Method and system for analyzing ion currents

Abstract

This invention provides an analysis method that enables analysis in a short time by appropriately providing analysis tools that handle the enormous amount of computational power required for analyzing current data. [Solution] A method for analyzing ion current flowing through an ion channel, comprising: an ion current measurement step of measuring the ion current of at least one artificial cell membrane chip; an ion current data storage step of storing the measured ion current data; a transmission step of sending the stored ion current data to a server via a network; an analysis step of analyzing the ion current data on the server using a predetermined analysis method; and an analysis result storage step of storing the analyzed results on the server. The ion current measurement step and the ion current data storage step are performed in an ion current measuring device, and the server is connected to at least one ion current measuring device via a network.

Description

Technical Field

[0001] The present invention relates to a method for analyzing ion current and an ion current analysis system.

Background Art

[0002] Cells that make up an organism, and mitochondria, Golgi bodies, endoplasmic reticulum, etc. present inside the cells are covered with a biological membrane on the outside, and this biological membrane is basically composed of a lipid bilayer. And various proteins having physiological activity are held on the lipid bilayer in a form penetrating this lipid bilayer, and such proteins are called transmembrane proteins. These transmembrane proteins play important roles in vivo.

[0003] Among such transmembrane proteins, there is an ion channel. An ion channel is a general term for proteins that pass ions passively. In addition to maintaining and changing the membrane potential of cells, it also allows the inflow and outflow of ions in cells. It is involved in the generation of action potentials in electrically excitable cells such as nerve cells, the generation of receptor potentials in sensory cells, and the maintenance of resting membrane potentials in cells.

[0004] When an ion channel opens, ions permeate, and when it closes, the permeation of ions stops. Therefore, due to the opening and closing of the ion channel, the flow of ions passing through the lipid bilayer changes, and the ion current changes.

[0005] When a certain type of pharmaceutical acts on a cell, the opening and closing of the ion channel are controlled so that a physiological activity effect is expressed. Therefore, it becomes possible to confirm the effects of various pharmaceuticals administered by measuring the ion current.

[0006] In recent years, as described in Patent Documents 1 to 3, an artificial lipid bilayer is formed, an ion channel is introduced therein, and the effects of various pharmaceuticals are confirmed to develop pharmaceuticals.

Prior Art Documents

Patent Documents

[0007] [Patent Document 1] Special Publication No. 2010-513332 [Patent Document 2] Japanese Patent Publication No. 2012-81405 [Patent Document 3] Japanese Patent Publication No. 2017-158464 [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] Ion channels come in various types, such as potassium channels, sodium channels, calcium channels, and chlorine channels, depending on the type of ion they pass through. These differences in type affect the way ionic current flows and its magnitude, and these characteristics also change depending on the reagents used in the test.

[0009] The magnitude and flow of ion current are determined by analyzing the measured ion current data using a specific algorithm to calculate the degree of opening and closing of ion channels. However, the type of algorithm used must be changed depending on the flow and magnitude of the ion current to obtain accurate calculation results. If the calculation results are incorrect, the effects of the drug cannot be properly certified.

[0010] Furthermore, creating an appropriate algorithm is time-consuming and laborious, and the algorithm program itself tends to be large in size. Therefore, a computer with a large capacity is required to store multiple types of algorithm programs and perform their respective analyses.

[0011] The present invention has been made in view of the above, and its objective is to provide an analysis method that can perform analysis in a short time by appropriately providing analysis means that require a huge amount of computation for the analysis of current data. [Means for solving the problem]

[0012] The present invention relates to a method for analyzing ion currents flowing through an ion channel, and includes an ion current measurement step of measuring the ion current with respect to at least one artificial cell membrane chip; an ion current data storage step of storing the measured ion current data; a transmission step of sending the stored ion current data to a server via a network; an analysis step of analyzing the ion current data on the server using a predetermined analysis method; and an analysis result storage step of storing the analyzed results on the server. The ion current measurement step and the ion current data storage step are performed in an ion current measuring device, and the server is connected to at least one of the ion current measuring devices via a network.

[0013] There may be multiple servers, and the ion current measuring device may select one of the servers to perform the transmission step.

[0014] The server stores multiple algorithms for the predetermined analysis method, and one of them may be selected for analysis.

[0015] The analysis condition modification device connected to the server may further include the step of modifying the analysis conditions of the algorithm.

[0016] Preferably, the server includes a data storage unit for storing the ion current data, a data analysis unit for analyzing the ion current data sent from the data storage unit using a predetermined analysis method, an analysis method selection unit for selecting one of the predetermined analysis methods from a plurality of predetermined analysis methods and causing the data analysis unit to perform the analysis, and a result storage unit for storing the analyzed results.

[0017] The analysis results transmission step may further include sending the analysis results stored on the server to the ion current measuring device via the network.

[0018] The ion current analysis system of the present invention is an ion current analysis system that analyzes the ion current flowing through an ion channel, and includes an ion current measurement device and a server connected to the ion current measurement device via a network. The ion current measurement device has a measurement unit that measures the ion current for at least one artificial cell membrane chip, and a processing unit that processes the measured value of the ion current, converts it into ion current data, stores the ion current data, and transmits the ion current data to the server. The server analyzes the ion current data by a predetermined analysis method.

Advantages of the Invention

[0019] In the present invention, since the ion current measurement system and the server that analyzes the ion current data are connected via a network, the high-capacity and high-speed computing power required for analysis can be easily used separately from the ion current measurement system, and appropriate analysis can be performed in a short time.

Brief Description of the Drawings

[0020] [Figure 1] FIG. 1 is a schematic diagram showing a configuration for analyzing an ion current according to an embodiment. [Figure 2] FIG. 2 is a schematic diagram showing a configuration of an ion current measurement system according to an embodiment. [Figure 3] FIG. 3 is a schematic diagram showing a configuration of a server according to an embodiment. [Figure 4] FIG. 4 is a diagram showing the current waveform of an ion current. [Figure 5] FIG. 5 is a diagram showing a regression model. [Figure 6] FIG. 6 is a schematic diagram showing a configuration of a server according to another embodiment. [Figure 7] FIG. 7 is a schematic diagram showing a configuration for analyzing an ion current according to another embodiment.

Embodiments for Carrying Out the Invention

[0021] Embodiments of the present invention will be described in detail below with reference to the drawings. The following description of preferred embodiments is essentially illustrative and is not intended to limit the present invention, its applications, or its uses.

[0022] (Embodiment 1) The ion current analysis system according to Embodiment 1 comprises an ion current measurement system 100 and a server 200, as shown in Figure 1. The ion current measurement system 100 includes an ion current measuring device 20 that measures ion current on an artificial cell membrane chip 10, as shown in Figure 2. The server 200 has the configuration shown in Figure 3.

[0023] As shown in Figure 2, an artificial cell membrane 15 made of a lipid bilayer is formed on the artificial cell membrane chip 10. The artificial cell membrane 15 mimics a biological cell membrane and is artificially formed in two adjacent recesses provided on the artificial cell membrane chip 10, as described in Patent Document 2.

[0024] The method for forming the artificial cell membrane 15 is as follows: First, an organic solvent (oil) in which lipid molecules are dispersed is placed into two recesses. The two recesses are separated by a partition wall having through-pores. Next, water containing ions is dropped into the two recesses. As a result, lipid molecules are arranged around the water mass 14, and a lipid monolayer 12 is spontaneously formed. Then, at the through-pores where the liquids of the two recesses come into contact, the lipid monolayers 12 overlap to form a lipid bilayer, thus forming the artificial cell membrane 15. One of the two recesses mimics the inside of a living cell, and the other mimics the outside of a living cell.

[0025] In addition to ions, the water mass 14 contains dispersed proteins 13, which are precursors to ion channels 11. When proteins 13 attach to the artificial cell membrane 15, ion channels 11 are formed.

[0026] The ion channel 11 is a passage that penetrates the artificial cell membrane 15, connecting the two water masses 14, 14 located in the two recesses. In the ion channel 11, ions move from one water mass 14 to the other. The ion channel 11 is an ion passage in the artificial cell membrane 15. Examples of ions include potassium ions and sodium ions.

[0027] The ion channel 11 opens and closes. When the ion channel 11 opens, ions move between the two water masses 14, and since ions have an electric charge, an ionic current I flows due to this movement. When the ion channel 11 closes, there is no ion movement, so an ionic current I should not flow. However, as will be described later, even when the ion channel is closed, some kind of current is measured to be flowing between the two water masses 14.

[0028] The ion current analysis system of this embodiment obtains analysis results by the ion current analysis method described below.

[0029] The ion current measuring device 20 comprises a measuring unit 22 and a processing unit 24. The measuring unit 22 is an ammeter, and a known ammeter can be used. The measuring unit 22 is connected in series to both ends of the ion channel 11 (one water mass 14 side and the other water mass 14 side) and measures the ion current I flowing through the ion channel 11. The measuring unit 22 also has a function to apply a command voltage to the ion channel 11.

[0030] The processing unit 24 is connected to the measurement unit 22 and processes the current value measured by the measurement unit 22, such as amplifying it, removing noise, and converting it to digital data, to make it suitable for analysis in the analysis step described later, and saves that current data (current data saving step).

[0031] The processing unit 24 is built into the main body of the ion current measuring device 20 and preferably includes a computer. The computer in the processing unit 24 includes, for example, a processor mounted on a circuit board, a memory device that stores software for operating the processor, and a data storage unit that stores current data. Furthermore, it has a transmission unit that sends the stored current data to the server 200, either in the computer itself or in a device connected to the computer in the processing unit 24. As shown in Figure 1, the ion current measuring device 20 included in the ion current measuring system 100 transmits current data from the transmission unit to the server 200 via the network (transmission step). At this time, information about the measured artificial cell membrane chip 10, such as the type of ions in the water mass 14, and the names and concentrations of reagents used in the test, is transmitted as chip data along with the current data. The processing unit 24 also instructs the measurement unit 22 on the conditions for applying the command voltage to apply the command voltage to the ion channel 11, and therefore transmits the command voltage information to the server 200.

[0032] As shown in Figure 3, the server 200 includes a data storage unit 210, a data analysis unit 220, an analysis method selection unit 230, and a results storage unit 240. Current data of ion current transmitted from the ion current measurement system 100 via the network is stored in the data storage unit 210. Next, the current data is sent from the data storage unit 210 to the data analysis unit 220. The data analysis unit 220 performs analysis of the current data using the algorithm of the analysis method selected by the analysis method selection unit 230 (regression model described later) (analysis step). The analyzed results are stored in the results storage unit 240 (analysis result storage step). The analysis results are transmitted to a predetermined location as needed, for example, a data storage device connected to the ion current measurement system 100 as shown in Figure 1.

[0033] Next, we will explain the waveform of the ion current.

[0034] Figure 4 shows the current data 40 for the ion current I in which the current waveform 50 appears. In Figure 4, the horizontal axis represents time t, and the vertical axis represents the value of the ion current I. The unit of time is, for example, [s]. The unit of ion current I is, for example, [A]. The current waveform 50 is a collection of sets of data for time t and data for ion current I.

[0035] In the current waveform 50, the ion current I includes the leakage current value IL as the base current value and the peak current value IP. The leakage current value IL corresponds to the value of the ion current I when the ion channel 11 is closed. Even when the ion channel 11 is closed, the ion current I does not become completely zero, but flows a small amount through the ion channel 11 by leaking through the artificial cell membrane 15. For this reason, the leakage current value IL is slightly greater than zero.

[0036] The magnitude of the leakage current value IL in the ion current I is determined in proportion to the magnitude of the command voltage applied to the ion channel 11. If the applied command voltage is at a negative potential, the leakage current value IL in the ion current I will also be a negative value.

[0037] The peak current value IP is greater than the leakage current value IL in absolute value. The peak current value IP corresponds to the value of the ion current I when ion channel 11 is open. When ion channel 11 is open, a large amount of ion current I flows through ion channel 11. Therefore, the peak current value IP is greater than the leakage current value IL in absolute value. As shown in Figure 4, the ion current I alternates between the leakage current value IL and the peak current value IP. The leakage current value IL is not perfectly constant, but fluctuates randomly within the range of noise σ. The peak current value IP is not perfectly constant, but fluctuates randomly within the range of noise σ.

[0038] When ion channel 11 changes from closed to open, that is, it takes time for the ion current I to reach the peak current IP from the leakage current IL, by a first time constant τo. When ion channel 11 changes from open to closed, that is, it takes time for the ion current I to reach the leakage current IL from the peak current IP, by a second time constant τc.

[0039] The ionic current I persists at the leakage current value IL for a closed duration Tc. The closed durations Tc at the leakage current values ​​IL for the first to fourth valleys are denoted by Tc1, Tc2, Tc3, and Tc4. The total closed duration Tc for the period in question is the sum of Tc1 to Tc4. That is, Tc = Tc1 + Tc2 + Tc3 + Tc4.

[0040] The ion current I is maintained at a peak current value IP for an open duration To. The open durations To at the peak current values ​​IP of the first to fourth peaks are denoted by To1, To2, To3, and To4. The total open duration To for the period is the sum of To1 to To4. That is, To = To1 + To2 + To3 + To4.

[0041] The open probability Po is an indicator that represents the open state of ion channel 11. The open probability Po is the ratio of the open duration To of ion channel 11 to the period of time under consideration. The open probability Po can be roughly obtained as To / (Tc+To) (Po=To / (Tc+To)).

[0042] The closure probability Pc is an indicator that represents the open / closed state of ion channel 11. The closure probability Pc is the ratio of the closed duration Tc of ion channel 11 to the period of time under consideration. The closure probability Pc can be roughly obtained as Tc / (Tc+To) (Pc=Tc / (Tc+To)).

[0043] The sum of the open probability Po and the closed probability Pc is 1 (Po + Pc = 1). If one of the open probability Po or the closed probability Pc is determined, the other is also determined. Determining the open probability Po and determining the closed probability Pc are essentially the same thing. The open probability Po is a major indicator used to evaluate the effect of a reagent on the opening and closing of the ion channel 11 when it is added to the artificial cell membrane chip 10. Therefore, it is important to accurately determine the open probability Po.

[0044] The following explains how to determine the open-circuit probability Po from the current waveform 50.

[0045] The period in question includes not only the closed duration Tc and the open duration To, but also the first time constant τo and the second time constant τc. In order to accurately determine the open probability Po, the first time constant τo and the second time constant τc must be allocated to either the closed duration Tc or the open duration To.

[0046] For example, a suitable threshold IA can be set for the ion current I. The time when the ion current I is less than the threshold IA can be allocated to the closed duration Tc, and the time when the ion current I is greater than the threshold IA can be allocated to the open duration To.

[0047] For a human, a threshold IA can be set visually each time, midway between the leakage current value IL and the peak current value IP, for a given current waveform 50. This allows a human to accurately determine the open probability Po, taking into account the first time constant τo and the second time constant τc.

[0048] However, it is difficult for a computer to automatically determine the accurate open probability Po based on the current waveform 50. A computer cannot even recognize the leakage current value IL and the peak current value IP, even if the current waveform 50 is provided. Therefore, the computer cannot appropriately set a threshold IA between the leakage current value IL and the peak current value IP for each given current waveform 50. Furthermore, the influence of noise σ also makes it difficult for the computer to recognize the leakage current value IL and the peak current value IP.

[0049] While it is conceivable to pre-fix the threshold value IA to an appropriate predetermined value, the characteristics of the current waveform 50 vary each time depending on the type of ion channel 11, the magnitude of the command voltage applied to the ion channel 11, or the type of ions passing through the ion channel 11. For example, both the leakage current value IL and the peak current value IP may increase or decrease (the entire current waveform 50 may shift upward or downward). Therefore, if the threshold value IA is pre-fixed to an appropriate predetermined value, both the leakage current value IL and the peak current value IP in the current waveform 50 may increase or decrease compared to the threshold value IA, making it impossible to determine an accurate open probability Po.

[0050] Therefore, different current waveforms 50 with varying shapes and sizes are observed depending on the type of ion channel 11, the magnitude of the command voltage applied to the ion channel 11, or the type of ions passing through the ion channel 11. By using the regression model described below for each current waveform 50, we decided to create analysis algorithms that correspond to the type of ions passing through the ion channel 11. This makes it possible to prepare multiple analysis algorithms, for example, separate analysis algorithms for each type of ion passing through. As an example of an algorithm, we can give the "method for determining the opening and closing of an ion channel by threshold discrimination".

[0051] (Regression model) Figure 5 shows the regression model M, which is the algorithm according to this embodiment. The regression model M is stored in the server 200; specifically, the regression model M is stored in the server 200.

[0052] The regression model M is a supervised machine learning model. The trained regression model is the algorithm that actually performs the analysis of the ion current data. Specific regression models M include, for example, ridge regression, GDBT (Gradient Boosting Decision Tree), multilayer perceptron (MLP), CNN (Convolutional Neural Network) models, and Transformer models.

[0053] The regression model M is trained as follows: The regression model M uses known ion current I current data and known mathematical parameters 70 as training data. The known mathematical parameters 70 correspond to the known current data.

[0054] During the training of the regression model M, known current data is provided as training data to the input layer of the regression model M, and known mathematical parameters 70 are provided as training data to the output layer of the regression model M.

[0055] For example, a regression model M uses a known current waveform 50 and known mathematical parameters 70 as training data. In this case, the known mathematical parameters 70 correspond to the known current waveform 50. The known current waveform 50 is provided as training data to the input layer of the regression model M, and the known mathematical parameters 70 are provided as training data to the output layer of the regression model M.

[0056] The mathematical parameters 70 are input variables corresponding to current data (current waveform 50). Known current data (current waveform 50) are generated by numerical simulation based on known mathematical parameters 70. Numerous mathematical parameters 70 are set while changing the conditions of the mathematical parameters 70. For each mathematical parameter 70 with different conditions, corresponding current data (current waveform 50) is generated. In this way, a large number of sets of current data (current waveform 50) and mathematical parameters 70 are prepared according to the conditions. Therefore, the algorithm according to this embodiment can also be described as a regression model M with pairs of sets of current data (current waveform 50) and mathematical parameters 70.

[0057] The mathematical parameter 70 contains information about the open / closed state of the ion channel 11. The open / closed state of the ion channel 11 refers to the state of whether the ion channel 11 is open or closed, and the degree to which it is open or closed. Specifically, the mathematical parameter 70 contains information about the open probability Po, which is an index representing the open / closed state of the ion channel 11.

[0058] More specifically, the mathematical parameter 70 includes, as information relating to the open probability Po of the ion channel 11, a leakage current value IL, a peak current value IP, a first time constant τo from the leakage current value IL to the peak current value IP, a second time constant τc from the peak current value IP to the leakage current value IL, a closed duration Tc at the leakage current value IL, and an open duration To at the peak current value IP.

[0059] Furthermore, the mathematical parameter 70 may include the open probability Po itself as information about the open probability Po of the ion channel 11.

[0060] The mathematical parameter 70 may include, as information regarding the opening probability Po of the ion channel 11, the number of opening / closing events D (the number of times the ion channel 11 opens and closes during the target period), the opening / closing timing E (the time when the ion channel 11 opens and closes), the closing duration Tc for each opening / closing event (e.g., Tc1 to Tc4), and the opening duration To for each opening / closing event (e.g., To1 to To4).

[0061] Since known current waveforms 50 are used as training data for the input layer, it is preferable to provide these known mathematical parameters 70 (items in parentheses in Figure 5) to the output layer.

[0062] The data analysis unit 220 of the server 200 executes the regression model M as follows: The data analysis unit 220 outputs mathematical parameters 70 corresponding to the input current data by inputting the current data (current waveform 50) related to the ion current I detected by the measurement unit 22 and transmitted to the server 200 into the regression model M. The data analysis unit 220 uses the regression model M on the server 200 to input the detected current data (current waveform 50) related to the ion current I into the regression model M. The data analysis unit 220 obtains the mathematical parameters 70 (corresponding to the current data (current waveform 50)) output by the regression model M.

[0063] As mathematical parameters 70 corresponding to the current data (current waveform 50), information regarding the open probability Po (open / closed state) of the ion channel 11 is output.

[0064] As described above, the mathematical parameters 70 corresponding to the current waveform 50 are output as follows: leakage current value IL, peak current value IP, first time constant τo, second time constant τc, closed duration Tc, open duration To, and open probability Po itself. Furthermore, as mathematical parameters 70 corresponding to the current waveform 50, the number of switching events D, switching timing E, closed duration Tc for each switching event (e.g., Tc1 to Tc4), and open duration To for each switching event (e.g., To1 to To4).

[0065] The data analysis unit 220 analyzes the state of the ion channel 11 based on the output mathematical parameters 70. Specifically, the data analysis unit 220 analyzes the open / closed state of the ion channel 11 based on the output mathematical parameters 70.

[0066] More specifically, the data analysis unit 220 determines the open probability Po of the ion channel 11 based on the output mathematical parameters 70. Since specific numerical values ​​are given as mathematical parameters 70, the data analysis unit 220 can easily determine the open probability Po.

[0067] For example, the validity (reliability) of the mathematical parameter 70 obtained from the regression model M can be confirmed by comparing the open probability Po obtained using the threshold IA described above with the open probability Po given as a mathematical parameter 70 by the regression model M.

[0068] Alternatively, the data analysis unit 220 may determine the open probability Po based on mathematical parameters 70 corresponding to the current waveform 50 (see Figure 4).

[0069] When based on mathematical parameters 70 corresponding to the current waveform 50, the open probability Po given by the regression model M as the mathematical parameter 70 may be applied directly.

[0070] The mathematical parameters 70 obtained in this way and the open probability Po of the ion channel 11 calculated based on the mathematical parameters 70 are stored in the result storage unit 240.

[0071] The regression model M is not merely a dataset of known current data and known mathematical parameters 70, but a learning model. Because the regression model M is a learning model, even if the current data input to the regression model M at runtime is in a complex form (for example, even if the noise σ of the current waveform 50 is large as shown in Figure 4), the regression model M, whose accuracy has been refined through learning, will output reliable and reasonable mathematical parameters 70.

[0072] The above set of mathematical parameters 70 is obtained by selecting a specific "set of ion channel 11 type, command voltage magnitude, etc." (hereinafter referred to as "set of ion channel, measurement conditions, etc."), measuring the ion current with the ion current measuring device 20, obtaining current data (current waveform 50), and inputting this as known data into the regression model M (<Learning> in the upper part of Figure 5). By selecting a different set of ion channel, measurement conditions, etc. and performing the analysis using the regression model M in the same way, a different set of mathematical parameters 70 can be obtained.

[0073] In this embodiment, multiple sets of ion channels, measurement conditions, etc., are prepared, and multiple regression models M corresponding to each are prepared. These are multiple analysis algorithms. Along with the current data (current waveform 50), information on the artificial cell membrane chip 10 measured by the measurement unit 22 (chip data) and command voltage information are also transmitted to the server 200. Therefore, the analysis method selection unit 230 may select which analysis algorithm, i.e., which set of mathematical parameters 70 is used to create the regression model M, to analyze the current data (current waveform 50) transmitted to the server, based on the chip data and command voltage information, or a specific set of ion channels, measurement conditions, etc., may be specified in advance.

[0074] To perform ion current analysis using a regression model M at a sufficient speed (for example, a speed at which the analysis can be completed in about the same amount of time as the ion current measurement), it is necessary to use a high-capacity computer capable of high-speed calculations. This is partly because the data size of the ion current data (current waveform 50) is large. Such computers are expensive and bulky, and while a computer for server 200 would qualify as such a high-capacity computer, the computer equipped in the ion current measuring device 20 is insufficient in terms of both capacity and calculation speed. In this embodiment, the ion current measuring device 20 is responsible for measuring the ion current and transmitting the ion current measurement data to the server 200, while the server 200 is responsible for the analysis of the ion current. Therefore, the ion current measuring device 20 can be configured to be suitable for ion current measurement and inexpensive, and the analysis can be performed at high speed by the server 200. Moreover, since the data is transmitted from the ion current measuring device 20 to the server 200 via a network, the installation locations of the ion current measuring device 20 and the server 200 can be freely selected. Furthermore, in parallel with acquiring ion current measurement data by the ion current measuring device 20, the server 200 can perform analysis of already acquired measurement data.

[0075] (Embodiment 2) The ion current analysis system and ion current analysis method according to Embodiment 2 differ from Embodiment 1 in that, as shown in Figure 6, the analysis method selection unit 230 of the server 200 is instructed to change the analysis conditions from an analysis condition changing device 300 located outside the server 200. All other configurations and methods are the same as in Embodiment 1. Therefore, the differences between Embodiment 2 and Embodiment 1 will be explained below.

[0076] For example, when transmitting ion current data from the ion current measurement system 100 to the server 200, the operator of the ion current measurement system 100 selects an appropriate regression model M from several regression models M learned under different conditions, taking into account the characteristics of the artificial cell membrane chip 10 that was measured. Then, the operator specifies the appropriate regression model M to the analysis method selection unit 230 by sending a selection signal to the server 200 using the analysis condition change device 300, thereby allowing the analysis to be performed using that regression model M. The data analysis unit 220 then performs the analysis of the ion current data using the specified regression model M.

[0077] Furthermore, when the analysis condition change device 300 sends the change in analysis conditions to the server 200, it is not only possible to select one algorithm from multiple algorithms as described above, but also to add, rewrite (update), or delete some or all of the mathematical parameters 70. For example, a new regression model M may be added, or, when using the "method for determining the opening and closing of ion channels by threshold discrimination" as the algorithm, a specific threshold may be specified, or multiple thresholds may be made selectable.

[0078] In this embodiment, the analysis algorithm used by the data analysis unit 220 can be easily and appropriately changed to a different algorithm or partially modified using the analysis condition change device 300, depending on the ion current data. This also achieves the same effects as in Embodiment 1.

[0079] (Embodiment 3) The ion current analysis system and ion current analysis method according to Embodiment 3 differ from Embodiment 1 in that, as shown in Figure 7, it uses multiple ion current measurement systems 101, 102, and 103 and multiple servers 201 and 202 to perform ion current analysis. Other configurations and methods, such as the method of measuring ion current within the ion current measurement system and the method of analyzing ion current within the server, are the same as in Embodiment 1. Therefore, the differences between Embodiment 3 and Embodiment 1 will be explained below.

[0080] In this embodiment, ion current is measured by three separate systems: ion current measurement system A101, ion current measurement system B102, and ion current measurement system C103. Then, the ion current is analyzed by two separate servers: server α201 and server β202. In Figure 7, ion current measurement systems A101 and B102 are connected to one server α201, and ion current measurement system C103 is connected to one server β202.

[0081] Ion current measurement systems A101 and B102 may simultaneously transmit ion current measurement data to server α201, or only one of them may transmit data, and there may also be times when neither transmits data. If server α201 has sufficient capacity and processing power, it can perform simultaneous analysis even when data is transmitted from both systems simultaneously. Alternatively, if only one of the two systems transmits data to the server, a server with the same capacity and processing power as in Embodiment 1 may be used.

[0082] Furthermore, ion current measurement system A101 and / or ion current measurement system B102 may select server β202 and transmit ion current measurement data (connected by dashed lines in Figure 7). Similarly, ion current measurement system C103 may select server α201 and transmit ion current measurement data (connected by dashed lines in Figure 7). The choice of which server to select may be determined, for example, by the type of algorithm stored in each server, by selecting the server that is not currently performing analysis, or by the size of the server's capacity and computing power.

[0083] The method for determining which server to send data to can be, for example, determined by the operator of the ion current measurement system based on the server's storage algorithm and operating status, or it can be determined through communication between the ion current measurement system and the server. Alternatively, a separate management device may be installed to manage the connections between the three ion current measurement systems 101, 102, and 103 and the two servers 201 and 202, and this management device may make the determination.

[0084] In this embodiment, each of the multiple ion current measurement systems is configured to connect to multiple servers, making it possible to select a server capable of performing appropriate analysis depending on the conditions of the artificial cell chip being measured (such as a combination of ion channels and measurement conditions). Furthermore, since only some of the multiple ion current measurement systems may be performing measurements, it becomes possible to analyze ion current measurement data from a large number of ion current measurement systems compared to the number of servers.

[0085] (Other embodiments) The embodiments described above are illustrative examples of the present invention, and the present invention is not limited to these examples. These examples may be combined with or partially replaced with well-known, conventional, or prior art. Modified inventions that would be easily conceived by a person skilled in the art are also included in the present invention.

[0086] Multiple regression models may be prepared, and the regression model used for analysis may be changed depending on the "combination of ion channels, measurement conditions, etc." In this case, the choice of which regression model to use may be selected using an analysis condition changing device.

[0087] A server may be a computer with a physically independent hardware configuration, or it may be a virtual computer environment within a larger computer. Alternatively, it may be a server as a single virtual environment built across multiple physical servers.

[0088] Alternatively, a histogram may be used for analysis instead of the current waveform. The histogram shows the frequency for each ion current value and is converted from the current waveform.

[0089] Embodiments 2 and 3 may be combined. Furthermore, if the server has sufficient capacity and processing speed, a single server may analyze data from multiple ion current measurement systems.

[0090] In Embodiment 3, the number of ion current measurement systems and the number of servers are not particularly limited, as long as each is two or more. Alternatively, the number of ion current measurement systems and servers may be at least two of each, or only one of each.

[0091] In the above embodiment, the analysis results are sent from the server to the ion current measurement system, but the configuration may also involve sending them to a system other than the ion current measurement system, such as a system for managing and analyzing the analysis results. Alternatively, instead of sending the analysis results from the server, the system may be configured to retrieve them from the server as needed. [Explanation of Symbols]

[0092] Ionic current 10 Artificial cell membrane chips 11 Ion Channels 20 Ion current measuring device 22 Measurement section 24 Processing Unit 40 Current Data 100 Ion Current Measurement System 101 Ion Current Measurement System A 102 Ion Current Measurement System B 103 Ion Current Measurement System C 200 servers 201 Server α 202 Server β 210 Data Storage Unit 220 Data Analysis Department 230 Analysis Method Selection Section 240 Result storage section 300 Analysis Condition Changer

Claims

1. A method for analyzing ion currents flowing through ion channels, An ion current measurement step for measuring the ion current of at least one artificial cell membrane chip, An ion current data storage step for storing the measured ion current data, A transmission step of sending the saved ion current data to a server via a network, The analysis step involves analyzing the ion current data in the server using a predetermined analysis method, A step of saving analysis results, which involves saving the analyzed analysis results to the server. It includes, The ion current measurement step and the ion current data storage step are performed in an ion current measuring device. A method for analyzing ion current, wherein the server is connected via a network to at least one of the ion current measuring devices.

2. The method for analyzing ion current according to claim 1, wherein there are multiple servers, and the ion current measuring device selects one of the servers to perform the transmission step.

3. The ion current analysis method according to claim 1, wherein the server stores multiple algorithms for the predetermined analysis method, and one of them is selected for analysis.

4. The method for analyzing ion current according to claim 3, further comprising the step of a device for changing analysis conditions connected to the server for changing the analysis conditions of the algorithm.

5. The server comprises a data storage unit for storing the ion current data, a data analysis unit for analyzing the ion current data sent from the data storage unit using a predetermined analysis method, an analysis method selection unit for selecting one of the predetermined analysis methods from a plurality of predetermined analysis methods and causing the data analysis unit to perform the analysis, and a result storage unit for storing the analyzed results. A method for analyzing ion current according to claim 1, comprising the following:

6. The method for analyzing ion current according to claim 1, further comprising an analysis result transmission step of sending the analysis results stored on the server to the ion current measuring device via a network.

7. An ion current analysis system for analyzing ion currents flowing through ion channels, The system comprises an ion current measuring device and a server connected to the ion current measuring device via a network. The ion current measuring device includes a measuring unit that measures the ion current of at least one artificial cell membrane chip, and a processing unit that processes the measured value of the ion current, converts it into ion current data, stores the ion current data, and transmits it to the server. The server is an ion current analysis system that analyzes the ion current data using a predetermined analysis method.

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