WO2025204133A1 - Information processing device, operation method for information processing device, and operation program for information processing device - Google Patents

Abstract

This information processing device comprises a processor. By analyzing, using a method independent of dispersion in measurements, the morphology of control waveform data that represents an electrical change corresponding to the pulsation of a cardiomyocyte and that is used for a toxicity evaluation test of a drug candidate substance, the processor determines eligibility of whether or not the control waveform data can be used for the toxicity evaluation test of the drug candidate substance, and presents the determination result of the eligibility.

Description

Information processing device, operating method for information processing device, and operating program for information processing device

The technology disclosed herein relates to an information processing device, an operating method for an information processing device, and an operating program for an information processing device.

In the field of drug discovery, a method using microelectrode arrays (MEAs) has been developed as a method for evaluating toxicity using cardiomyocytes generated from iPS (induced pluripotent stem) cells (see International Publication No. WO 2022/176310). A microelectrode array is an arrangement of multiple microelectrodes, and the microelectrode array is provided at the bottom of each well of a well plate. A well plate with such a microelectrode array provided in each well is called an MEA plate. A sheet of cardiomyocytes is formed at the bottom of each well in contact with the multiple microelectrodes. Each microelectrode outputs waveform data representing the extracellular potential corresponding to the pulsation of the cardiomyocytes as a waveform indicating electrophysiological changes. Toxicity evaluation of a drug candidate substance is performed using drug-treated waveform data obtained by administering the drug candidate substance and control waveform data that is compared with the drug-treated waveform data. Control waveform data is, for example, pre-administration waveform data obtained from cardiomyocytes before administration of a drug candidate substance, and drug-treated waveform data is, for example, post-administration waveform data obtained after administration of a drug candidate substance to the same cardiomyocytes.

In order to use such drug-treated waveform data for toxicity assessment, the control waveform data must have an ideal waveform that indicates a normal beat. If the control waveform data is abnormal, it will be impossible to accurately detect changes caused by the drug candidate substance from the drug-treated waveform data. For this reason, the control waveform data is evaluated for suitability for use in toxicity assessment tests.

Eligibility assessment is currently carried out by human visual sensory evaluation, but due to the enormous amount of data involved, there is a demand for mechanization of this process. WO 2022/176310 describes a method that uses a clustering technique based on a machine learning model to assess eligibility.

However, methods using machine learning models sometimes fail to properly reflect the key points of human visual sensory evaluation.

One embodiment of the technology disclosed herein provides an information processing device, an operating method for the information processing device, and an operating program for the information processing device that can obtain judgment results that are closer to human visual sensory evaluation than conventional methods regarding the suitability of waveform data for use in toxicity evaluation tests.

In order to achieve the above objective, the information processing device disclosed herein is an information processing device equipped with a processor, which analyzes the morphology of control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, using a method that is not dependent on variability between measurements, to determine whether the control waveform data is suitable for use in toxicity evaluation tests, and presents the results of the eligibility determination.

Preferably, the processor analyzes the morphology of the control waveform data in a manner that is independent of variations in both the time from depolarization to repolarization within a beat cycle and the amplitude corresponding to the repolarization.

A method that is not dependent on measurement-to-measurement variability is preferably one that normalizes for time and amplitude relative to the reference waveform data.

It is preferable that the processor excludes from the morphology analysis control waveform data in which at least one of the amplitudes corresponding to depolarization and repolarization does not satisfy a preset condition.

The conditions preferably include a first condition that the absolute value of the amplitude corresponding to depolarization is equal to or greater than a certain value, and a second condition that the amplitude corresponding to repolarization is within a predetermined range.

It is preferable that the analysis items for analyzing the morphology include items set for each interval, with the pulsation cycle divided into multiple intervals.

It is preferable that the items set for each section include items that use multiple approximation curves of different degrees.

Preferably, the processor determines eligibility using at least one of rule-based, template matching, and machine learning techniques.

The control waveform data is preferably waveform data obtained using an MEA plate having multiple electrodes on the bottom and multiple wells in which cardiomyocytes can be placed.

The processor preferably has the ability to indicate whether or not a well can be used for toxicity evaluation testing based on a determination of the suitability of the control waveform data.

The processor preferably uses the drug-treated waveform data acquired after administering the drug candidate substance to the cardiomyocytes to determine whether the well can be used for toxicity evaluation testing.

In addition to the assessment results, it is preferable to present standard waveform data with a standard form that is recognized as being suitable.

The disclosed method for operating an information processing device is a method for operating an information processing device equipped with a processor, in which the processor analyzes the form of control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, to determine whether the control waveform data is suitable for use in toxicity evaluation tests and present the results of the eligibility determination.

The operating program for an information processing device disclosed herein is an operating program for an information processing device equipped with a processor, and causes the processor to execute processing including: determining the suitability of control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, by analyzing the form of the control waveform data, as to whether the control waveform data can be used in toxicity evaluation tests, and presenting the results of the suitability determination.

The information processing device disclosed herein is an information processing device equipped with a processor, which normalizes control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, in terms of the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to repolarization, and presents the normalized control waveform data.

In addition to the normalized control waveform data, it is preferable to present standard waveform data with a standard form that is recognized as being qualified.

The disclosed method for operating an information processing device is a method for operating an information processing device equipped with a processor, in which the processor normalizes control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, for the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to repolarization, and presents the normalized control waveform data.

The operating program for an information processing device disclosed herein is an operating program for an information processing device equipped with a processor, and causes the processor to execute processing including normalizing control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, for the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to repolarization, and presenting the normalized control waveform data.

The technology disclosed herein makes it possible to obtain judgment results on the suitability of waveform data for use in toxicity evaluation tests that are closer to human visual sensory evaluation than conventional methods.

FIG. 1 is a diagram schematically illustrating an electrical function evaluation system. FIG. 2 is a perspective view showing an example of an MEA plate. FIG. 1 is a diagram showing an example of a well. FIG. 1 shows an example of a microelectrode array. FIG. 2 is a block diagram illustrating an example of a hardware configuration of the electrical function evaluation system. FIG. 2 is a block diagram illustrating an example of a functional configuration of the information processing device. FIG. 1 is a diagram showing an example of a myocardial waveform. FIG. 10 is a diagram showing the variability of pre-administration waveform data. FIG. 10 is a diagram showing an example of waveform data output from a microelectrode array. FIG. 10 is a diagram showing an example of waveform data that changes upon administration of a drug candidate substance. FIG. 10 is a diagram showing an example of waveform data in which EAD occurs. FIG. 10 is a diagram showing an example of waveform data in which DAD occurs. FIG. 10 is a diagram showing an example of waveform data in which cardiac arrest occurs. FIG. 10 is a diagram showing an example of normalized pre-administration waveform data. This is a list of analysis items for eligibility determination. FIG. 10 is a diagram showing an example of analysis items based on the morphological analysis viewpoint “1-3.” FIG. 10 is a diagram illustrating an example of a procedure for determining eligibility. FIG. 10 is a diagram showing an example of a display form of the determination result of eligibility determination. FIG. 10 is a diagram showing an example of a screen that displays whether or not a toxicity evaluation test is successful. FIG. 10 is a diagram showing an example of a screen when a toxicity evaluation test is successful. FIG. 10 is a diagram showing an example of a screen displayed when a toxicity evaluation test is not successful. FIG. 10 is a diagram showing an example in which post-administration waveform data is used to determine the success or failure of a toxicity evaluation test. FIG. 10 is a diagram showing a modified example 3. FIG. 10 is a diagram showing a fourth modified example.

Embodiments of the technology disclosed herein will be described below with reference to the drawings.

Figure 1 shows a schematic diagram of an electrical function evaluation system 2 that measures the electrical activity of cells. The electrical function evaluation system 2 shown in Figure 1 is composed of a cell culture device 10 and an information processing device 20. The cell culture device 10 makes it possible to measure waveforms that indicate electrophysiological changes in cells (e.g., myocardial waveforms that indicate the pulsation of cardiomyocytes) while culturing the cells. The cell culture device 10 also controls the culture environment (e.g., temperature, carbon dioxide concentration).

An MEA plate 30 is used for cell culture. The cell culture device 10 is provided with a culture chamber 11 that houses the MEA plate 30. The cell culture device 10 also has a sliding lid 12 for opening and closing the culture chamber 11. The MEA plate 30 is attached to the culture chamber 11 with cells seeded on it. The culture chamber 11 functions as an incubator, allowing cells to be cultured for long periods of time.

In this embodiment, cardiomyocytes created from iPS cells are cultured using the cell culture device 10. The cell culture device 10 also uses a multipoint measurement method to measure the extracellular potential representing the myocardial waveform of the cardiomyocytes seeded on the MEA plate 30, and outputs the waveform data obtained by the measurement to the information processing device 20. The waveform data represents changes in the extracellular potential in response to the pulsation of the cardiomyocytes.

The information processing device 20 is configured as a general-purpose computer such as a personal computer. Software for analyzing waveform data input from the cell culture device 10 is installed in the information processing device 20. The information processing device 20 has a display unit 21 and an input unit 22. The display unit 21 is a display device such as a liquid crystal display or an organic EL (Electro Luminescence) display. The input unit 22 is an input device such as a keyboard, touchpad, or mouse. The information processing device 20 is connected to the cell culture device 10 via a wired or wireless connection. The display unit 21 and input unit 22 may be configured as external devices connected to the information processing device 20.

The information processing device 20 has the function of analyzing the input waveform data and presenting the analysis results to the user. The analysis results are used to evaluate the toxicity of drug candidate substances. Drug candidate substances are substances such as compounds that are drug candidates created during the drug development process. Drug-treated waveform data in which the drug candidate substance is administered and control waveform data that is compared with the drug-treated waveform data can be used to evaluate the cardiotoxicity, which is the effect that the drug candidate substance has on cardiomyocytes, such as the risk of arrhythmia. The information processing device 20 can present features that appear in the waveform data and indicate the risk of arrhythmia, etc., as analysis results.

Control waveform data is, for example, pre-administration waveform data obtained from cardiomyocytes before the administration of a drug candidate substance, and drug-treated waveform data is, for example, post-administration waveform data obtained after the drug candidate substance is administered to the same cardiomyocytes. Alternatively, a negative control group of cardiomyocytes not administered the drug candidate substance and a drug-administered group of cardiomyocytes administered the drug candidate substance may be prepared, and waveform data obtained from the negative control group may be used as control waveform data, and waveform data obtained from the drug-administered group may be used as drug-treated waveform data. In the following, an example will be explained using post-administration waveform data as drug-treated waveform data and pre-administration waveform data as control waveform data.

Figure 2 shows an example of an MEA plate 30. The MEA plate 30 is a multi-well plate in which multiple culture wells (hereinafter simply referred to as wells) 32 are arranged on a substrate 31. The MEA plate 30 shown in Figure 2 has 48 wells 32. Note that the number of wells 32 provided on the MEA plate 30 is not limited to 48, and may be 24, 96, etc.

Figure 3 shows an example of a well 32. The well 32 is a roughly cylindrical container with an opening 33 at the top. Cardiomyocytes are seeded so that they adhere to the bottom 34 of the well 32. The well 32 is filled with a culture solution containing a medium. A microelectrode array 40 (see Figure 4) is provided on the bottom 34 of the well 32; for example, the microelectrode array 40 is embedded in the bottom 34.

Figure 4 shows an example of a microelectrode array 40. The microelectrode array 40 has a plurality of electrodes 41. In the example shown in Figure 4, the microelectrode array 40 has 16 microelectrodes (hereinafter simply referred to as electrodes) 41 arranged in a 4x4 square. The electrodes 41 are exposed at the bottom 34 of the well 32 and come into contact with the seeded cardiomyocytes. Each of the electrodes 41 is connected to a potential measurement circuit 50 (described below) via wiring 42. Below, the electrodes 41 may be referred to as channels CH. The 16 electrodes 41 are also distinguished by being referred to as channels CH1 to CH16.

Figure 5 shows an example of the hardware configuration of the electrical function evaluation system 2. The cell culture device 10 has a culture chamber 11, a potential measurement circuit 50, and a communication I/F (interface) 51. The potential measurement circuit 50 measures the extracellular potential of cardiomyocytes cultured on an MEA plate 30 housed in the cell culture device 10. Specifically, the potential measurement circuit 50 measures the extracellular potential via each electrode 41 of a microelectrode array 40 provided in each well 32. In other words, the potential measurement circuit 50 measures 16 myocardial waveforms for each well 32.

The potential measurement circuit 50 transmits the measured myocardial waveform as waveform data to the information processing device 20 via the communication I/F 51. If the number of wells 32 formed in the MEA plate 30 is 48 and the number of microelectrode arrays 40 provided in each well 32 is 16, 768 pieces of waveform data are transmitted from the potential measurement circuit 50 to the information processing device 20. The measurement time for each waveform data is, for example, several minutes, which is a length that includes several tens of beats of the myocardial waveform. Furthermore, the waveform data is transmitted at timings such as before and after administration of the drug candidate substance. As will be described later, the waveform data is measured while changing the concentration of the drug candidate substance, and therefore, post-administration waveform data for different concentrations is transmitted as post-administration waveform data.

The information processing device 20 includes a processor 23, memory 24, input unit 22, display unit 21, communication I/F 25, and bus 26. The processor 23 is a computer that realizes various functions by reading and processing programs 28 and various data stored in the memory 24. The processor 23 is, for example, a CPU (Central Processing Unit).

The memory 24 is a storage device that stores the program 28 and various data used by the processor 23 when executing processing. The memory 24 includes, for example, RAM (Random Access Memory), ROM (Read Only Memory), or storage. The RAM is, for example, a volatile memory used as a work area for the processor 23. The ROM is, for example, a non-volatile memory that holds the program 28 and various data. The ROM is, for example, a flash memory. The storage is, for example, a large-capacity storage device such as an HDD (Hard Disk Drive) or SSD (Solid State Drive), which stores the OS (Operating System), various data, etc. The memory 24 may be configured as an external device connected to the information processing device 20. The memory 24 also stores reference information 29 used by the processor 23 to analyze waveform data.

FIG. 6 shows an example of the functional configuration of the information processing device 20. The information processing device 20 realizes various functions by having the processor 23 execute processing based on the program 28. These various functions may also be realized by hardware. Note that the program 28 is an example of an "operation program" according to the technology disclosed herein.

The processor 23 functions as a data acquisition unit 60, an analysis unit 61, and an output unit 62. The data acquisition unit 60 performs an acquisition process to acquire waveform data transmitted from the cell culture device 10. As described above, the waveform data transmitted from the cell culture device 10 includes pre-administration waveform data and post-administration waveform data. The analysis unit 61 performs an analysis process on the acquired waveform data. Details of the analysis process will be described later.

The output unit 62 performs output processing to output the analysis results of the analysis unit 61 to the display unit 21. The analysis results are presented to the user through the output processing. The output processing is an example of processing that realizes "presentation" according to the technology of the present disclosure. Note that in this example, the output processing shows an example of outputting to the display unit 21 of the information processing device 20, but the analysis results may also be output to a display device other than the information processing device 20, or the analysis results may be transmitted to another terminal via a network. Presentation of the analysis results can also be realized through such output processing.

FIG. 7 shows an example of a myocardial waveform. FIG. 7(A) shows a myocardial waveform representing the intracellular action potential of myocardial cells, and FIG. 7(B) shows a myocardial waveform representing changes in the extracellular potential of myocardial cells measured using the MEA plate 30. The waveform data acquired by the information processing device 20 is the waveform data of the myocardial waveform in FIG. 7(B). The waveform data of the myocardial waveform representing changes in the extracellular potential shown in FIG. 7(B) is an example of "waveform data representing electrical changes in response to the pulsation of myocardial cells" according to the technology of the present disclosure. The following explanation takes waveform data representing changes in the extracellular potential as an example.

In addition, waveform data of myocardial waveforms that represent changes in action potential may also be used as "waveform data that represent electrical changes in response to the pulsation of cardiomyocytes." When using waveform data that represent changes in action potential, the action potential is measured using the patch clamp method or the like.

As is well known, cardiomyocytes have corresponding ion channels that allow ions such as sodium ions (Na ⁺ ), calcium ions (Ca ²⁺ ), and potassium ions (K ⁺ ) to pass in and out of the cells. When the cell membrane is stimulated, the permeability of the ion channels changes, allowing ions to flow in and out through the ion channels. This causes contraction and expansion of the cardiomyocytes. Contraction and expansion occur periodically, resulting in pulsation. The action potential within the cardiomyocytes changes in response to this pulsation, as shown in Figure 7(A).

Specifically, when the cell membrane of a cardiac muscle cell is not excited, the intracellular potential is maintained at a negative level, while the extracellular potential is positive, resulting in a polarized state between the inside and outside of the cell. When the cell membrane is stimulated, the permeability of the sodium ion (Na ⁺ ) ion channel increases, allowing sodium ions (Na ⁺ ) to flow into the cell. As positive ions flow into the cell, the intracellular potential shifts to a positive state. This marks the beginning of an excited state for cardiac muscle cells. This state is called depolarization, as it transitions in a direction that eliminates the potential difference between the polarized cell and its outside. This change in potential increases the permeability of the calcium ion (Ca ²⁺ ) ion channel, allowing calcium ions (Ca ²⁺ ) to flow into the cell. This maintains a positive intracellular potential for a while. Subsequently, the permeability of the potassium ion (K ⁺ ) ion channel increases, allowing potassium ions (K ⁺ ) to flow out of the cell, returning the intracellular potential to a negative state. This results in polarization again inside and outside the cell. This is called repolarization. Repolarization terminates the excited state of cardiac muscle cells. Cardiomyocytes periodically repeat this excited state, which manifests as a pulsation.

In response to this pulsation, the extracellular potential measured by the MEA plate 30 changes as shown in Figure 7 (B). First, when no action potential is generated in the cardiomyocytes, the extracellular potential maintains a reference potential of approximately "0." When depolarization occurs in the cardiomyocytes, the extracellular potential shows a nearly vertical rise and fall. This is called the first peak P1. The first peak P1 has peaks in both the positive and negative directions. After the first peak P1, the extracellular potential rises sharply to near the reference potential, and then, while the intracellular potential remains positive, the extracellular potential rises gradually while maintaining a potential near the reference potential. Then, when repolarization occurs in the cardiomyocytes, the extracellular potential shows relatively steep rises and falls. The apex of this mountain-shaped waveform that is convex in the positive direction is called the second peak P2.

In Figure 7 (B), FPD is the extracellular potential duration (FPD: Field Potential Duration), and ISI is the interspike interval (ISI: Interspike Interval), which corresponds to the pulsation period. A1 is the amplitude of the first peak P1, and A2 is the amplitude of the second peak P2. These values will vary depending on the state of the cardiomyocytes or various factors at the time of measurement, even under the same measurement conditions.

Furthermore, in Figure 7 (B), SA is the section from the first peak P1 to the second peak P2, and SB is the section after the second peak P2. SA1 to SA3 are sections obtained by further subdividing section SA. SA1 is a section defined by the fixed time it takes for the extracellular potential from the first peak P1 to rise to near the reference potential of "0". SA2 is the section from the end of section SA1 to the point where the extracellular potential begins to rise toward the second peak P2 near the base of the mountain-shaped waveform with the second peak P2 as its apex. SA3 is the section from the end of section SA2 to the second peak P2. The morphological characteristics of each of these sections, such as the slope and shape of the waveform in section SA and the shape of the waveform in section SB, also vary depending on the various factors mentioned above.

Figure 8 shows waveform variation under the same measurement conditions. Figure 8 shows multiple waveform data output from each electrode 41 of the microelectrode array 40 in one well 32. All waveform data represent pre-administration waveform data prior to administration of a drug candidate substance. The pre-administration waveform data shown in Figure 8 are superimposed with the first peak P1 time aligned. As shown in Figure 8, the pre-administration waveform data vary in the time of the second peak P2, resulting in variation in the FPD. There is also variation in the ISI. As a result, in addition to the duration of interval SA (see Figure 7) and interval SB (see Figure 7), there is also variation in the duration of interval SA2 (see Figure 7) and interval SA3 (see Figure 7), which are subdivisions of interval SA. There is also variation in the amplitude A2 of the second peak P2. Note that there is no variation in interval SA1 (see Figure 7), as it is defined by a fixed time from the first peak P1.

In addition to quantitative characteristics such as time and amplitude, morphological characteristics also vary. For example, there is variation in the shape of the extracellular potential waveform in the section SA between the first peak P1 and the second peak P2, and in the section SB after the second peak P2.

Figure 9 shows an example of waveform data output from multiple electrodes 41 included in the microelectrode array 40. Figure 9 shows waveform data corresponding to each of channels CH1 to CH16. The multiple waveform data shown in Figure 8 is, for example, data obtained by superimposing the waveform data for each of channels CH1 to CH16 shown in Figure 9.

Furthermore, the waveforms shown in Figures 7(B) and 8 show the myocardial waveforms before the drug candidate substance is administered, but when the drug candidate substance is administered, the waveform changes depending on the toxicity of the drug candidate substance.

Figure 10 shows the change in waveform when a drug candidate substance is administered to cardiomyocytes. Figure 10 shows pre-administration waveform data before administration and post-administration waveform data after administration superimposed with the time of the first peak P1 aligned. The post-administration waveform data shows multiple post-administration waveform data with different concentrations of the drug candidate substance. The post-administration waveform data shows four types of data when the concentration is changed to four levels: low concentration, medium concentration, high concentration, and ultra-high concentration. The concentrations correspond to the administered amount of the drug candidate substance.

As shown in Figure 10, the waveform data changes not only in quantitative characteristics such as the FPD (see Figure 7) and the amplitude A2 of the second peak P2 (see Figure 7) but also in morphological characteristics before and after administration of the drug candidate substance. For example, in the example shown in Figure 10, the first peak P1 and the second peak P2 appear at the same points before and after administration, but the slope and shape of the waveform in each section SA (see Figure 7) change before and after administration. Furthermore, the quantitative and morphological characteristics of the waveform data also change depending on the concentration of the administered drug candidate substance. In the example shown in Figure 10, the higher the concentration of the drug candidate substance, the longer the FPD and the smaller the amplitude A2 of the second peak P2. Accordingly, the slope and shape of the waveform in section SA between the first peak P1 and the second peak P2 also change. In the example of Figure 10, the length of the FPD changes significantly, particularly at ultra-high drug candidate concentrations, and the slope and shape of the waveform in section SA also change significantly. As a general rule, the higher the concentration, the less sharp the second peak P2 becomes, and the mountain-shaped waveform with the second peak P2 at its apex becomes gentler.

The toxicity assessment of a drug candidate substance is performed by analyzing pre-administration waveform data and multiple post-administration waveform data at different concentrations, as shown in Figure 10, and comparing the analysis results. For example, the FPD (see Figure 7) corresponds to the QT interval (the time from the start of the Q wave to the end of the T wave) in an electrocardiogram, and is therefore used as an indicator of the risk of arrhythmia caused by the administration of a drug candidate substance. A prolonged QT interval indicates the possibility of causing arrhythmia. Based on the FPD, users can assess the cardiotoxicity of a drug candidate substance, which is its toxicity to the heart. In addition to FPD, other cardiotoxicity assessment items include EAD (Early After Depolarization), DAD (Delayed After Depolarization), and cardiac arrest.

As shown in Figure 11, EAD is a phenomenon in which depolarization occurs before the second peak P2, and as shown in Figure 12, DAD is a phenomenon in which depolarization occurs after the second peak P2. Both EAD and DAD appear as abnormal waveforms with negative peaks in the extracellular potential waveform data. Furthermore, as shown in Figure 13(A), in the case of cardiac arrest, signals such as peaks at the time of pulsation are not observed in the extracellular potential waveform data. Figure 13(A) shows a case in which pulsation has completely stopped, and is a typical example of cardiac arrest. In addition to Figure 13(A), a state in which there is some amplitude indicating pulsation but no signals such as peaks are observed may also be evaluated as cardiac arrest, as shown in Figure 13(B). When evaluating both Figure 13(A) and Figure 13(B) as cardiac arrest, cardiac arrest is determined based on the following two features. The first feature (Feature 1 in Figure 13(B)) is that the first peak P1 does not drop much in the negative direction and the absolute value is below a certain value THC. The second feature (feature 2 in Figure 13(B)) is that the second peak P2 cannot be confirmed. By determining the abnormal waveform based on these features, it is possible to evaluate Figure 13(B) as cardiac arrest in addition to Figure 13(A).

In order to conduct such toxicity assessments, the waveform data that is the subject of the toxicity assessment must be suitable for use in toxicity assessment tests. Suitability refers to the properties that control waveform data (in this example, pre-administration waveform data) must possess as waveform data that is compared to assess the toxicity of a drug candidate. As shown in Figure 10, waveform data changes upon administration of a drug candidate, but in order to properly assess this change, the pre-administration waveform data that is compared (an example of control waveform data) must be a waveform that is close to the ideal waveform.

Therefore, the analysis unit 61 performs the following normalization process on all pre-administration waveform data output from the MEA plate 30, and then analyzes the form of the normalized pre-administration waveform data to determine eligibility.

Normalization processing is performed on the time from the first peak P1 to the second peak P2 and the amplitude A2 of the second peak P2. The time from the first peak P1 to the second peak P2 corresponds to the time of section SA (see Figure 7). The time of section SA is also the time of the FPD described above. Normalization of the time of section SA is a process of aligning the time of section SA of each pre-administration waveform data to a constant value. The amplitude A2 of the second peak P2 of each pre-administration waveform data is also normalized by aligning it to a constant value.

Here, performing this normalization process and analyzing the morphology of the normalized pre-administration waveform data is an example of "analyzing the morphology of control waveform data in a manner that is independent of variations in both the time from depolarization to repolarization in the pulsatile cycle and the amplitude corresponding to repolarization" according to the technology disclosed herein.

As mentioned above, the first peak P1 corresponds to the depolarization of cardiomyocytes, the second peak P2 corresponds to the repolarization of cardiomyocytes, and the time from the first peak P1 to the second peak P2 corresponds to the time from depolarization to repolarization in a cardiac cycle. In this example, waveform data representing changes in the extracellular potential at which the first peak P1 and the second peak P2 appear, as shown in Figure 7(B), is used as pre-administration waveform data, which is an example of control waveform data. As mentioned above, waveform data representing changes in the action potential, as shown in Figure 7(A), may also be used as pre-administration waveform data. In this case, the analysis unit 61 detects the timing of depolarization and repolarization from waveform data representing changes in the action potential measured using patch clamping or the like, and evaluates the time from depolarization to repolarization. The analysis unit 61 then normalizes the amplitude and time of the waveform data representing changes in the action potential.

FIG. 14 shows the state in which normalization processing is performed on multiple pre-administration waveform data shown in FIG. 8, which have variations in the time and amplitude A2 (see FIG. 7) of section SA. The normalized pre-administration waveform data are superimposed. Because multiple pre-administration waveform data are superimposed, they are shown with a spread in the amplitude direction. In the example of FIG. 14, the normalization processing has been performed to set the time of section SA to a constant value TN. As an example, the constant value TN is 0.4 seconds. Furthermore, the amplitude A2 of the second peak P2 is set to a constant value AN. As an example, the constant value AN is 1 mV. Furthermore, the curve Lav shown in FIG. 14 represents the average value of the multiple superimposed pre-administration waveform data. Although the curve Lav is somewhat difficult to see in FIG. 14, it passes through the center of the multiple pre-administration waveform data that vary in the amplitude direction.

By performing this normalization process, quantitative features such as the time and amplitude of each piece of pre-administration waveform data are ignored, allowing the morphological features of each piece of pre-administration waveform data to stand out. Conventionally, this type of eligibility determination has been carried out by human visual sensory evaluation, but in human visual sensory evaluation, attention is focused on morphological features such as subtle differences in the shape of the waveform rather than quantitative features such as time and amplitude. By performing this normalization process, the morphological analysis by the analysis unit 61 can be made closer to a human visual sensory evaluation.

FIG. 15 shows an example of evaluation criteria for determining eligibility. In the example shown in FIG. 15, the evaluation criteria include those for preprocessing and those for morphological analysis. Analysis items based on these evaluation criteria are included in reference information 29.

As an example, there are three evaluation criteria for preprocessing: "0-1" to "0-3." Qualification criteria "0-1" stipulates that "the absolute values of the positive and negative amplitudes of the first peak P1 are equal to or greater than a certain value." Qualification criteria "0-2" stipulates that "the amplitude A2 of the second peak P2 is within a certain range." Qualification criteria "0-3" stipulates that "the ratio of the average value of section SA to the amplitude A2 of the second peak P2 is within a certain range."

The analysis unit 61 analyzes the pre-administration waveform data based on the conditions of these viewpoints "0-1" to "0-3" and excludes pre-administration waveform data that does not satisfy the conditions from the morphology analysis target. In other words, the analysis unit 61 executes processing to exclude pre-administration waveform data in which at least one of the amplitudes A1 of the first peak P1 and the amplitude A2 of the second peak P2 does not satisfy a preset condition from the morphology analysis target. By performing such pre-processing, the processing time for eligibility determination can be shortened.

Furthermore, the three aspects "0-1" to "0-3" are examples of "conditions in which at least one of the amplitudes corresponding to depolarization and the amplitude corresponding to repolarization is preset" according to the technology of the present disclosure. Furthermore, the condition of aspect "0-1" is an example of "a first condition in which the absolute value of the amplitude corresponding to depolarization is equal to or greater than a certain value" according to the technology of the present disclosure, and the condition of aspect "0-2" is an example of "a second condition in which the amplitude corresponding to repolarization is within a preset range" according to the technology of the present disclosure.

Furthermore, as shown in Figure 15, there are three example evaluation perspectives for morphological analysis: perspectives "1-1" to "1-3." Perspective "1-1" is that "the evaluation index for each individual section, such as the maximum amplitude of section SA3, must be within a certain standard." Perspective "1-2" is that "the values for each section, such as the ratio of the average amplitudes of sections SA2 and SA3, must be compared and the difference must be within a certain standard." Perspective "1-3" is that "the indices for evaluating the shape of each section, such as the slope, straightness, and waviness of section SA2, must be within a certain standard. The slope or straightness is evaluated using, for example, linear approximation. The waviness is evaluated using a quadratic or cubic approximation curve."

More specifically, detailed analysis items are set based on these evaluation criteria. Analysis items include thresholds and numerical ranges that serve as criteria for judgment.

As shown as an example in Figure 15, the analysis items for analyzing the morphology include items set for each section, with the area around the beat divided into multiple sections, such as section SA2 and section SA3. By setting items for each section in this way, the analysis process can be simplified compared to when the sections are not divided.

Furthermore, the analysis items configured for each section include items using multiple approximation curves of different orders, as in viewpoint "1-3." As shown as an example in Figure 16, the less undulation there is in the pre-administration waveform data for section SA2, the closer it is to the ideal waveform. As a specific criterion, for example, the ratio of the quadratic approximation error to the cubic approximation error of the waveform for section SA2 is equal to or less than a certain value. As shown as an example in Figure 16, first, a quadratic approximation curve and a cubic approximation curve of the pre-administration waveform data are derived for section SA2. Then, the error between the pre-administration waveform data and the quadratic approximation curve is calculated as the quadratic approximation error, and the error between the pre-administration waveform data and the cubic approximation curve is calculated as the cubic approximation error. Then, it is determined whether the ratio of the quadratic approximation error to the cubic approximation error is equal to or less than a certain value.

In addition to waviness, multiple approximation curves of different orders can also be used when evaluating straightness. In this way, the shape analysis items set for each section include items using multiple approximation curves of different orders, making it possible to analyze the shape in more detail than if these were not used.

The specific values, such as thresholds, used for the analysis items in these eligibility assessments may be values obtained through experiments or simulations, or may be determined based on electrophysiological knowledge. They may also be determined using a machine learning model based on ideal waveforms.

The operation of the above configuration will be explained using the flowchart shown in Figure 17. First, the information processing device 20 acquires pre-administration waveform data from the cell culture device 10, measured using the MEA plate 30, prior to administration of the drug candidate substance. As an example, eligibility determination is performed on a channel-by-channel basis for the pre-administration waveform data for 16 channels (see Figure 9) output from all wells 32 of the MEA plate 30.

In determining eligibility, first, the analysis unit 61 performs normalization in step S1000. In step S1000, the analysis unit 61 normalizes the pre-administration waveform data with respect to the time from the first peak P1 to the second peak P2 and the amplitude A2 of the second peak P2. The measurement time for the pre-administration waveform data output from one channel is several minutes, and the acquired pre-administration waveform data includes data for several tens of beats. The analysis unit 61 divides these several tens of beats of pre-administration waveform data into groups of one to two beats, and normalizes the time and amplitude of the divided data. As a result, multiple normalized pre-administration waveform data such as those shown in Figure 14 are generated for each channel.

In step S2000, the analysis unit 61 analyzes the morphology of the normalized pre-administration waveform data. The morphology analysis is performed for morphology analysis items based on the multiple evaluation perspectives shown in Figure 15. In this case, the analysis unit 61 performs analysis for each of the pre-processing perspectives "0-1" to "0-3" prior to the morphology analysis items. The analysis unit 61 then excludes from the morphology analysis any pre-administration waveform data that does not satisfy the conditions of each of the pre-processing perspectives "0-1" to "0-3." By performing such pre-processing, the processing time for eligibility determination can be shortened.

After performing preprocessing, the analysis unit 61 judges the pre-administration waveform data that satisfies the preprocessing conditions based on the morphology analysis items. The analysis unit 61 determines whether the data meets the criteria specified in the analysis items based on viewpoints "1-1" to "1-3" shown in Figure 15. As described above, the analysis items divide the pulsation cycle into multiple intervals and include items set for each interval. Furthermore, the items set for each interval include items that use multiple approximation curves of different orders, as shown in Figure 16.

By performing this type of analysis, the analysis unit 61 determines the eligibility of the pre-administration waveform data on a channel-by-channel basis. That is, for one well 32, the eligibility is determined for the pre-administration waveform data of 16 channels, and this is done for the pre-administration waveform data of all wells 32 on the MEA plate 30. If the pre-administration waveform data is determined to be eligible, the channel that outputs that pre-administration waveform data is also determined to be eligible. A channel determined to be eligible is selected, for example, as a golden channel that can be used for toxicity evaluation.

In step S3000, the analysis unit 61 presents the eligibility determination results to the user by outputting them to the display 20. Screen 71 shown in FIG. 18 is an example of a screen displaying the eligibility determination results. Screen 71 displays waveforms for 16 channels of one well 32 side by side. Channels determined to be eligible are displayed with a bold frame 72, for example, to distinguish them from channels determined to be "unqualified." Of course, the bold frame 72 is an example of an indicator indicating "eligibility," and the indicator may be displayed in a manner other than the bold frame 72. The indicator may be displayed in a manner such as by adding a circle or by inserting the word "eligible." Alternatively, "unqualified" channels may be hidden and only "eligible" channels may be displayed.

Furthermore, for example, if even one of the multiple channels within a well 32 is qualified, that well 32 is also determined to be qualified. A well 32 determined to be qualified is determined to be usable for toxicity evaluation.

After the eligibility assessment is complete, the drug candidate substance is administered to each well 32 of the MEA plate 30. Post-administration waveform data is measured by the cell culture device 10. The information processing device 20 analyzes the post-administration waveform data according to the evaluation items of the toxicity assessment. This analysis includes, for example, FPD measurement as shown in Figure 7 and the presence or absence of abnormal waveforms characteristic of EAD, DAD, and cardiac arrest as shown in Figures 11 to 13. The results of these analyses are presented, and the user makes a final evaluation of the toxicity of the drug candidate substance based on the analysis results.

As explained above, the processor 23 of the information processing device 20 determines the suitability of control waveform data, which is waveform data representing electrical changes in response to the pulsation of cardiomyocytes and is used in toxicity evaluation tests of drug candidate substances, by analyzing the morphology using a method that is not dependent on variability between measurements, and presents the eligibility determination result. In the above example, pre-administration waveform data is an example of control waveform data, and normalization of pre-administration waveform data is an example of a method for analyzing morphology using a method that is not dependent on variability between measurements. This makes it possible to obtain a determination result regarding the suitability of waveform data for use in toxicity evaluation tests that is closer to a visual sensory evaluation by a human than in the past.

More details are as follows. As described above, when a person visually assesses the eligibility of pre-administration waveform data, attention is focused on the morphological features of the waveform rather than quantitative features such as amplitude and time. According to the technology disclosed herein, as an example, a method is adopted that is not dependent on measurement-to-measurement variability by normalizing the quantitative features. Because morphological features stand out in the normalized pre-administration waveform data, the morphological features are easy to grasp even when mechanical analysis is performed by the analysis unit 61. For example, as described in International Publication No. 2022/176310, there have been conventional techniques for mechanically processing eligibility assessments using machine learning models. However, conventional techniques using machine learning models do not take into account the normalization of waveform data. In other words, conventional techniques using machine learning models do not employ methods that are independent of measurement-to-measurement variability. As a result, there is a possibility that feature values may be extracted without distinguishing between quantitative and morphological features, and the morphological features may not be appropriately reflected in the assessment results due to being influenced by the quantitative features. Morphological features are key points in sensory evaluation by humans visually. The technology disclosed herein makes it possible to determine eligibility based on morphological characteristics, thereby obtaining evaluation results that are closer to human visual sensory evaluation than conventional methods.

In addition, processor 23 analyzes the morphology of control waveform data (pre-administration waveform data, for example) using a method that is independent of variations in both the time from depolarization (first peak P1, for example) to repolarization (second peak P2, for example) in the pulsation cycle and the amplitude A2 of repolarization (second peak P2, for example). Therefore, compared to when focusing on variations in other parts, it is possible to obtain assessment results that are closer to human visual sensory evaluation.

Specifically, it is as follows. First, the objects of normalization are the time corresponding to the horizontal axis of the waveform data and the amplitude corresponding to the vertical axis. Then, for the time on the vertical axis, the time from the first peak P1 to the second peak P2 in the beat cycle (an example of the time from depolarization to repolarization) is the object. This time corresponds to the aforementioned section SA. As shown in Figure 15, the morphological analysis items include many of the morphological characteristics of section SA. These morphological analysis items are items that reflect the points that people focus on, so the greater the number of analysis items in section SA, the greater the number of points that people focus on in this section SA. According to the technology disclosed herein, the time in section SA is one of the objects of normalization, and therefore it is possible to more closely approximate the results of a visual assessment by a human, compared to when the time in section SA is not used as a normalization target.

Furthermore, the amplitude on the horizontal axis is the amplitude A2 of the second peak P2. As mentioned above, the shape of the section SA from the first peak P1 to the second peak P2 is an important subject of analysis, and therefore, in order to compare the morphological characteristics of section SA, it is conceivable to normalize using the amplitude of either the first peak P1 or the second peak P2. With the technology disclosed herein, by normalizing using the amplitude A2 of the second peak P2, which has a relatively small amplitude, it is possible to more appropriately extract changes in the amplitude direction of section SA compared to when the amplitude A1 of the first peak P1 is normalized.

In this way, in the above embodiment, the analysis unit 61, which is an example of a processor, analyzes the morphology in a manner that is not dependent on the variability of both the time from depolarization to repolarization and the amplitude corresponding to repolarization for the control waveform data. This makes it possible to obtain assessment results that are closer to a human visual sensory evaluation than when focusing on variability in other areas.

Furthermore, as shown in the above embodiment, one example of a method that is not dependent on variations between measurements is to normalize the control waveform data. By using normalization, processing can be made relatively simple compared to using methods other than normalization.

In addition to normalization, there is another method that is not dependent on variations between measurements: when performing morphological analysis of the control waveform data, the evaluation value of the morphological analysis is adjusted according to the difference in amplitude and time. The analysis unit 61 performs morphological analysis using the adjusted evaluation value and determines eligibility. In other words, while normalization involves the process of shaping the control waveform data, the method of adjusting the evaluation value of the morphological analysis is a method that does not involve shaping the control waveform data, but instead performs a numerical process equivalent to normalization.

Furthermore, as shown as an example of pre-processing for eligibility determination, the analysis unit 61, which is an example of a processor, excludes from the morphology analysis target control waveform data in which at least one of the amplitudes corresponding to depolarization and repolarization does not satisfy a preset condition. As an example, the analysis unit 61 excludes from the morphology analysis target pre-administration waveform data in which at least one of the amplitude A1 of the first peak P1 and the amplitude of the second peak P2 does not satisfy a preset condition. By performing such pre-processing, waveform data that is clearly ineligible can be excluded, thereby shortening the processing time for eligibility determination. Furthermore, because the determination of whether the conditions are satisfied is performed with a focus on amplitude, it is possible to easily identify targets that should be excluded from the analysis target.

Furthermore, the conditions for determining an object to be analyzed include a first condition that the absolute value of the amplitude corresponding to depolarization is equal to or greater than a certain value, and a second condition that the amplitude corresponding to repolarization is within a preset range. As an example, the first condition is that the absolute value of the amplitude A1 of the first peak P1 is equal to or greater than a certain value, and the second condition is that the amplitude of the second peak P2 is within a preset range. The first and second conditions are one of the basic properties that qualifying waveform data must have at a minimum in terms of amplitude. By using these first and second conditions, it is possible to appropriately narrow down the objects to be analyzed for morphology.

In the above embodiment, the preprocessing for determining eligibility is performed on normalized waveform data, but preprocessing may also be performed on control waveform data before normalization (pre-administration waveform data, for example). This makes it possible to exclude inappropriate waveform data further upstream.

Furthermore, the analysis items for analyzing morphology include items set for each interval that divides the pulsation cycle of cardiomyocytes into multiple intervals (for example, interval SA, interval SB, interval SA1, and interval SA2 shown in Figure 14). Because the analysis items include items set for each interval, the analysis process can be simplified compared to when the intervals are not divided.

Furthermore, the items set for each section include items that use multiple approximation curves of different orders, as shown as examples in items "1-3," "1-4," and "1-7." Because the items include items that use multiple approximation curves of different orders, more detailed morphology analysis is possible compared to when these are not used, and the eligibility assessment results can be closer to a visual sensory evaluation by a human.

The analysis unit 61, which is an example of a processor, determines eligibility using at least one of rule-based, template matching, and machine learning methods. Rule-based analysis is a method of analyzing morphology by setting conditions such as thresholds and numerical ranges, as in the evaluation criteria shown in FIG. 15, and determining whether the control waveform data satisfies the set conditions. Template matching is a method of analyzing morphology by comparing standard waveform data that serves as a template with the control waveform data, deriving a similarity for each analysis item based on the evaluation criteria, and using the similarity as an evaluation value. Machine learning is a method of determining eligibility using, for example, a machine learning model that inputs control waveform data and outputs eligibility. This machine learning model is a model trained using training data consisting of pairs of control waveform data for training and corresponding ground truth data that indicate the eligibility determination result. The analysis unit 61 may determine eligibility using any one of multiple methods, such as rule-based analysis, template matching, and machine learning, or a combination of multiple methods.

Furthermore, the control waveform data (pre-administration waveform data, for example) is waveform data acquired using an MEA plate 30 having multiple electrodes 41 on the bottom 34 and multiple wells 32 in which cardiomyocytes can be placed. Therefore, the technology disclosed herein is effective for determining the eligibility of multiple wells 32 of an MEA plate 30.

"Variation 1"
The processor 23 may have a function of displaying whether or not the wells 32 of the MEA plate 30 can be used for toxicity evaluation tests based on the determination result of the eligibility of the control waveform data (pre-administration waveform data, for example). Here, the suitability of the wells 32 for use in toxicity evaluation tests is referred to as "well eligibility" to distinguish it from the eligibility of the control waveform data. The examples shown in FIGS. 19 to 21 are examples of a screen 81 that displays the well eligibility for each well 32 of the MEA plate 30. First, as shown in FIG. 19 , the screen 81 displays the arrangement of the multiple wells 32 of the MEA plate 30. On the screen 81, the wells 32 are represented by round well icons 82. A total of 24 well icons 82 are arranged in a matrix of 4 rows and 6 columns on the screen 81, corresponding to the number and arrangement of the wells 32 of the MEA plate 30.

Note that the MEA plate 30 shown in Figure 2 has a total of 48 wells 32 arranged in 6 rows and 8 columns, but for convenience, the screen 81 in Figures 19 to 21 is shown in a 4 row x 6 column format.

As an example of how each column of the MEA plate 30 is used, columns 1 and 2 are used as references, and columns 3 to 6 are used as test subjects. Reference columns are columns into which substances known to be positive (toxic) or negative (non-toxic) are administered. It is normal for abnormal waveforms indicating toxicity to appear in the post-administration waveform data output from each well 32 in the positive columns, while it is normal for abnormal waveforms to not appear in the post-administration waveform data of the negative columns. However, if the pre-administration waveform data of wells 32 in these reference columns is not qualified, abnormal waveforms may also appear in the negative columns, for example. Therefore, the well qualification of wells 32 in the reference columns is also determined based on the qualification of the pre-administration waveform data.

The test subject columns are columns into which drug candidate substances with unknown toxicity, the subject of toxicity evaluation tests, are administered. In the example of Figure 19, different drug candidate substances, Compound 1 to Compound 4, are administered to each test subject column. The toxicity of these test subject Compounds 1 to 4 is evaluated based on the post-administration waveform data output from the wells 32 of each column. In order for toxicity evaluation to be performed properly, it is necessary that the pre-administration waveform data output from each well 32 in the test subject columns is qualified, just like in the reference columns.

Each row has four wells 32, and well eligibility is determined for each well 32. In this example, the well eligibility of an individual well 32 is determined to be eligible if there is eligible pre-administration waveform data for at least one of the 16 channels of electrodes 41 in that well 32.

The processor 23 also determines whether the toxicity evaluation test for each substance is successful based on the well eligibility determination results. In this example, because the administered substance differs for each column of the MEA plate 30, the success or failure of the toxicity evaluation test for each substance is presented as the success or failure of the toxicity evaluation test for each column. For example, if three of the four wells 32 in a column are well eligible, the toxicity evaluation test for that column is determined to be successful. If two or more wells 32 in a column are unqualified, the toxicity evaluation test for that column is determined to be unqualified. This is because, for example, when determining whether the toxicity evaluation test for a single substance is successful, the reliability of the toxicity evaluation test cannot be ensured unless the number of wells 32 determined to be "well eligible" out of the wells 32 used for that substance is greater than the number of wells 32 determined to be "unqualified."

Furthermore, in this example, the success or failure of the toxicity evaluation test for the entire MEA plate 30 is also determined. For example, if the toxicity evaluation test for at least one of the reference columns fails, the toxicity evaluation test for the entire MEA plate 30 is determined to be unsuccessful. For the test columns, if the toxicity evaluation test for even one column fails, the test is determined to be successful overall.

This will be explained in detail using Figures 20 and 21. First, Figure 20 shows an example in which the toxicity evaluation test for the entire MEA plate 30 is determined to be successful, and Figure 21 shows an example in which the toxicity evaluation test for the entire MEA plate 30 is determined to be unsuccessful.

In Figure 20, a total of three wells 32 have been determined to be "unqualified wells", namely the well 32 corresponding to row B in the fourth column, and the wells 32 corresponding to rows B and C in the sixth column. When a well is determined to be "unqualified well", the corresponding well icon 82 is displayed so that it can be distinguished from the other well icons 82, as indicated by hatching. As a display format, the color of the well icon 82 may be changed, or an indicator such as a mark or text information indicating that the well is unqualified may be displayed. Furthermore, if the well is qualified, the well icon 82 may indicate this.

In the sixth column, two wells 32 are judged to be "unsuitable wells," so the toxicity evaluation test for compound 4 in the sixth column is judged to be unsuccessful. On the other hand, in the fourth column, only one well 32 is judged to be "unsuitable wells," so the toxicity evaluation test for the fourth column is judged to be successful. As an example, a bold frame 83 is displayed in columns where the toxicity evaluation test is successful. On the other hand, a bold frame 83 is not displayed in columns where the toxicity evaluation test is unsuccessful. This allows the success or failure of each column of the toxicity evaluation test to be displayed in an identifiable manner.

Furthermore, in the example of Figure 20, the toxicity evaluation test for the reference column is successful, and there is also a column for the test subject that has passed the toxicity evaluation test. Therefore, it is determined that the toxicity evaluation test for the entire MEA plate 30 is successful. To indicate this, the outer frame of the screen 81 is displayed with a bold frame 84. Of course, this display format is just one example, and other display formats besides the bold frame 84 may also be used. Furthermore, the screen 81 also displays that the test was successful.

In the example of Figure 21, a total of six wells 32 have been determined to be "unqualified wells", including the wells 32 corresponding to rows A and B in the first column, the well 32 corresponding to row C in the second column, the well 32 corresponding to row B in the fourth column, and the wells 32 corresponding to rows B and C in the sixth column. Since there are two wells 32 determined to be "unqualified wells" in the first and sixth columns, the toxicity evaluation test for each column is determined to be unsuccessful. Therefore, the thick frame 83 is not displayed in the first and sixth columns.

Furthermore, in the example of Figure 21, the toxicity evaluation test for the first column, which is the reference column, is not successful, so the toxicity evaluation test for the entire MEA plate 30 is determined to be unsuccessful. Therefore, in the example of Figure 21, the thick frame 84 is not displayed on the screen 81. Furthermore, the screen 81 also displays "test failed."

In this way, the processor 23 has the function of indicating whether or not a well 32 can be used for toxicity evaluation testing based on the eligibility of the control waveform data, allowing the user to easily grasp the well eligibility of each well 32. It is also possible to easily indicate the success or failure of a toxicity evaluation test for a row made up of multiple wells 32, and the success or failure of a toxicity evaluation test for the entire MEA plate 30, based on well eligibility.

"Variation 2"
While the first modification example is an example in which well eligibility is determined solely based on the determination of the eligibility of control waveform data (e.g., pre-administration waveform data), drug-treated waveform data (e.g., post-administration waveform data) may also be used to determine well eligibility, i.e., whether or not the well 32 can be used for toxicity evaluation testing. Similar to FIG. 10 , FIG. 22 shows an example in which pre-administration waveform data and post-administration waveform data are displayed for comparison. Similarly to FIG. 10 , the post-administration waveform data also includes multiple waveform data with different concentrations of the drug candidate substance. FIG. 22(A) shows an example in which a result is determined to be "eligible," while FIG. 22(B) shows an example in which a result is determined to be "ineligible." In the example shown in FIG. 22(B), waveform data up to high concentrations before and after administration show measured extracellular potential waveforms, but no change in potential is observed for waveform data at ultra-high concentrations. This is presumably due to, for example, cardiomyocytes being detached from the bottom 34 of the well 32.

In such cases, post-administration waveform data cannot be obtained for the ultra-high concentration waveform data, and the toxicity of the drug candidate substance at ultra-high concentrations cannot be evaluated. In such cases, the well 32 in question may be determined to be "unsuitable as a well."

In other words, in variant 2, in addition to the control waveform data, the drug-treated waveform data is also used to determine whether or not the well 32 can be used for toxicity evaluation testing. Since the toxicity evaluation testing is ultimately performed based on the drug-treated waveform data, by checking the state of the drug-treated waveform data, as in variant 2, the well's suitability can be more appropriately determined.

In addition, well eligibility may be determined based solely on drug-treated waveform data, without using control waveform data.

"Variation 3"
Furthermore, as shown in Modification 3 in FIG. 23 , in step S3000, the processor 23 may present standard waveform data having a standard form recognized as being suitable, in addition to the result of the qualification determination. The standard waveform data is, for example, data showing an ideal waveform such as that shown in FIG. 7(B). The standard waveform data may be actual measurement data selected from control waveform data acquired from actual cardiomyocytes, or may be data created by simulation or the like. By presenting such standard waveform data, the user can easily perform a sensory evaluation in which the morphological characteristics of the control waveform data are visually confirmed. This allows both the determination result of the processor 23 and a visual sensory evaluation to be performed.

"Variation 4"
Alternatively, as shown in Variation 4 in FIG. 24 , the processor 23 may simply normalize the control waveform data (e.g., pre-administration waveform data) representing electrical changes in response to the pulsation of cardiomyocytes and used in toxicity evaluation tests of drug candidate substances, with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization, and present the normalized control waveform data. That is, in Variation 4 in FIG. 24 , unlike the examples shown in FIGS. 17 and 23 , the processor 23 does not analyze the form of the control waveform data or determine its eligibility. The normalized control waveform data is simply presented. This allows the user to visually evaluate the drug-treated waveform data, such as post-administration waveform data.

Furthermore, in variant 4, as in variant 3 shown in Figure 23, standard waveform data having a standard form that is recognized as being suitable may be presented in addition to the normalized control waveform data.

In the above embodiment, the hardware structure of the processing units that perform various processes, such as the data acquisition unit 60, analysis unit 61, and output unit 62, is the various processors shown below.

Various types of processors include CPUs, programmable logic devices (PLDs), dedicated electrical circuits, etc. As is well known, a CPU is a general-purpose processor that executes software (programs) and functions as various processing units. A PLD is a processor such as an FPGA (Field Programmable Gate Array) whose circuit configuration can be changed after manufacturing. A dedicated electrical circuit is a processor with a circuit configuration designed specifically to perform specific processing, such as an ASIC (Application Specific Integrated Circuit).

A single processing unit may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, multiple FPGAs, or a combination of a CPU and an FPGA). Multiple processing units may also be configured with a single processor. Examples of multiple processing units configured with a single processor include, first, a form in which one or more CPUs are combined with software to form a single processor, and this processor functions as multiple processing units. Second, a form in which a processor is used to realize the functions of an entire system including multiple processing units on a single IC chip, as typified by a system on chip (SoC). In this way, the various processing units are configured with a hardware structure using one or more of the various processors listed above.

Furthermore, the hardware structure of these various processors is, more specifically, an electrical circuit that combines circuit elements such as semiconductor devices.

The above explanation allows one to understand the following techniques.
[Additional note 1]
An information processing device including a processor,
The processor
Control waveform data, which is waveform data representing electrical changes according to the pulsation of cardiomyocytes, is used in a toxicity evaluation test of a drug candidate substance. The control waveform data is analyzed for its morphology using a method that is not dependent on variability between measurements, thereby determining whether the control waveform data is suitable for use in the toxicity evaluation test;
Present the results of the eligibility determination;
Information processing device.
[Additional note 2]
The processor analyzes the morphology of the control waveform data in a manner that is independent of variations in both the time from depolarization to repolarization in a beat cycle and the amplitude corresponding to the repolarization.
Item 1. An information processing device according to item 1.
[Additional note 3]
A method that is independent of measurement-to-measurement variability is to normalize the data in time and amplitude to the reference waveform data.
3. The information processing device according to claim 2.
[Additional note 4]
The processor excludes control waveform data in which at least one of the amplitudes corresponding to depolarization and the amplitude corresponding to repolarization does not satisfy a preset condition from the analysis of the morphology.
Item 3. The information processing device according to any one of items 2 and 3.
[Additional note 5]
The conditions include a first condition that the absolute value of the amplitude corresponding to the depolarization is equal to or greater than a certain value, and a second condition that the amplitude corresponding to the repolarization is within a predetermined range.
5. The information processing device according to claim 4.
[Additional note 6]
The analysis items for analyzing the morphology include items set for each section by dividing the pulsation cycle into multiple sections,
6. An information processing device according to any one of claims 1 to 5.
[Additional note 7]
The items set for each section include items using multiple approximation curves of different degrees.
7. The information processing device according to claim 6.
[Additional Note 8]
the processor determines eligibility using at least one of rule-based, template matching, and machine learning;
8. An information processing device according to any one of claims 1 to 7.
[Additional Note 9]
The control waveform data is waveform data acquired using an MEA plate having a plurality of electrodes on the bottom and a plurality of wells in which cardiomyocytes can be placed.
9. The information processing device according to any one of claims 1 to 8.
[Additional Note 10]
The processor has a function of indicating whether or not the well can be used for a toxicity evaluation test based on the determination of the eligibility of the control waveform data.
10. The information processing device according to claim 9.
[Additional Note 11]
The processor
and using the drug-treated waveform data obtained after administering the drug candidate substance to the cardiomyocytes to determine whether the well can be used for toxicity evaluation tests.
Item 11. An information processing device according to item 10.
[Additional Note 12]
In addition to the judgment result, standard waveform data having a standard form that is recognized as being suitable is presented.
12. The information processing device according to any one of claims 1 to 11.
[Additional Note 13]
A method for operating an information processing device having a processor, comprising:
The processor
Control waveform data, which is waveform data representing electrical changes according to the pulsation of cardiomyocytes, is used in a toxicity evaluation test of a drug candidate substance. The control waveform data is analyzed for its morphology using a method that is not dependent on variability between measurements, thereby determining whether the control waveform data is suitable for use in the toxicity evaluation test;
Present the results of the eligibility determination;
A method for operating an information processing device.
[Additional Note 14]
An operating program for an information processing device having a processor,
Control waveform data, which is waveform data showing electrical changes according to the pulsation of cardiomyocytes, is used in toxicity evaluation tests of drug candidate substances, and the control waveform data is analyzed for its morphology using a method that is not dependent on variability between measurements, thereby determining whether the control waveform data is suitable for use in toxicity evaluation tests.
Present the results of the eligibility determination;
An operating program for an information processing device that causes a processor to execute processing including the steps of:
[Additional Note 15]
An information processing device including a processor,
The processor
Waveform data representing electrical changes in response to the pulsation of cardiomyocytes, wherein control waveform data used in a toxicity evaluation test for a drug candidate substance is normalized with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization;
Presenting the control waveform data after normalization,
Information processing device.
[Additional Note 16]
In addition to the normalized control waveform data, standard waveform data having a standard form that is recognized as eligible is presented.
Item 16. An information processing device according to item 15.
[Additional Note 17]
A method for operating an information processing device having a processor, comprising:
The processor
Waveform data representing electrical changes in response to the pulsation of cardiomyocytes, wherein control waveform data used in a toxicity evaluation test for a drug candidate substance is normalized with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization;
Presenting the control waveform data after normalization,
A method for operating an information processing device.
[Additional Note 18]
An operating program for an information processing device having a processor,
Normalizing control waveform data representing electrical changes in response to the pulsation of cardiomyocytes, which is used in a toxicity evaluation test of a drug candidate, with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization;
Presenting the control waveform data after normalization;
An operating program for an information processing device that causes a processor to execute processing including the steps of:

The technology of the present disclosure can be appropriately combined with the various embodiments and/or modified examples described above. Furthermore, it is not limited to the above embodiments, and various configurations can be adopted as long as they do not deviate from the gist of the technology. Furthermore, the technology of the present disclosure extends not only to programs but also to storage media that non-temporarily store programs. Storage media are, for example, computer-readable non-temporary storage media such as USB (Universal Serial Bus) memory, flexible disks, and CD-ROMs (Compact Disc Read Only Memory). Programs may also be provided online via a network such as the Internet. The technology of the present disclosure also extends not only to programs but also to program products. Program products include all forms of products for providing programs. Like programs, program products may be provided stored on computer-readable non-temporary storage media, or they may be provided online.

The above-described written content and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above explanation of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or substitutions may be made to the above-described written content and illustrations, as long as they do not deviate from the spirit of the technology of the present disclosure. Furthermore, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above-described written content and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

The disclosure of Japanese Patent Application No. 2024-051832, filed on March 27, 2024, is incorporated herein by reference in its entirety. In addition, all documents, patent applications, and technical standards described herein are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard was specifically and individually indicated to be incorporated by reference.

Claims (18)

An information processing device including a processor,
The processor:
Control waveform data, which is waveform data representing electrical changes according to the pulsation of cardiomyocytes, is used in a toxicity evaluation test of a drug candidate substance, and the control waveform data is analyzed for its morphology using a method that is not dependent on variability between measurements, thereby determining whether the control waveform data is suitable for use in the toxicity evaluation test;
presenting the results of the eligibility determination;
Information processing device. The processor analyzes the morphology of the control waveform data in a manner that is independent of variations in both the time from depolarization to repolarization in the cycle of the beat and the amplitude corresponding to the repolarization.
The information processing device according to claim 1 . A method that is independent of measurement-to-measurement variability is a method that normalizes the time and amplitude to the reference waveform data.
The information processing device according to claim 2 . The processor excludes the control waveform data in which at least one of the amplitude corresponding to the depolarization and the amplitude corresponding to the repolarization does not satisfy a preset condition from the analysis target of the morphology.
The information processing device according to claim 2 . The conditions include a first condition that the absolute value of the amplitude corresponding to the depolarization is equal to or greater than a certain value, and a second condition that the amplitude corresponding to the repolarization is within a predetermined range.
The information processing device according to claim 4 . The analysis items for analyzing the morphology include items set for each of the intervals obtained by dividing the pulsation cycle into a plurality of intervals.
The information processing device according to claim 1 . The items set for each section include items using a plurality of approximation curves of different degrees.
The information processing device according to claim 6 . the processor determines the eligibility using at least one of a rule-based approach, template matching, and machine learning.
The information processing device according to claim 1 . The control waveform data is waveform data acquired using an MEA plate having a plurality of electrodes on the bottom and a plurality of wells in which the cardiomyocytes can be placed.
The information processing device according to claim 1 . The processor has a function of indicating whether or not the well can be used for the toxicity evaluation test based on the determination of the eligibility of the control waveform data.
The information processing device according to claim 9 . The processor:
and using the drug-treated waveform data obtained after administering the drug candidate substance to the cardiomyocytes to determine whether the well can be used for a toxicity evaluation test.
The information processing device according to claim 10. In addition to the judgment result, standard waveform data having a standard form that is recognized as being suitable is presented.
The information processing device according to claim 1 . A method for operating an information processing device having a processor, comprising:
The processor:
Control waveform data, which is waveform data representing electrical changes according to the pulsation of cardiomyocytes, is used in a toxicity evaluation test of a drug candidate substance, and the control waveform data is analyzed for its morphology using a method that is not dependent on variability between measurements, thereby determining whether the control waveform data is suitable for use in the toxicity evaluation test;
presenting the results of the eligibility determination;
A method for operating an information processing device. An operating program for an information processing device having a processor,
Control waveform data, which is waveform data representing electrical changes according to the pulsation of cardiomyocytes, is used in a toxicity evaluation test of a drug candidate substance, and the control waveform data is analyzed for its morphology using a method that is not dependent on variability between measurements, thereby determining whether the control waveform data is suitable for use in the toxicity evaluation test;
Presenting the results of said eligibility determination;
An operating program for an information processing device that causes a processor to execute processing including the steps of: An information processing device including a processor,
The processor:
Waveform data representing electrical changes in response to the pulsation of cardiomyocytes, wherein control waveform data used in a toxicity evaluation test of a drug candidate substance is normalized with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization;
presenting the control waveform data after normalization;
Information processing device. In addition to the control waveform data after normalization, standard waveform data having a standard form that is recognized as acceptable is presented.
The information processing device according to claim 15. A method for operating an information processing device having a processor, comprising:
The processor:
Waveform data representing electrical changes in response to the pulsation of cardiomyocytes, wherein control waveform data used in a toxicity evaluation test of a drug candidate substance is normalized with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization;
presenting the control waveform data after normalization;
A method for operating an information processing device. An operating program for an information processing device having a processor,
Normalizing control waveform data representing electrical changes in response to the pulsation of cardiomyocytes, the control waveform data being used in a toxicity evaluation test of a drug candidate, with respect to the time from depolarization to repolarization in the pulsation cycle and the amplitude corresponding to the repolarization;
presenting said control waveform data after normalization;
An operating program for an information processing device that causes the processor to execute processing including the steps of: