Analysis method for ion current and ion current analysis system

Abstract

Provided is an analysis method whereby an analysis can be performed in a short time by appropriately providing a means of analyzing an enormous amount of calculations required for analyzing current data. Specifically, an analysis method for an ion current flowing through an ion channel comprises: an ion current measurement step of measuring an ion current for at least one artificial cell membrane chip; an ion current data storage step of storing the measured ion current data; a transmission step of transmitting the stored ion current data to a server via a network; an analysis step of analyzing the ion current on the server by a predetermined analysis method; and an analysis result storage step of storing the analyzed analysis result on the server, wherein the ion current measurement step and the ion current data storage step are executed on ion current measurement devices, and the server is connected to the at least one of the ion current measurement devices via the network.

Description

Method for Analyzing Ion Current and Ion Current Analysis System

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

[0002] Cells that make up an organism, mitochondria, Golgi bodies, endoplasmic reticulum, etc. present inside 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] One type of such transmembrane protein is an ion channel. An ion channel is a general term for proteins that passively allow ions to permeate. 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 the resting membrane potential 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 the physiological activity effect is manifested. Therefore, it is 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.

[0007] Japanese Patent Publication No. 2010-513332, Japanese Patent Application Laid-Open No. 2012-81405, Japanese Patent Application Laid-Open No. 2017-158464

[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.

[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 present invention provides an ion current analysis system for analyzing ion currents flowing through ion channels, comprising an ion current measuring device and a server connected to the ion current measuring device via a network, wherein the ion current measuring device includes a measuring unit for measuring ion currents targeting at least one artificial cell membrane chip and a processing unit for processing the measured ion current values, converting them into ion current data, storing the ion current data, and transmitting it to the server, and the server analyzes the ion current data using a predetermined analysis method.

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

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

[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, for example. 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, and the artificial cell membrane 15 is formed. 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 that serve as precursors to ion channels 11. When the proteins 13 attach to the artificial cell membrane 15, ion channels 11 are formed.

[0026] The ion channel 11 serves as a passage that penetrates the artificial cell membrane 15, connecting the two water masses 14, 14 located in the two recesses. Ions move from one water mass 14 to the other through the ion channel 11. 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 (later regression model) of the analysis method selected by the analysis method selection unit 230 (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 of 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 the ion channel 11 is open. When the ion channel 11 is open, a large amount of ion current I flows through the 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 a perfectly constant value, but fluctuates randomly within the range of noise σ. The peak current value IP is not a perfectly constant value, but fluctuates randomly within the range of noise σ.

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

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

[0040] The ionic current I persists at the peak current value IP for the open duration To. The open durations To at the peak current values IP of the first to fourth peaks are denoted as To1, To2, To3, and To4. The total open duration To in the target period is the sum of To1 to To4. That is, To = To1 + To2 + To3 + To4.

[0041] There is an opening probability Po as an index representing the open / closed state of the ion channel 11. The opening probability Po is the ratio of the open duration To during which the ion channel 11 is open with respect to the target period. The opening probability Po is approximately obtained by To / (Tc + To) (Po = To / (Tc + To)).

[0042] There is a closing probability Pc as an index representing the open / closed state of the ion channel 11. The closing probability Pc is the ratio of the closed duration Tc during which the ion channel 11 is closed with respect to the target period. The closing probability Pc is approximately obtained by Tc / (Tc + To) (Pc = Tc / (Tc + To)).

[0043] The sum of the opening probability Po and the closing probability Pc is 1 (Po + Pc = 1). If one of the opening probability Po and the closing probability Pc is determined, the other is also determined. Obtaining the opening probability Po and obtaining the closing probability Pc are essentially the same. The opening probability Po is a major index for evaluating what effect a reagent has on the opening and closing of the ion channel 11 when the reagent is added to the artificial cell membrane chip 10. Therefore, it is important to accurately obtain the opening probability Po.

[0044] Hereinafter, a method for obtaining the opening probability Po from the current waveform 50 will be described.

[0045] During the target period, in addition to the closed duration Tc and the open duration To, there are also a first time constant τo and a second time constant τc. In accurately obtaining 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, an appropriate threshold value IA is set for the ion current I. It is conceivable to allocate the time when the ion current I is smaller than the threshold value IA to the closed duration Tc, and the time when the ion current I is larger than the threshold value IA to the open duration To.

[0047] In the case of a human, for the given current waveform 50, the threshold value IA may be set visually each time in the middle between the leakage current value IL and the peak current value IP. Thus, in the case of a human, an accurate open probability Po considering the first time constant τo and the second time constant τc can be obtained.

[0048] However, it is difficult for a computer to automatically and accurately obtain the open probability Po based on the current waveform 50. In the first place, even if the current waveform 50 is given, the computer cannot recognize the leakage current value IL and the peak current value IP. For this reason, the computer cannot appropriately set the threshold value IA in the middle between the leakage current value IL and the peak current value IP for the given current waveform 50 each time. Also, the influence of the noise σ makes it difficult for the computer to recognize the leakage current value IL and the peak current value IP.

[0049] It is also conceivable to fix the threshold value IA in advance at an appropriate predetermined value. However, the mode of the current waveform 50 varies each time depending on the type of the 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 move upward or downward). For this reason, when the threshold value IA is fixed in advance at an appropriate predetermined value, both the leakage current value IL and the peak current value IP in the current waveform 50 may be larger or smaller than the threshold value IA, and an accurate open probability Po cannot be obtained.

[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, GDPT (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 includes 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 includes information about the open probability Po, which serves as an indicator of the open / closed state of the ion channel 11.

[0058] More specifically, the mathematical parameter 70 includes, as information relating to the opening 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 regarding the open probability Po of the ion channel 11.

[0060] The mathematical parameters 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 mathematical parameters 70 corresponding to the current waveform 50, the following are output: 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 following are output: number of opening / closing events D, opening / closing timing E, closed duration Tc for each opening / closing event (e.g., Tc1 to Tc4), and open duration To for each opening / closing 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 opening probability Po of the ion channel 11 determined 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 the "ion channel / measurement condition set"), 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 (the upper part of Figure 5, <Learning>). By selecting a different ion channel / measurement condition set and performing the same analysis using the regression model M, 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, and the server 200 is responsible for analyzing the ion current. Therefore, the ion current measuring device 20 can be configured to be suitable for measuring ion current 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. The other configurations and methods are the same as those of Embodiment 1, so 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 transmitting changes to the analysis conditions from the analysis condition changing device 300 to the server 200, in addition to selecting one algorithm from multiple algorithms as described above, some or all of the mathematical parameters 70 may be added, rewritten (updated), or deleted. 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. Furthermore, the same effects as in Embodiment 1 are achieved.

[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 a plurality of ion current measurement systems 101, 102, 103 and a plurality of servers 201, 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 analyze data simultaneously even when data is transmitted from both systems at the same time. 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 (connection by dashed line in Figure 7). Similarly, ion current measurement system C103 may select server α201 and transmit ion current measurement data (connection by dashed line 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 the 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 technologies, conventional technologies, or prior art. Modified inventions that can 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 user may select which regression model to use 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. Also, 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.

[0092] I Ion current 10 Artificial cell membrane chip 11 Ion channel 20 Ion current measuring device 22 Measurement unit 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 Server 201 Server α 202 Server β 210 Data storage unit 220 Data analysis unit 230 Analysis method selection unit 240 Result storage unit 300 Analysis condition change device

Claims

1. A method for analyzing ion current flowing through an ion channel, comprising: an ion current measurement step of measuring the ion current on 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, wherein the ion current measurement step and the ion current data storage step are performed on an ion current measuring device, and the server is connected to at least one of the ion current measuring devices via a network.

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 method for analyzing ion current according to claim 1, wherein 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 the 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.

6. The method for analyzing ion current according to claim 1, further comprising the step of transmitting analysis results, which involves 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 an ion channel, comprising an ion current measuring device and a server connected to the ion current measuring device via a network, wherein the ion current measuring device includes a measuring unit for measuring ion currents for at least one artificial cell membrane chip and a processing unit for processing the measured values ​​of the ion currents, converting them into ion current data, storing the ion current data, and transmitting it to the server, and the server analyzes the ion current data using a predetermined analysis method.

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