for each of a plurality of parameters for performing the bioexperiments in each one of the disposable bioreactors of the plurality of disposable bioreactors and determining parameter vectors whose components are respectively the predetermined first values and second values such that a plurality of combinations of the respective first values and second values are respectively present once in a resultant ensemble of the parameter vectors, and wherein the entirety of the parameter vectors is one Parameter vector group forms.

The method further comprises reducing the number of parameter vectors of the parameter vector group, based on a comparison of each specific parameter vector with existing concrete parameter vectors, for each of which a measurement result of a comparable bioexperiment based on the specific parameter vector exists, such that a reduced parameter vector group from the Entirety of the parameter vectors arises. In addition, each of a specific parameter vector is assigned from the reduced parameter vector group to a one-way bioreactor of the plurality of single-use bioreactors and the parameter vector component values are provided to an experiment control unit.

Furthermore, the method comprises: filling the disposable bioreactors with starting materials for the bioexperiments, controlling by means of the experimental control unit the values of the parameter vectors specific to each disposable bioreactor by means of detectors at each disposable bioreactor and actuators for the values of the parameter vectors Measuring one-way bioreactor-specific measurement results of the bioexperiments, and determining result values for the components of a specific parameter vector based on the measured one-way bioreactor-specific measurement results and the associated concrete parameter vector values as well as the existing concrete parameter vectors and associated measurement results, so that a minimal number of experiments is needed to determine optimal concrete process parameter values.

According to another aspect of the invention, a bioexperiment control system for performing a plurality of bioexperiments in a plurality of bioexperiments in parallel to determine optimal process parameters while minimizing the number of bioexperiments is presented. The bioexperiment control system comprises an interface component for receiving a first value and a second value for a respective one of a plurality of parameters for carrying out the bioexperiments in a respective one-way bioreactor from the plurality of disposable bioreactors, and a combination module is adapted to determine concrete parameter vectors whose components are respectively the predetermined first values and second values, such that a plurality of combinations of the respective first values and second values are respectively present once in an ensuing ensemble of the parameter vectors, and wherein the entirety of the Parameter vectors forms a parameter vector group. Furthermore, the bioexperiment control system has a reduction module which is adapted to reduce the number of parameter vectors of the parameter vector group based on a comparison of each specific parameter vector with already existing concrete parameter vectors for which a measurement result of a bioexperiment based on the specific parameter vector exists, such that a reduced parameter vector group arises from the totality of the parameter vectors.

The bioexperiment control system further comprises: an assignment module adapted to assign each of a particular parameter vector from the reduced parameter vector group to a single-use bioreactor of the plurality of one-way bioreactors; a transmit module adapted to provide the parameter vector component values to an experiment control unit and a control module adapted to be controlled by the experimental control unit of the values of the parameter vectors specific to each disposable bioreactor by means of detectors at each disposable bioreactor and actuators for the values of the parameter vectors.

In addition, the bioexperiment control system comprises: a measurement module adapted for measuring one-way bioreactor-specific measurement results of the bioexperiments, and a calculation module adapted to determine result values for the components of a parameter vector based on the measured one-way bioreactor-specific ones Measurement results and the associated specific parameter vector values and existing parameter vectors and associated measurement result values for the components of a parameter vector, so that a minimum number of experiments is needed.

It should be noted that optimal process parameters can be optimized experimentally for different aspects. For example, "optimal" may mean that a maximum amount of bioreactor has been produced, the shortest possible time has been claimed for a gradient of biomass production to be as large as possible, or that, for example, the consumption of raw materials is as minimal as possible. Combinations of these or other conditions are also possible.

The disposable bioreactors in particular have a plurality of closable openings. They can also be used to record measurement or control instruments for bioexperiments.

"Existing concrete parameter vectors" can mean parameter vectors with concrete values that are stored, for example, in a data storage system-such as a database-together with the associated measurement results. They do not have to belong to the current set of bioexperiments, but related experiments may have already been performed earlier. Specific parameter vectors can be understood to mean parameter vectors with concrete values for the parameters of the parameter vector.

Detailed description of the invention

It should also be noted that a parallel execution of bioexperiments can also be understood as a parallel-sequential execution of the experiments. This means that one part of the bioexperiments is performed in parallel with one another, while another set of experiments can be performed with a time delay to a first set of bioexperiments.

The following terms and expressions are used in this document:
"Bioexperiment" is understood to mean a test arrangement for carrying out and investigating reactions of starting materials or educts and resultants or products based on biology. In doing so, biological resultants are often produced with the aid of bacteria, animal or human (stem) cells or other living organisms as the resulting biomass.

By "disposable bioreactor" bioreactor containers can be understood to carry out bioexperiments. Typically, process parameters of the bioexperiments can both be measured and controlled. Disposable bioreactors can be made of plastic, which can be transparent. There may be a plurality of closable openings through which starting materials (educts) can be filled, or measuring or control instruments can be introduced. Disposable bioreactors may be intended for single use as a vessel for a bioexperiment. Typically, cleaning and reuse is not required or technically prevented for another experiment.

"Rules" differs from "Control" in that a setpoint is compared with a currently measured actual value for a parameter during control, and corresponding control signals are generated in order to allow an adjustment. During control, only a control value is generated which generates the desired target value for a parameter based on historical experience and / or measured values.

"Values of parameters" designate explicit numerical information regarding the parameters. For example, each may be a lower value or an upper value for the respective parameter. These can also be referred to as first and second values and represent framework parameters for a bioexperiment with respect to the parameters. Suitable parameters are, for example, starting material concentrations of different bioexperiment starting materials, temperature, oxygen partial pressure, pH, glucose concentration, stirring speed and so forth.

The term "plurality of combinations of respective first and second values" may refer to all possible combinations of the values in parameter vectors. This would allow 2 ⁿ combinations, where n would be the number of dimensions or components of the parameter vector. Alternatively, it may also mean a predefined subset of combinations that is required, for example, to ensure statistical relevance of bioexperiment series. It is also possible to work with an increased set of parameter vectors.

"Actuators" can be understood to mean influencing modules for process parameter values. This concerns for example components for a temperature control unit, a stirring speed unit, valves for gassing, pumps for liquid metering in the bioreactor, etc. To actuators can also automatic valves to z. B. downstream outlets of the bioreactor count.

In this context, "controlling" means actively influencing physical parameters within the bioreactor to match a measured parameter value with a predetermined parameter value.

"Measurement results" in the context of this application means determined values that characterize the bioprocess. These values can be measured during or after the experiment. They can also be computationally determined from other measured values and parameter values. The computational determination can be algorithm based.

In contrast to "measurement results", "result values" here mean concrete values for components of a parameter vector, so that the respective bioexperiment can be optimally performed.

The term "parameter midpoint vector" refers to a combination of values of different experimental parameters that can be represented as a vector. All values of the parameter center point vector are within the respective predetermined first and second values of the respective process parameter.

The term "aseptic conditions" may describe specific bioexperiment conditions. These can mean a sterility for the bioexperiment. This means, for example, that no germs can be introduced through the openings of a disposable bioreactor.

By "concrete parameter vector components" is meant specific values for a parameter vector. A concrete parameter vector then gives the bioexperiment parameter values for a bioexperiment. These may for example consist of specific values for the temperature at which the bioexperiment is to proceed, the stirring rate to be used and / or the oxygen partial pressure to be maintained in the bioexperiment. Many other parameters for the bioexperiments are conceivable, as set out elsewhere in this document. A concrete parameter vector thus has exactly as many numerical values as the vector has components.

The method or system described above for carrying out a plurality of bioexperiments in parallel to determine optimum process parameters may have the following advantages.

The method described above allows cost-effective determination of bioexperiment process parameters for optimal results of the bioexperiment. "Optimal" can have several meanings here, as mentioned above. It can be about consuming as little starting material as possible or generating as much target biomass as possible from the bioexperiment. Other meanings are possible. For this purpose, it is not necessary to carry out very extensive test series using the method, which were time consuming and costly to perform. The process optimally exploits existing resources by requiring a small or minimal number of bioexperiments, so that optimized process parameters can be found so that scale-up and, if necessary, implementation of bioprocesses on an industrial scale is economically feasible. The method uses measurement results and parameter vectors of previously performed bioexperiments and performs a comparison with planned bioexperiments, whereby those bioexperiments for which measurement results are already available are no longer performed. The measurement results and parameter vectors can be retrieved from a database. This too contributes to a reduction in the required number of experiments. Thus, the use of disposable bioreactors and an algorithm-based implementation of the required experiments complement each other, so that overall there is a cost-effective and time-saving method of determining suitable process parameters for bioexperiments as efficiently as possible.

Hereinafter, further advantageous embodiments of the method or the Bioexperimentsteuerungssystems will be described.

According to an embodiment of the method, the method may additionally comprise defining at least one parameter midpoint vector, wherein the components are selected such that respective values lie between the respective first value and second value for a respective one of a plurality of experimental parameters. Not only would it be necessary to use the first and second values of the respective parameters as bioexperiment parameters, but also intermediate values of the concrete parameter vectors could be used, from which results can be extracted. Such a combination would require more experiments, but the statistical relevance of the experiments would increase.

According to an advantageous embodiment of the method, the components of the parameter vector may be selected at least as follows: selected from the group consisting of temperature, pH, oxygen partial pressure, carbon dioxide partial pressure, stirring speed, conductivity, pressure, educt concentration - e.g. Glucose concentration, product concentration, supplement concentration and inhibitor concentration. Other parameters are conceivable depending on the type of bioexperiment. The stirring rate or the conductivity can each refer to the contents of the disposable bioreactor. The inhibitor concentration may refer, for example, to a substance added to the contents of the disposable bioreactor during the bioexperiment.

According to a further advantageous embodiment of the method, the components of the parameter vector can at least partially represent or have a time dependency. This makes it possible to set and vary the experimental processes within wide limits. For example, a substance (inhibitor) may be added to the contents of the disposable bioreactor at some point in the experiment to redirect the original course of the bioexperiment. Also in this way the temporal change (gradient) of a manipulated variable can be used as a parameter.

The method of claim 1, wherein in addition to a first value and a second value for the components of the parameter vector, a third value is set for at least one component of the parameter vector, wherein the third value lies between the first value and the second value, whereby the number is increased by concrete parameter vectors of a set of concrete parameter vectors. Such a choice of specific values for bioexperiment parameters can increase the statistical relevance of bioexperiment results. This can reduce the misinterpretation of bioexperiment results and help reduce the cost of the experiment series. This applies even though none of the totality of the concrete parameter vectors represents an optimal result of the bioexperiments and this optimum only results from an algorithm-based determination.

In a further advantageous embodiment of the method, the bioexperiments can be performed in time-graduated subgroups if the number of specific parameter vectors in the reduced parameter vector group is greater than the number of bioreactors available for bioexperiments. The assignment of concrete parameter vectors to the disposable bioreactors may be randomized, so that two concrete Parameter vectors are performed with a first value of a component of the parameter vector and a second value of the same component of the parameter vector in disposable bioreactors at different experimental locations within a test arrangement.

The term "different test sites" can be understood to mean that disposable bioreactors, for example, in batteries of four disposable bioreactors - are summarized - corresponding to four test locations. It should therefore be avoided, each time a bioexperiment for a lower value of a parameter component and the associated upper value in a disposable bioreactor perform delayed, when the disposable bioreactors are in the same place or trial in the battery of disposable bioreactors. Distributed allocation of associated concrete parameter vectors to bioreactor sites in a trial can reduce systematic errors.

The term "staggered in time" can also mean that one subgroup of bioexperiments runs in parallel and another subgroup of bioexperiments runs chronologically after the first subgroup. This procedure can be described as partial-parallel. For a new subgroup of bioexperiments new disposable bioreactors would be used. So it would be necessary only small set-up times between the resulting series of experiments, since no purification steps of the bioreactors would be required. A total number of necessary bioexperiment runs would depend on the number of disposable bioreactors to be operated in parallel.

In a further modified embodiment of the method, each of the time-graduated sub-groups of bio-experiments may each contain a bio-experiment, which is carried out based on a parameter-midpoint vector. In addition, the assignment of concrete parameter vectors to bioreactors can be randomized, so that two concrete parameter vectors are performed with a first value of one component of the parameter vector and a second value of the same component of the parameter vector in one-way bioreactors at different test sites within a test setup. In this way, incorrect measurements in the bioexperiments, which are based on systematic errors, can be better detected and eliminated.

In an alternative embodiment of the method, a first group of bioexperiments may be performed at a first location and a second group of bioexperiments at a second location, wherein the specific parameter vectors are each selected from the reduced parameter vector and an assignment from concrete parameter vectors to disposable bioreactors is randomized. This approach can be useful if there is not enough experimental space or measuring equipment for disposable bioreactors or other restrictions in one place, such as a laboratory. In this case, the values of the concrete parameter vectors from the reduced parameter vector group would be transferred to a geographically distant laboratory with further disposable bioreactor experiment sites, if necessary electronically. The geographically distant laboratory may be located in the same building as the experimental setup for the first group of bioexperiments. Alternatively, any other arbitrary location - such as in another city, another country or on another continent - conceivable. This procedure can optimally utilize all available resources of a company or a group of companies at different locations.

It is also conceivable to perform a temporal and a local nesting of the bioexperiments. Time-shifted subgroups of bioexperiments can be carried out at different laboratory locations. If, for example, 16 bio-experiments were to be carried out and only four test sites each for a single-use bioreactor were present at each laboratory site, chronologically staggered bioexperiments could be carried out at each laboratory site. Four subgroups of bioexperiments would be carried out - two groups of four at each laboratory site.

In a further modified embodiment of the method, the first group of bioexperiments and the second group of bioexperiments, each of which may be performed at different locations, contain a bioexperiment performed based on a parameter midpoint vector. As already mentioned in the time-staggered bioexperiments, it is also possible to better recognize and eliminate erroneous results that are based on systematic errors.

According to a further embodiment of the method, two consecutive bioexperiments with two different concrete parameter vectors from the reduced parameter vector group may be successively executable in the same one-way biorector. This can be particularly useful in bio-experiments with continuous bioprocesses. In this way, disposable bioreactorrhea times can be avoided for a second set of bioexperiments. In addition, a disposable bioreactor can be used for more than one bioexperiment. A concrete execution of the procedure This embodiment can be done by changing parameter values of the parameter vectors during a cultivation so that a first concrete parameter vector is converted into a second concrete parameter vector of the parameter vector group or first concrete parameter vector value into a second concrete parameter vector value and the first and second measurements result associated with respective parameter vectors.

According to an advantageous embodiment of the method, detectors and actuators can be at least partially introduced and operated via openings in corresponding bioreactors under aseptic conditions. The aseptic conditions ensure that the bioexperiment results are not falsified. For example, the process values such as pH, dissolved oxygen and the temperature within the bioreactor can be measured from the outside without providing openings in the disposable bioreactor. Concentrations of substances within the contents of the respective bioreactor can often only be measured by contact of a sensor with the medium. In this case, openings for introducing sensors into the disposable bioreactor are advantageous.

According to a further embodiment of the method, in each case a representation of the measured bioreactor-specific results and a representation of the associated concrete parameter vector values can be electronically stored. This can be done using a database or other storage mechanism. A database has the advantage that the parameter vectors and measurement results can easily be found, extracted and easily used to form the reduced parameter vector group. In addition, statistical evaluations of the bioexperiments and associated results for planning new experiments are more easily possible.

The inventive system may be implemented in whole or in part as a data processing program or computer program or program element. For this purpose, it may be stored in whole or in part on a computer-readable medium.

For the purposes of this document, the mention of such a computer program is synonymous with the notion of a program element, a computer program product, and / or a computer-readable medium containing instructions for controlling a computer system to suit the operation of a system or method to coordinate to achieve the effects associated with the method according to the invention.

Any combination of a computer-readable medium or multiple computer-readable media may be used. The computer readable medium may be a medium having a computer readable signal or a computer readable storage medium. For example, a computer-readable storage medium may be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, device, or any suitable combination of the foregoing. Other specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection to one or more cables, a portable computer disk, a hard disk, Random Access Memory (RAM), Read Only Memory (ROM). only memory), an erasable programmable read only memory (EPROM or flash memory), a glass fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device or each suitable combination of the preceding. In the context of this document, a computer-readable storage medium may be any tangible medium that may store a program for use by or in connection with an instruction execution system, an instruction execution device, or an instruction execution device.

The computer readable signal media may include a forwarded data signal having computer readable program code therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including but not limited to, electromagnetic, optical, or any suitable combination of the foregoing forms. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicate, forward, or transport a program for use or in connection with an instruction execution system, an instruction execution device, or an instruction execution device.

Program code contained on a computer readable medium may be transmitted with an appropriate medium including, but not limited to, radio, cable, fiber, HF, or any suitable combination of the foregoing.

Computer program code for performing the operations for aspects of the present invention may be written in any combination of one or more languages, including Object-oriented programming languages such as Java, Smalltalk, C ++ or similar and conventional programming languages, such as the programming language "C" or similar programming languages. The program code can be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be to an external network Computer (for example, over the Internet with an internet service provider).

It should be noted that embodiments of the invention have been described with reference to different subject matters. In particular, some embodiments of the invention are described with apparatus claims and other embodiments of the invention with method claims. However, it will be readily apparent to those skilled in the art upon reading this application that, unless explicitly stated otherwise, in addition to a combination of features associated with a type of subject matter, any combination of features that may result in different types of features is also possible Subject matters belong.

Further advantages and features of the present invention will become apparent from the following exemplary description of presently preferred embodiments. The individual figures of the drawing of this application are merely to be regarded as schematic and not to scale.

Brief description of the figures

1 shows an example of a block diagram of the presented method for performing a plurality of bioexperiments in parallel.

2 shows an exemplary schematic embodiment of a disposable bioreactor.

3 shows an example of an assignment of concrete parameter vectors to different disposable bioreactors.

4 shows an embodiment of a block diagram of a bioexperiment control system for performing a plurality of bioexperiments in parallel.

5 shows a computer system with the bioexperiment control system according to the invention.

Description of exemplary embodiments

It should be noted that features or components of different embodiments, which are the same or at least functionally identical to the corresponding features or components of the embodiment, are provided with the same reference numerals or with a different reference numeral, which is only in its first digit of the reference number of a (functionally) corresponding feature or a (functional) corresponding component. In order to avoid unnecessary repetitions, features or components already explained on the basis of a previously described embodiment will not be explained in detail later.

It should also be noted that the embodiments described below represent only a limited selection of possible embodiments of the invention. In particular, it is possible to suitably combine the features of individual embodiments with one another, so that a multiplicity of different embodiments are to be regarded as obviously disclosed to the person skilled in the art with the embodiment variants explicitly illustrated here.

1 shows an embodiment of a block diagram of the method 100 to perform a plurality of bioexperiments in parallel to determine optimal process parameters while minimizing a number of bioexperiments.

The method has a number of elements: provision 102 a plurality of disposable bioreactors, setting 104 and determining a first value and a second value for each of a plurality of parameters for performing the bioexperiments in each one-way bioreactor of the plurality of disposable bioreactors 106 In particular receiving, for example, via an input medium such as a keyboard / screen combination, concrete parameter vectors whose components are respectively the fixed first values and second values, such that a plurality of combinations of the respective first values and second values are each once in an ensemble thus formed of the parameter vectors, and wherein the totality of the parameter vectors forms a parameter vector group.

If all possible combinations of first and second values were used for the formation of the concrete parameter vectors, the totality of the concrete parameter vectors would be 2 ⁿ , where n is the number of different components of the parameter vector would. Alternatively, a defined subset of the entirety can be determined. The statistical significance of the totality of the bioexperiments can be used.

Furthermore, the method has a reduction 108 the number of parameter vectors of the parameter vector group. The reduction is based on a comparison of each concrete parameter vector with already existing concrete parameter vectors, for each of which a measurement result of a bioexperiment based on the concrete parameter vector exists. These existing or historical values may have been stored in electronic form, e.g. B. in a database for Bioexperimentparameter and associated measurement results. So they are easily retrievable and usable for comparisons.

This reduction results in a reduced group of concrete parameter vectors from the totality of the parameter vectors, which has fewer than 2 ⁿ concrete parameter vectors. This naturally reduces the number of experiments required. Those parameter vectors for which measurement results of the bioexperiment already exist do not have to be performed again.

Subsequently, an assign takes place 110 each of a specific parameter vector from the reduced parameter vector group to a single-use bioreactor of the plurality of disposable bioreactors instead. However, this does not automatically mean that there is a free disposable bioreactor for each specific parameter vector. Rather, the number of disposable bioreactors can be limited in number, so that a selection must be made in the allocation. In order to carry out all bioexperiments, a summary in experiment groups, which are processed one after the other, is necessary. The limitations may also arise from the number of control systems for performing the bioexperiments.

Subsequently, a provision is made 112 the parameter vector component values are performed on one or each an experimental control unit. Experimental control units can be grouped together.

The bioreactors are filled with starting materials or educts for each bioexperiment, 114 , The quantities can be described by parameter component values or managed externally. By means of the experimental control unit, the values of the specific parameter vectors specific to each disposable bioreactor are detected by means of detectors - "an" can here also mean "in" - each single-use bioreactor and actuators are controlled for the values of the parameter vectors, 116 , It can also be a control process with individual parameters. In this way it is ensured that the respective parameter values for each disposable bioreactor are observed.

Finally, one-way bioreactor-specific measurement results of the bioexperiments are measured, 118 , The measurement results can occur in time series; it can be measured directly or samples can be taken from the disposable bioreactor at defined time intervals. The samples can be taken from the top of the bioreactor. Alternatively, a sample may be taken via an outlet at the lower end of the disposable bioreactor and a solenoid valve and either measured manually or analyzed via an automated measuring system. So or with the help of a computational algorithm, the specific result value can be determined.

In a further step 120 Result values for the components of a parameter vector can be determined based on the measured bioreactor-specific measurement results and the associated specific parameter vector values as well as already existing parameter vectors and associated measurement result values for the components of a parameter vector. The result values describe optimal concrete parameter values. The different meaning variants of "optimal" have already been discussed above, for example, generating a maximum of product biomass, a minimum of raw material consumption, etc. The determination takes place here arithmetically and algorithm-based. The algorithm can be adjusted differently depending on the type of bioexperiment. The above-mentioned reduction of the number of parameter vectors and a combination of the parameter vectors with the results ensures that only a minimum number of experiments is needed to determine the optimal process parameters.

2 shows a schematically illustrated embodiment of a disposable bioreactor 200 , It typically has a volume of several liters. However, a size restriction is neither down nor up. As a material plastic comes into consideration. The disposable bioreactor has a lid at the top 206 on, the one or more, completely or partially closable openings 204 for filling and / or measuring. In addition, are sensors 202 shown schematically. Not shown is a lower outlet, which may be closed with a solenoid valve, for example, to sample biomass in the disposable bioreactor 200 refer to.

3 shows an example of an assignment 336 of concrete parameter vectors 302 . 304 , ..., 316 to various disposable bioreactors. In the parameter vector 302 are exemplified T for temperature, pO2 for oxygen partial pressure, k _Gl for glucose concentration and U for stirring speed. Others already mentioned or more than those under reference numbers 302 illustrated parameter vector components are typical of real experimental setups. The parameter vector 302 is shown as an abstract vector with "T", "pO2", "k _GL " and "U". As a concrete parameter vector, however, he has concrete values, such. B. "37" ° C for "T", "20" revolutions / minute for "U", etc.

3 also shows two groups of disposable bioreactors: subgroup 1, consisting of disposable bioreactors 320 . 322 . 324 . 326 and subgroup 2, consisting of the disposable bioreactors 328 . 330 . 332 . 334 , Each disposable bioreactor can have its own controller to ensure compliance with the process parameters. Alternatively, subgroups of disposable bioreactors may be controlled in groups by one group controller each.

As already mentioned above, the first subgroup and the second subgroup of disposable bioreactors can be constructed at different sites or laboratories. In this case, spatially separate control systems may also be provided. Each subgroup of disposable bioreactors can be controlled by a common module 338 - shown here only for subgroup 2 - be summarized mechanically and / or control technology.

In the event that only one subgroup - z. B. subgroup 1, consisting of the disposable bioreactors 320 to 326 , were available for experiments, but on the other hand for all concrete parameter vectors shown 302 to 316 Bioexperiment results were to be determined, the concrete parameter vectors in time-shifted groups can be assigned to the disposable bioreactor positions available. However, every single trial would use a new disposable bioreactor.

4 shows an embodiment of a block diagram of the bioexperiment control system 400 to carry out a plurality of bioexperiments in parallel.

Via an interface component 402 For example, a first value and a second value for each of a plurality of parameters for performing the bioexperiments in each one of the one-way bioreactors from the plurality of bioreactors can be made available to the system. The interface component can be, for example, a user interface by means of a screen, knobs for setting or also an interface to a memory system so that the values of the parameter components can be called up.

A combination module 404 is adapted so that it is designed to determine specific parameter vectors whose components are respectively the specified first values and second values. In this case, it is combined such that parameter vectors having different combinations of different parameter vector values with respective first and second values would each occur once in the ensuing entirety of the parameter vectors. If all combinations were used, 2 ⁿ concrete parameter vectors would be created. In the event that a parameter midpoint vector is added, a total of 2 ⁿ + 1 experiments would be required to model all combinations in an overall experiment. This can be very time consuming and costly.

To avoid this circumstance, the group of possible parameter vectors can be reduced. It is also possible to make use of historical bioexperiments. A reduction module 408 , is for reducing the number of parameter vectors of the parameter vector group, based on a comparison of each concrete parameter vector with existing concrete parameter vectors, for each of which a measurement result of a comparable bioexperiment based on the specific parameter vector - e.g. B. in a database - exists, adapted so that a reduced parameter vector group from the totality of the parameter vectors arises. The historical values can be stored in a memory component 420 be saved.

An assignment module 410 can each assign a specific parameter vector from the reduced parameter vector group to a single-use bioreactor from the plurality of disposable bioreactors, as already described with reference to FIG 3 was discussed.

A transmission module 412 may provide the necessary control values of the parameter vector component values based on results of the assignment module to a control module 414 to transfer. The control module 414 can with the experimental setup, which in this case four disposable bioreactors 322 . 324 . 326 . 328 , Module 338 and optionally other components for controlling bioexperiments - such as one or more experimental control units (not shown). The Sebdemodul 412 may also transmit the necessary control values of the parameter vector component values to other remote sites or laboratories.

A control module 414 That's about the connection 420 may be connected to the experimental setup or one or more experimental control units (not shown), by means of the experimental control unit (s), can control the values of the parameter vectors specific to each disposable bioreactor by means of detectors on each disposable bioreactor and actuators for the values of the parameter vectors . regulate. Depending on the experimental setup, ie even at remote laboratories, at least one control module 414 to be available.

The control module 414 For each controlled disposable bioreactor, it may have its own sub-control unit, which occupies a particular place within a battery of biorecoder stands in the common module 338 assigned. If a sub-control unit measures inaccurately, has a systematic measurement error, or has associated probes or actuators with perhaps too large tolerances, a suitable assignment - e.g. For example, randomized assignment - provide specific parameter vectors for the extraction of errors and error sources.

By means of a measuring module 416 For example, one-way bioreactor-specific measurement results can be measured - as described above - of the bioexperiments. Here, measuring instruments or probes can be inserted through the openings in the respective disposable bioreactor. One or more measuring modules may be present per laboratory site. In the case of spatially distributed bioexperiments, the measurement module can also be set up, its measurement results to a calculation module 418 to transfer.

The calculation module 418 can determine result values for the components of a specific parameter vector, based on the measured bioreactor-specific measurement results and the associated concrete parameter vector values as well as the already existing parameter vectors and associated measurement results. These can turn in the memory component 420 get saved. In this way, an optimal concrete process parameter vector can be determined by means of a suitable small, limited possibly minimal number of experiments. The calculation can be done by means of the following mathematical mapping: X _opt = F (X ₁ , X ₂ , ... X _n , Y), where X _{n is} a concrete parameter vector consisting of individual components X _{n, 1} , X _{n, 2} ,..., X _{n, m} . Where m is the number of dimensions of the parameter vector. Y is the result vector of the dimension n. The optimal parameter _vector X _opt can be obtained by mathematical methods such. B. calculate the regression analysis.

Embodiments of the invention may be practiced with virtually any type of computer regardless of whether the platform is suitable for storing and / or executing the program code. As in 5 can be exemplified, a computer system 500 one or more processors 502 each with one or more cores per processor, associated memory elements 504 , an internal storage device 506 (eg, a hard disk, an optical drive such as a CD drive, or a DVD drive a flash memory, etc.) and a variety of other elements and functional units typical of today's computer systems. The memory elements 504 can a main memory - z. As a random access memory (RAM) - have, which is used during a current execution of program code. In addition, a cache memory may be present, which serves as a temporary memory for at least part of the program code and / or data. This allows the number of accesses to a permanent storage medium or an external long-term storage 516 to reduce. Elements within the computer system 500 can through a bus system 518 be connected to appropriate adapters. Additionally, the bioexperiment control system 400 for carrying out a plurality of bioexperiments in parallel with the bus system 518 be connected. In this case, subcomponents of the Bioexperimentsteuerungssystems or the computer 500 - such as memory components or controls - are shared. Alternatively, the bioexperiment control system 400 also via another interface with the computer 500 be connected.

The computer system 500 can also input elements such as a keyboard 508 , a pointing device such as a computer mouse 512 or a microphone / speaker combination (not shown). In addition, the computer system 500 Output devices such as a monitor or screen 512 (For example, a liquid crystal monitor, a plasma screen, an LED display unit (LED, OLED), a CRT monitor). The computer system 500 can also connect to a network (for example, a Local Area Network (LAN) or Wide Area Network (WAN) such as the Internet or another type of network such as a wireless network) through a network adapter 514 be connected. This allows connection to other computer systems, a storage networking system, etc. One skilled in the art will appreciate that there are many different types of computer systems. The aforementioned input and output devices can also have other shapes. Generally speaking should the computer system 500 at least the processing, input and / or output systems that are required to meet embodiments of the invention.

The person skilled in the art also knows that one or more elements of said computer system 500 placed in a remote location and with the other elements of the computer system 500 can be connected via a network. Moreover, embodiments of the invention may be implemented as a distributed system having a plurality of nodes, with one part of the invention being located on another node within the distributed system. In one embodiment, a node corresponds to a computer system. Alternatively, the node may also consist of a processor and associated physical memory. The node may also correspond to a processor having a memory system designed for multiple access or a mobile device.

In addition, software instructions for carrying out embodiments of the invention may be stored on a computer-readable medium such as a CD, a floppy disk, a tape, or any other computer-readable storage medium.

The in the computer 500 The hardware elements shown are not to be considered exhaustive, but are representative of the emphasis on essential components required by the present invention.

The flowchart and block diagrams in the figures (FIG. 1) illustrate the architecture, functionality, and operation of the possible implementations of the systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowcharts or in the block diagrams may represent a module, segment, or code section having one or more executable instructions for implementing the specified logical function (s). It should also be noted that in some alternative implementations, the functions specified in the block may not occur in the order shown in the figures. For example, depending on the functionality involved, two consecutive blocks may be executed substantially simultaneously, or blocks may sometimes be executed in the reverse order. It should also be noted that each block in the block diagram and / or flowchart illustrations and the combinations of blocks in the block diagram and / or flowchart illustrations are implemented by specialized hardware-based systems that perform the specified functions or operations, or combinations of specialized hardware and computer instructions can.

The terminology used herein is for the purpose of describing only particular embodiments and is not intended to limit the invention. As used herein, the singular forms "a," "an," and "the," "the" are intended to include plurals, unless the context clearly dictates otherwise. It should be understood that the term "comprising" or "comprising" when used in this specification is used to indicate the presence of specified features, integers, steps, operations, elements and / or components, but not the presence or absence thereof excludes adding one or more features, one or more integers, one or more steps, one or more operations, one or more elements, one or more components, and / or groups thereof.

The associated structures, materials, acts, and equivalents of all means or steps plus functional elements in the following claims are intended to encompass any structure, material, or act to perform the function in combination with other claimed elements as specifically claimed to perform. The description of the various embodiments of the present invention has been presented for purposes of illustration and description. It is not intended, however, to be exhaustive or limited to the disclosed form of the invention. Many changes and variations will be apparent to those skilled in the art without departing from the scope and spirit of the invention. The embodiments have been chosen and described in order to best explain the principles of the invention and of practical application, and to enable others skilled in the art to understand the invention in various embodiments with various changes as appropriate to the particular intended use , to understand.

In summary, the process of performing a plurality of bioexperiments in parallel offers an elegant, effective and cost-effective way of finding optimal experimental parameters from a large number of possible parameter value combinations. This requires only a limited number of actual trials. Historical information regarding comparable experiments may be included in the evaluation so that algorithm based on a set of matching parameter component values may be determined. Restrictions in availability - in terms of space or time - of disposable bioreactors or their locations in experimental setups can also be taken into account.

Claims (16)

Procedure ( 100 ) for carrying out a plurality of bioexperiments in parallel to determine optimal process parameters while simultaneously minimizing a number of bioexperiments, the method ( 100 ): - provision ( 102 ) a plurality of disposable bioreactors ( 200 ; 320 . 322 , ... 334 ), - Establish ( 104 ) of a first value and a second value for a respective one of a plurality of parameters for carrying out the bioexperiments in in each case one of the disposable bioreactors ( 200 ; 320 . 322 , ... 334 ) from the majority of disposable bioreactors, - determining ( 106 ) of parameter vectors ( 302 . 304 , ..., 316 ) whose components are respectively the predetermined first values and second values, such that a plurality of combinations of the respective first values and second values are respectively present once in an ensemble of the parameter vectors thus formed, and wherein the set of the parameter vectors constitutes a parameter vector group; To reduce ( 108 ) the number of parameter vectors ( 302 . 304 , ..., 316 ) of the parameter vector group based on a comparison of each concrete parameter vector ( 302 . 304 , ..., 316 ) exists with already existing concrete parameter vectors for which in each case a measurement result of a comparable bioexperiment based on the concrete parameter vector exists, so that a reduced parameter vector group arises from the totality of the parameter vectors, - assign ( 110 ) each of a concrete parameter vector ( 302 . 304 , ..., 316 ) from the reduced parameter vector group to a single-use bioreactor ( 200 ; 320 . 322 , ... 334 ) from the majority of disposable bioreactors, - providing ( 112 ) of the parameter vector component values to an experiment control unit, - filling ( 114 ) of disposable bioreactors ( 200 ; 320 . 322 , ... 334 ) with starting materials for bioexperiments, - taxes ( 116 ) by means of the experimental control unit of the values of the parameter vectors specific for each single-use bioreactor by means of detectors at each disposable bioreactor ( 200 ; 320 . 322 , ..., 334 ) and actuators ( 202 ) for the values of the parameter vectors ( 302 . 304 , ..., 316 ), - Measure up ( 118 ) of one-way bioreactor-specific measurement results of the bioexperiments and - determination ( 120 ) of result values for the components of a specific parameter vector based on the measured bioreactor-specific measurement results and the associated concrete parameter vector values ( 302 . 304 , ..., 316 ) as well as the already existing concrete parameter vectors and associated measurement results, so that a minimum number of experiments is needed to determine optimal concrete process parameters. Procedure ( 100 ) according to claim 1, further comprising - defining at least one parameter midpoint vector, wherein the components are selected such that respective values lie between the respective first value and second value for each one of a plurality of experimental parameters. Method according to claim 1 or 2, wherein the components of the parameter vector ( 302 . 304 , ..., 316 ) are at least selected from the group consisting of temperature, pH, oxygen partial pressure, carbon dioxide partial pressure, stirring speed, conductivity, pressure, educt concentration, product concentration, supplement concentration, inhibitor concentration. Procedure ( 100 ) according to claim 3, wherein the components of the parameter vector ( 302 . 304 , ..., 316 ) at least partially have a time dependence. Procedure ( 100 ) according to one of the preceding claims, wherein besides a first value and a second value for the components of the specific parameter vector ( 302 . 304 , ..., 316 ) a third value is set for at least one component of the parameter vector, the third value lying between the first value and the second value, whereby the number of concrete parameter vectors ( 302 . 304 , ..., 316 ) of a set of concrete parameter vectors is increased. Procedure ( 100 ) according to one of the preceding claims, wherein, if the number of concrete parameter vectors ( 302 . 304 , ..., 316 ) in the reduced parameter vector group greater than the number of disposable bioreactors available for bioexperiments ( 320 . 322 , ... 334 ), the bioexperiments are carried out in time staggered subgroups, whereby the assignment of concrete parameter vectors ( 302 . 304 , ..., 316 ) to disposable bioreactors ( 320 . 322 , ... 334 ) is randomized such that in each case two concrete parameter vectors having a first value of a component of the parameter vector and a second value of the same component of the parameter vector in disposable bioreactors ( 200 ; 320 . 322 , ... 334 ) are carried out at different test sites within a test arrangement. Procedure ( 100 ) according to claim 6, wherein each of the temporally staggered subgroups of Bioexperiments each containing a bioexperiment performed based on a parameter midpoint vector, wherein bioexperiments with the parameter midpoint vector from the time-graded subgroups in disposable bioreactors ( 200 ; 320 . 322 , ... 334 ) are carried out at different test sites within a test arrangement. Procedure ( 100 ) according to one of claims 2 to 5, wherein a first group of bioexperiments at a first location and a second group of bioexperiments at a second location are performed, wherein the concrete parameter vectors ( 302 . 304 , ..., 316 ) are each selected from the reduced parameter vector and an assignment of concrete parameter vectors ( 302 . 304 , ..., 316 to disposable bioreactors ( 200 ; 320 . 322 , ... 334 ) is randomized. Procedure ( 100 ) according to claim 8, wherein the first group of bioexperiments and the second group of bioexperiments each contain a bioexperiment which is performed based on a parameter midpoint vector. Procedure ( 100 ) according to one of the preceding claims, wherein two consecutive bioexperiments with two different concrete parameter vectors from the reduced parameter vector group are successively executable in the same one-way biorector with the same culture medium and strain. Method according to one of the preceding claims, wherein the detectors and actuators at least partially pass through openings into corresponding one-way bioreactors ( 200 ; 320 . 322 , ... 334 ) are introduced and operated under aseptic conditions. Method according to one of the preceding claims, wherein in each case a representation of the measured bioreactor-specific results and a representation of the associated concrete parameter vector values are electronically stored. Bioexperiment control system ( 400 ) for performing a plurality of bioexperiments in a plurality of disposable bioreactors in parallel ( 200 ; 320 . 322 , ... 334 ) for determining optimal process parameters while simultaneously minimizing the number of bioexperiments, whereby the bioexperiment control system ( 400 ) - an interface component ( 402 ) for receiving a first value and a second value for each one of a plurality of parameters for carrying out the bioexperiments in in each case one of the disposable bioreactors ( 320 . 322 , ..., 334 ) from the majority of bioreactors, - a combination module ( 404 ), which is adapted for the determination of concrete parameter vectors ( 302 . 304 , ..., 316 ), whose components are respectively the fixed first values and second values, so that a plurality of combinations of the respective first values and second values are respectively present once in an ensuing set of the parameter vectors, and wherein the set of the parameter vectors constitutes a parameter vector group, Reduction module ( 408 ) adapted to reduce the number of parameter vectors ( 302 . 304 , ..., 316 ) of the parameter vector group, based on a comparison of each concrete parameter vector ( 302 . 304 , ..., 316 ) with already existing concrete parameter vectors, for each of which a measurement result of a comparable bioexperiment based on the concrete parameter vector exists, so that a reduced parameter vector group arises from the totality of the parameter vectors, - an assignment module ( 410 ), which is adapted for assigning in each case a concrete parameter vector ( 302 . 304 , ..., 316 ) from the reduced parameter vector group to a single-use bioreactor ( 200 ; 320 . 322 , ... 334 ) from the majority of disposable bioreactors, - a transmission module ( 412 ) adapted to provide the parameter vector component values based on results of the assignment module ( 410 ) to an experiment control unit, - a control module ( 414 ) adapted for controlling by means of the experimental control unit the values of the parameter vectors specific to each one-way bioreactor ( 302 . 304 , ..., 316 ) by means of detectors ( 202 ) at each disposable bioreactor ( 200 ; 320 . 322 , ... 334 ) and actuators for the values of the parameter vectors ( 302 . 304 , ..., 316 ), - a measuring module ( 416 ) adapted for measuring one-way bioreactor-specific measurement results of the bioexperiments, and - a calculation module ( 418 ) adapted for determining result values for the components of a specific parameter vector, based on the measured bioreactor-specific measurement results and the associated concrete parameter vector values ( 302 . 304 , ..., 316 ) as well as the already existing parameter vectors and associated measurement results, so that a minimum number of experiments is needed to determine optimal concrete process parameters. Computer system comprising the bioexperiment control system ( 400 ) for carrying out a plurality of bioexperiments in parallel according to claim 13. A data processing program for controlling a parallel execution of a plurality of bioexperiments, the data processing program for execution in a data processing system comprising software code components suitable for Execution of the method according to one of Claims 1 to 12, when the computer program is stored on a data processing system ( 500 ) is performed. A computer program product for controlling parallel execution of a plurality of bioexperiments stored on a computer readable medium, the computer program product comprising computer processable program means comprising a computer ( 500 ) to carry out the method according to one of claims 1 to 12, when the program means on the computer ( 500 ).

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