Patent Publication Number: US-2021174509-A1

Title: Examination Method, Examination System, and Non-Transitory Computer Readable Recording Medium

Description:
BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present disclosure relates to an examination method for examining the efficacy of a drug against bacteria, an examination system including a processor having a program for examining the efficacy installed thereon, and a non-transitory computer readable recording medium having the program recorded thereon. 
     Description of the Background Art 
     In order to select an antibacterial drug, a susceptibility test of bacteria such as germs and fungi is conducted. “PLOS ONE”, 11 (2), Feb. 12, 2016 by Yoshimi Matsumoto, Shouichi Sakakihara, Andrey Grushnikov, Kazuma Kikuchi, Hiroyuki Noji, Akihito Yamaguchi, Ryota lino, Yasushi Yagi, and Kunihiko Nishino describes that an image of a sample obtained by bringing a drug into contact with bacteria is captured and the obtained image is processed using image analysis software, to thereby obtain the number of cells and the like from the image and determine a minimum inhibitory concentration (MIC) of the drug against the bacteria. 
     SUMMARY OF THE INVENTION 
     However, according to the conventional method, information indicating whether or not the drug is effective against the bacteria is only obtained from the image of the sample obtained by bringing the drug into contact with the bacteria, and obtainment of other information has not been considered. 
     The present disclosure has been made to solve the above-described problem, and an object of the present disclosure is to obtain not only information indicating whether or not a drug is effective against bacteria but also additional information about an effective drug. 
     An examination method according to the present disclosure is an examination method for examining efficacy of a drug against bacteria, the examination method including: obtaining a plurality of samples, each of the plurality of samples being obtained by bringing a drug into contact with the bacteria; obtaining an image data set by capturing an image of each of the plurality of samples, the plurality of samples being different from each other in at least one condition of a drug type, a drug concentration and exposure time of the bacteria to the drug; determining the efficacy of the drug against the bacteria based on the obtained image data set; and obtaining information indicating a difference in the efficacy of the drug due to being different in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug, by extracting an image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples including the drug determined as being effective, and comparing one image with another among the image data subset in accordance with a prescribed criterion. 
     An examination system according to the present disclosure includes a processor having a program for examining efficacy of a drug against bacteria based on an image data set installed thereon, the image data set being obtained by capturing an image of each of a plurality of samples, each of the plurality of samples being obtained by bringing a drug into contact with the bacteria, the plurality of samples being different from each other in at least one condition of a drug type, a drug concentration and exposure time of the bacteria to the drug. The program causes the processor to perform the functions of: determining a minimum inhibitory concentration of the drug against the bacteria; obtaining information indicating a difference in the efficacy of the drug due to being different in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug; and outputting an examination result list that shows the minimum inhibitory concentration and the information indicating the difference in the efficacy. 
     A non-transitory computer readable recording medium according to the present disclosure has the above-described program stored thereon. 
     The foregoing and other objects, features, aspects and advantages of the present disclosure will become more apparent from the following detailed description of the present disclosure when taken in conjunction with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a flow of examination according to the present embodiment. 
         FIG. 2  is a plan view of a culture plate. 
         FIG. 3  shows a schematic configuration of an examination device including a microscope camera according to the present embodiment. 
         FIG. 4  is a schematic view showing one example of a hardware configuration of an information processing device. 
         FIG. 5  is a block diagram showing one example of a functional configuration of the information processing device. 
         FIG. 6  shows an example of comparison based on a drug type. 
         FIG. 7  shows an example of comparison based on a drug concentration. 
         FIG. 8  shows an example of comparison based on the exposure time. 
     
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     An embodiment of the present disclosure will be described in detail hereinafter with reference to the drawings, in which the same or corresponding portions are denoted by the same reference characters and description thereof will not be repeated. 
     [Overview of Examination] 
       FIG. 1  shows a flow of examination according to the present embodiment. The examination according to the present embodiment includes a sample preparation step S 100 , an image capturing step S 200 , an analysis step S 300 , and an output step S 400 . 
     In sample preparation step S 100 , a test solution including bacteria is injected into a culture plate  10  on which drugs are arranged, and the drugs are brought into contact with the bacteria. Culture plate  10  into which the test solution is injected is housed in an incubator  60 . 
     Culture plate  10  has a plurality of flow paths. Each flow path is provided with an observation point and the drugs of different types are arranged at the respective observation points. In addition, different amounts of the drugs are arranged at the respective observation points. By supplying the test solution including the bacteria to each flow path, the drugs are brought into contact with the bacteria. 
     In image capturing step S 200 , an image of each observation point on culture plate  10  is captured using a microscope camera  140 , to thereby obtain image data of the samples. In addition, in image capturing step S 200 , culture plate  10  is housed in incubator  60  and an image of culture plate  10  is captured every prescribed time period. Culture plate  10  is housed in incubator  60  for, for example, three hours after the drugs are brought into contact with the bacteria. Then, assuming that the time of bringing the drugs into contact with the bacteria is 0 minute, culture plate  10  is taken out of incubator  60  and an image of culture plate  10  is captured at each of 0 minute, 60 minutes, 90 minutes, 120 minutes, 150 minutes, and 180 minutes. 
     In analysis step S 300 , an information processing device  200  obtains drug susceptibility information based on the images of the plurality of samples (sample images) different in conditions obtained in image capturing step S 200 . “Different in conditions” herein specifically means being different in at least one condition of a drug type, a drug concentration and exposure time of the bacteria. That is, in image capturing step S 200 , an image data set is obtained by capturing an image of each of the plurality of samples. 
     The drug susceptibility information is additional information about a drug that is effective against the bacteria, and is information indicating a difference in the efficacy of the drug due to being different in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug. The drug susceptibility information includes, for example, superiority or inferiority of the efficacy among the drugs, a relationship between the drug concentration and the efficacy, a relationship between the exposure time and the efficacy of the drug, and the like. 
     Analysis step S 300  includes an efficacy determination step S 320  and a drug susceptibility information obtaining step S 340 . In efficacy determination step S 320 , the efficacy of the drug against the bacteria is determined by, for example, inputting the sample images into a determination model trained by machine learning. In efficacy determination step S 320 , the efficacy of the drug may be determined by comparing the image data using a known image processing technique. 
     In drug susceptibility information obtaining step S 340 , the drug susceptibility information is obtained by extracting an image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples including the drug determined as being effective in efficacy determination step S 320 , and comparing one image with another among the image data subset in accordance with a prescribed criterion. 
     In output step S 400 , the drug susceptibility information is output as, for example, an analysis report. The analysis report may be output in the form of paper, or may be output in the form of presentation on a display. 
     Analysis step S 300  may further include a step of determining a minimum inhibitory concentration (MIC) based on the information obtained in efficacy determination step S 320 . 
     The analysis report may include the MIC. That is, the analysis report may show the MIC and the drug susceptibility information. 
     [Configuration of Culture Plate] 
       FIG. 2  is a plan view of the culture plate. Culture plate  10  includes a plate-shaped member  12  and a flow path structure. The flow path structure includes an opening portion  13 , an opening  14 , a micro flow path  15 , an observation point  16 , and an opening  17 . 
     Opening  14  is a portion provided in opening portion  13  and allowing opening portion  13  and micro flow path  15  to communicate with each other. Namely, opening  14  is connected to one end of micro flow path  15 . Using a fluid pressure, the test solution including the bacteria is injected from opening  14  into micro flow path  15 . On culture plate  10  shown in  FIG. 2 , four micro flow paths  15  are arranged radially around opening  14 . 
     Micro flow path  15  is configured such that the test solution can flow therethrough. Micro flow path  15  extending from opening  14  branches off to a plurality of micro flow paths  15 . The test solution introduced from opening  14  flows through branched micro flow paths  15 . In the present embodiment, one micro flow path  15  branches off to fourteen micro flow paths  15 . 
     Observation point  16  is provided partway through branched micro flow path  15 . Micro flow path  15  allows the test solution introduced from opening  14  to flow to observation point  16 . 
     Observation point  16  has the drug arranged thereat, and is connected to micro flow path  15  to store the test solution introduced from micro flow path  15 . At observation point  16 , the test solution reacts with the drug. The drug is, for example, an antibacterial drug. The drug may be solid, or may be liquid. The drug is preliminarily placed at observation point  16 . That is, the drug is placed at observation point  16  before the test solution flows into observation point  16 . Observation point  16  is formed to have a rectangular parallelepiped shape. One side of observation point  16  has a length of, for example, 10 μm to 10 mm. 
     In  FIG. 2 , fifty-six (=14×4) observation points  16  are formed on plate-shaped member  12 . That is, in the present embodiment, when one culture plate  10  is observed, fifty-six observation points  16  are observed using an examination device  100 . Volumes of the test solution stored in fifty-six observation points  16  are the same as each other. In contrast, the types and the amounts of the drugs placed at fifty-six observation points  16  may be the same as each other, or may be different from each other. Since the volumes of the test solution stored in fifty-six observation points  16  are the same as each other, a drug concentration in each observation point  16  can be changed by placing different amounts of the drugs at observation points  16 . 
     Plate-shaped member  12  is made of an acrylic resin such as a polymethyl methacrylate resin. A thickness of plate-shaped member  12  is not particularly limited, and is set at, for example, 1 mm to 6 mm. In addition, an identification code  18  for individually identifying culture plate  10  is assigned to plate-shaped member  12 . 
     Identification code  18  is not limited to an optically readable code such as a one-dimensional barcode or a two-dimensional QR code (registered trademark), and may be a code that can be read by wireless communication, such as an RF tag. Identification information indicated by identification code  18  is not limited to the serial number individually assigned to culture plate  10 , and may be the lot number assigned to culture plate  10 . 
     Culture plate  10  is made mainly of an acrylic resin. Therefore, culture plate  10  has a slight individual difference due to a difference in manufacturing condition, storage condition, environmental condition during use, or the like. When a camera having a wide depth of field is used, an image that is in focus to some extent is obtained, regardless of the slight individual difference, by focusing on the same position as a position of a focal point that is focused on when capturing an image of one culture plate  10 , and capturing an image of another culture plate  10 . However, in the examination according to the present embodiment, microscope camera  140  having an extremely narrow depth of field is used. Therefore, an in-focus image is not obtained by focusing on the same position as a position of a focal point that is focused on when capturing an image of one culture plate  10 , and capturing an image of another culture plate  10 . 
     Accordingly, in the examination according to the present embodiment using the microscope camera having an extremely narrow depth of field, information for focusing on each observation point  16  is managed, as an image capturing condition, by the identification information indicated by individual identification code  18  assigned to each culture plate  10 . 
     In addition, in the present embodiment, the number is assigned to each of fifty-six observation points  16 . The type and the amount of the drug placed at each observation point  16  can be identified by the identification information and the number of observation point  16 . 
     [Configuration of Examination Device Including Microscope Camera] 
       FIG. 3  shows a schematic configuration of the examination device including the microscope camera according to the present embodiment. Examination device  100  captures an image of each of the plurality of observation points provided on culture plate  10 . The sample obtained by bringing the drug into contact with the test solution including the bacteria is arranged at each of the plurality of observation points. 
     Examination device  100  includes a controller  120 , microscope camera  140 , a stage  160 , and a reader  180 . Controller  120  is electrically connected to microscope camera  140 , stage  160  and reader  180 . The electrically connected devices may be partly or entirely formed of one piece. 
     In order to capture an image of each observation point  16  on culture plate  10 , controller  120  controls each of microscope camera  140  and stage  160  based on the identification information read by reader  180 . 
     Microscope camera  140  includes an objective lens  142 , a focal point changing mechanism  144  and an image sensor  146 . 
     Objective lens  142  magnifies a part of culture plate  10  placed on stage  160 . Objective lens  142  is arbitrarily selected in accordance with an observation target. 
     Focal point changing mechanism  144  changes a focal point of microscope camera  140 . As one example, focal point changing mechanism  144  changes the focal point of microscope camera  140  by changing a position of objective lens  142  in an optical axis direction of objective lens  142 . 
     Image sensor  146  is a detector for capturing an image of the observation target magnified by objective lens  142 , and is, for example, a charge coupled device (CCD) image sensor, a complementary metal oxide semiconductor (CMOS) image sensor or the like. 
     Stage  160  includes an image-capturing field-of-view changing mechanism  162  and a lighting device  164 . Culture plate  10  is placed on stage  160 . Lighting device  164  is transparent lighting and irradiates stage  160  with light for observation. 
     Image-capturing field-of-view changing mechanism  162  changes an image-capturing field of view of microscope camera  140 . Image-capturing field-of-view changing mechanism  162  includes an X axis moving mechanism  162 X and a Y axis moving mechanism  162 Y. X axis moving mechanism  162 X moves culture plate  10  placed on stage  160  in an X axis direction in  FIG. 3 . Y axis moving mechanism  162 Y moves culture plate  10  placed on stage  160  in a Y axis direction in  FIG. 3 . In  FIG. 3 , a plane of stage  160  on which culture plate  10  is placed is defined as an X-Y plane, and an axis vertical to the X-Y plane is defined as a Z axis. 
     Reader  180  reads the identification information of culture plate  10 . Reader  180  is, for example, a barcode reader, a QR code (registered trademark) reader or a reader adapted to a radio frequency (RF) tag, and is selected in accordance with the type of the identification code assigned to culture plate  10 . Reader  180  transmits the read identification information to controller  120 . 
     Controller  120  reads the image capturing condition corresponding to the identification information based on the identification information from reader  180 , and controls microscope camera  140  and stage  160  based on the read image capturing condition, to capture an image of each observation point. 
     Specifically, controller  120  outputs, to image-capturing field-of-view changing mechanism  162 , location information of the observation point whose image is to be captured. In accordance with the output location information, Image-capturing field-of-view changing mechanism  162  moves culture plate  10 , such that the observation point whose image is to be captured is located within the image-capturing field of view of microscope camera  140 . 
     In addition, controller  120  provides a focal point changing instruction to focal point changing mechanism  144  in accordance with the image capturing condition. At this time, controller  120  outputs, to focal point changing mechanism  144 , location information when microscope camera  140  focuses on the observation point whose image is to be captured. Focal point changing mechanism  144  sets the focal point of microscope camera  140  in accordance with the output location information. 
     Controller  120  provides an image capturing instruction to image sensor  146  when the image-capturing field of view and the focal point of microscope camera  140  are set, and obtains image data as an observation result. 
     Controller  120  is communicably connected to information processing device  200 . Controller  120  transmits an observation result  240  including image data  242  to information processing device  200 . In addition to image data  242 , observation result  240  includes identification information  244  of culture plate  10  whose image was captured, observation point information  246  indicating which observation point  16  image data  242  corresponds to, and the time (image capturing time  248 ) at which image data  242  was obtained. 
     Controller  120  and information processing device  200  may be connected to be capable of exchanging various types of data. A communication method between controller  120  and information processing device  200  may be a wireless communication method using a wireless local area network (LAN) and the like, or may be a wired communication method using a universal serial bus (USB) and the like. Controller  120  may have the function of information processing device  200 . 
     [Hardware Configuration of Information Processing Device] 
       FIG. 4  is a schematic view showing one example of a hardware configuration of the information processing device. As one example, information processing device  200  is formed in accordance with a general-purpose computer architecture. 
     As main components, information processing device  200  includes a processor  202 , a memory  204 , a communication interface (I/F)  206 , a display unit  208 , and an input unit  210 . These components are communicably connected to each other through a bus  212 . Processor  202  is typically a processing unit such as a central processing unit (CPU) or a multi processing unit (MPU). Processor  202  reads and executes a program stored in memory  204 , to thereby implement each process of information processing device  200  described below. In the example of  FIG. 4 , information processing device  200  includes a single processor. However, information processing device  200  may include a plurality of processors. 
     Memory  204  is implemented by a nonvolatile memory such as a random access memory (RAM), a read only memory (ROM) and a flash memory. Memory  204  stores a program executed by processor  202 , data used by processor  202 , or the like. For example, memory  204  stores an examination program  205  for examining the efficacy of the drugs. 
     Memory  204  may be a compact disc-read only memory (CD-ROM), a digital versatile disk-read only memory (DVD-ROM), a universal serial bus (USB) memory, a memory card, a flexible disk (FD), a hard disk, a solid state drive (SSD), a magnetic tape, a cassette tape, a magnetic optical disc (MO), a mini disc (MD), an integrated circuit (IC) card (excluding a memory card), an optical card, a mask ROM, or an EPROM, as long as memory  204  can record the program in a non-transitory manner in the form of being readable by information processing device  200  which is one type of computer. 
     Communication I/F  206  is an interface for communicating with controller  120  of examination device  100 . 
     Display unit  208  is implemented by a liquid crystal display panel or the like. Display unit  208  displays, for example, a result of calculation made by processor  202 , and the like. Input unit  210  is implemented by a mouse, a keyboard or the like. Input unit  210  receives a user operation. Information processing device  200  may include a touch panel in which display unit  208  and input unit  210  are integrated. 
     [Functional Configuration of Information Processing Device] 
       FIG. 5  is a block diagram showing one example of a functional configuration of the information processing device. Each function shown in  FIG. 5  is implemented by processor  202  executing examination program  205  stored in memory  204 . 
     Information processing device  200  includes a determination unit  22 , a sample information extraction unit  24 , a comparison unit  26 , a report generation unit  28 , and an output unit  29 . 
     Sample information extraction unit  24  extracts sample information  250  corresponding to each observation result  240  (image data  242 ). Specifically, sample information extraction unit  24  obtains sample information  250  from a database  23 , based on identification information  244  and observation point information  246  included in observation result  240 . Sample information  250  includes type information  252 , concentration information  254  and time information  256 . 
     Type information  252  is information that can identify a drug type. Concentration information  254  is information that can identify a drug concentration. Concentration information  254  may be information indicating an amount of the drug arranged at observation point  16 . 
     Database  23  includes the information that can identify the type and the amount of the drug arranged at each observation point  16  of each culture plate  10 . Sample information extraction unit  24  obtains type information  252  and concentration information  254  from database  23 , based on identification information  244  and observation point information  246 . 
     The information that can identify the type and the amount of the drug, which is included in database  23 , is generated, for example, when the drug is arranged at each observation point  16 . The timing of arranging the drug may be the time of shipment of culture plate  10 , or may be the time of execution of the examination after culture plate  10  is shipped. When the drug is arranged at the time of shipment, the information that can identify the type and the amount of the drug, which is included in database  23 , is prestored in a server or the like that can communicate with information processing device  200 . When the drug is arranged at the time of execution of the examination, the information that can identify the type and the amount of the drug is generated by the user operating input unit  210  to input the type and the amount of the drug arranged at each observation point  16 . 
     Time information  256  indicates the time of injection of the test solution into culture plate  10  indicated by identification information  244 . Sample information extraction unit  24  can obtain the exposure time of the bacteria by subtracting the time indicated by time information  256  from image capturing time  248 . Time information  256  is stored in database  23  for each identification information  244 . 
     When the test solution is injected by a machine, time information  256  is recorded by the machine for injection. When the test solution is injected by the user, time information  256  is input by the user through input unit  210 . 
     Determination unit  22  is a model trained by machine learning (trained model). Determination unit  22  is a trained model for determining whether or not the bacteria is resistant to the drugs in the samples. Determination unit  22  includes a feature amount extraction unit  222  and an efficacy determination unit  224 . 
     Feature amount extraction unit  222  performs preprocessing for extracting a feature amount from image data  242 . For example, feature amount extraction unit  222  extracts image data  242  of a control based on sample information  250 . The control is a standard sample, and is, for example, a sample made only of the test solution. 
     Feature amount extraction unit  222  extracts the feature amount by comparing image data  242  of the control with image data  242  of a sample other than the control. The feature amount includes, for example, a degree of extension of the bacteria with respect to the control, the number of the bacteria that increase or decrease with respect to the control, roundness of the bacteria with respect to the control, image brightness with respect to the control, image contrast with respect to the control, and the like. 
     Efficacy determination unit  224  determines whether or not the drug is effective, by inputting the feature amount extracted by feature amount extraction unit  222  into the trained model. For example, for each sample, efficacy determination unit  224  determines whether or not the growth of the bacteria is inhibited, based on the feature amount. When efficacy determination unit  224  determines that the growth of the bacteria is inhibited, efficacy determination unit  224  determines that the drug is effective. When efficacy determination unit  224  determines that the growth of the bacteria is not inhibited, efficacy determination unit  224  determines that the drug is not effective. 
     In addition, efficacy determination unit  224  determines the MIC based on the determination result. That is, determination unit  22  including efficacy determination unit  224  has the function of determining the MIC. 
     Efficacy determination unit  224  determines the efficacy of the drug based on the determined MIC. The efficacy of the drug is expressed, for example, by S (susceptible) and R (resistant). S indicates that the drug is effective against the bacteria. R indicates that the bacteria is resistant to the drug and the drug is not effective against the bacteria. Efficacy determination unit  224  determines the efficacy for each of the drugs of a plurality of types. 
     Determination unit  22  may include a neural network. In this case, determination unit  22  does not necessarily need to include feature amount extraction unit  222 . 
     The trained model is generated based on, for example, a plurality of pieces of training data including an image indicating a state in which the bacteria is resistant to the drug and an image indicating a state in which the bacteria is not resistant to the drug. 
     Comparison unit  26  extracts a plurality of comparison targets from observation result  240  in accordance with a comparison condition, compares feature amounts of the extracted comparison targets, and generates drug susceptibility information  260 . 
     Comparison unit  26  receives information indicating an effective drug type from efficacy determination unit  224  as a determination result. Comparison unit  26  identifies samples of the effective drugs, of the plurality of samples, based on the information indicating the effective drug type. In addition, comparison unit  26  extracts samples serving as comparison targets from the samples of the effective drugs, based on the comparison condition. That is, comparison unit  26  extracts the image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples including the drug determined as being effective. 
     Drug susceptibility information  260  is information about the efficacy of the drug and includes, for example, the concentration dependence of the drug, an antibacterial activity for each drug type, whether or not the drug has an initial antibacterial activity against the bacteria, or the like. 
     Report generation unit  28  generates a report for suggesting a drug suitable as an antibacterial drug, a drug administration plan and the like, based on generated drug susceptibility information  260  and the MIC included in the determination result by determination unit  22 . The report includes at least an examination result list that shows the MIC and drug susceptibility information  260 . The examination result list shows, for example, the presence or absence of the efficacy for each drug type. For the effective drug, the examination result list also shows the concentration dependence of the drug, the presence or absence of the initial antibacterial activity of the drug and the like together with the MIC. The examination result list may include information about a difference in antibacterial activity for each drug type. 
     Output unit  29  outputs the report including the examination result list generated by report generation unit  28  to, for example, display unit  208 . A destination of the generated report is not limited to display unit  208 . The destination may be, for example, a printer, another information processing device (processor) communicably connected to information processing device  200 , a storage device such as a server communicably connected to information processing device  200 , or the like. 
     [Comparison Condition] 
     The comparison condition will be described with reference to  FIGS. 6 to 8 .  FIG. 6  shows an example of comparison based on the drug type.  FIG. 7  shows an example of comparison based on the drug concentration.  FIG. 8  shows an example of comparison based on the exposure time. 
     (Comparison Based on Drug Type) 
     Referring to  FIG. 6 , when “samples having the MIC” are set as the extraction condition, samples having the MIC are extracted from the samples of the effective drugs. The samples having the MIC include the drug determined as being effective and are different from each other in drug type and. That is, the image data subset is extracted from among the obtained image data set of the plurality of samples including the drug determined as being effective and being different from each other in drug type. The MIC is obtained in the course of the process performed by efficacy determination unit  224 . The exposure time of each of the extracted samples is preferably the same. 
     As to the samples having the MIC, of the identified drug types, feature amounts extracted from image data  242  of the samples are compared. The feature amount refers to, for example, the number of the bacteria that increase or decrease with respect to the control. By comparing the feature amounts, degrees of antibacterial activity of the drug types can be compared. That is, one image among the extracted image data subset is compared with another image among the extracted image data subset. 
     As a result, a difference in antibacterial activity between drug types is obtained as drug susceptibility information  260 . For example, when a drug B has higher antibacterial activity than a drug A, it is expected that drug B is suitable as a drug to be administered. 
     In order to obtain the difference in antibacterial activity between drug types, determination may be made based on a plurality of types of feature amounts. Comparison unit  26  may extract a feature amount different from the feature amount obtained by the preprocessing performed by determination unit  22 , to obtain the difference in antibacterial activity between drug types. 
     (Comparison Based on Drug Concentration) 
     Referring to  FIG. 7 , when “samples of drugs different in drug concentration” are set as the extraction condition, samples of drugs different in drug concentration are extracted from the samples of the effective drugs. For example, based on type information  252  and time information  256 , samples including drug A and exposed to the bacteria for the specific exposure time are extracted from the samples of the effective drugs. As a result, the samples of drug A having the specific exposure time and having the different concentrations are extracted. That is, the image data subset is extracted from among the obtained image data set of the plurality of samples including the drug determined as being effective and being different from each other in drug concentration. 
     Feature amounts extracted from image data  242  of the extracted samples are compared. The feature amount refers to, for example, the number of the bacteria that increase or decrease with respect to the control. By comparing the feature amounts, the concentration dependence of the antibacterial activity is known. For example, when an amount of decrease in the number of the bacteria becomes larger as the concentration becomes higher, it is determined that the drug has the concentration dependence. In contrast, when the amount of decrease in the number of the bacteria does not change even if the concentration becomes higher, it is determined that the drug does not have the concentration dependence. Comparison unit  26  determines the concentration dependence for each drug. That is, comparison unit  26  compares one image with another among the extracted image data subset. 
     For example, when it is determined that drug A has the concentration dependence, it can be seen that the antibacterial activity becomes higher by increasing an amount of drug A to be administered. In contrast, when it is determined that drug B does not have the concentration dependence, it can be seen that the antibacterial activity does not change even if an amount of drug B to be administered is increased. 
     In order to determine the concentration dependence of the antibacterial activity, determination may be made based on a plurality of types of feature amounts. Comparison unit  26  may extract a feature amount different from the feature amount obtained by the preprocessing performed by determination unit  22 , to determine the concentration dependence of the antibacterial activity. 
     (Comparison Based on Exposure Time) 
     Referring to  FIG. 8 , when “samples of drugs different in exposure time” are set as the extraction condition, samples of drugs different in exposure time are extracted from the samples of the effective drugs. That is, the image data subset is extracted from among the obtained image data set of the plurality of samples including the drug determined as being effective and being different from each other in exposure time. For example, based on type information  252  and concentration information  254 , samples including drug A, having different exposure times, and having a common drug concentration are extracted from the samples of the effective drugs. As a result, the samples of drug A having the different exposure times and having the specific concentration are extracted. 
     Feature amounts extracted from image data  242  of the extracted samples are compared. The feature amount refers to, for example, the number of the bacteria that increase or decrease with respect to the control. By comparing the feature amounts, it is known whether or not the antibacterial activity appears from the beginning of exposure. Specifically, when the bacteria greatly decrease with respect to the control from the beginning of exposure, it is estimated that the antibacterial activity appears from the beginning of exposure, and thus, it is determined that the drug has the initial antibacterial activity. Comparison unit  26  determines, for each drug, whether or not the drug has the initial antibacterial activity. That is, comparison unit  26  compares one image with another among the extracted image data subset. 
     For example, when it is determined that drug A has the initial antibacterial activity, it can be seen that the effect of administering drug A can be recognized in the beginning of administration. In contrast, when it is determined that drug B has the initial antibacterial activity, it can be seen that the effect of administering drug B cannot be recognized in the beginning of administration. 
     In order to determine whether or not the drug has the initial antibacterial activity, determination may be made based on a plurality of types of feature amounts. Comparison unit  26  may extract a feature amount different from the feature amount obtained by the preprocessing performed by determination unit  22 , to determine whether or not the drug has the initial antibacterial activity. 
     [Aspects] 
     It is understood by a person skilled in the art that the above-described embodiment and modifications thereof are provided as specific examples of the following aspects. 
     (Clause 1) 
     An examination method according to one aspect is an examination method for examining efficacy of a drug against bacteria. The examination method comprising: obtaining a plurality of samples, each of the plurality of samples being obtained by bringing a drug into contact with the bacteria; obtaining an image data set by capturing an image of each of the plurality of samples, the plurality of samples being different from each other in at least one condition of a drug type, a drug concentration and exposure time of the bacteria to the drug; determining the efficacy of the drug against the bacteria based on the obtained image data set; and obtaining information indicating a difference in the efficacy of the drug due to being different in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug, by extracting an image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples including the drug determined as being effective, and comparing one image with another among the image data subset in accordance with a prescribed criterion. 
     With such a configuration, the information indicating the difference in the efficacy of the drug is obtained for the drug determined as being effective, by comparing the image data of the plurality of samples including the drug determined as being effective, in accordance with the prescribed criterion. 
     (Clause 2) 
     The examination method according to clause 1 further comprises determining a minimum inhibitory concentration of the drug against the bacteria based on a result obtained by determining the efficacy of the drug against the bacteria. 
     With such a configuration, the effective drug can be identified based on the minimum inhibitory concentration. 
     (Clause 3) 
     The examination method according to clause 2 further comprises presenting the obtained information indicating the difference in the efficacy, together with the minimum inhibitory concentration. 
     With such a configuration, the two information is presented together, and thus, the user can identify the effective drug and check the difference in the efficacy about the identified drug at the same time. 
     (Clause 4) 
     In the examination method according to any one of clauses 1 to 3, in the obtaining information indicating a difference in the efficacy, a degree of the efficacy based on the drug type is obtained by extracting the image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples different from each other in the drug type, and comparing one image with another among the image data subset. 
     With such a configuration, the degree of the efficacy based on the drug type is obtained, and thus, selection of the drug type to be administered can be assisted. 
     (Clause 5) 
     In the examination method according to any one of clauses 1 to 4, in the obtaining information indicating a difference in the efficacy, a relationship between a difference in the drug concentration and a degree of the efficacy is obtained by extracting the image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples different from each other in the drug concentration, and comparing one image with another among the image data subset. 
     With such a configuration, the relationship between the difference in the drug concentration and the degree of the efficacy is obtained, and thus, selection of the concentration of the drug to be administered can be assisted. 
     (Clause 6) 
     In the examination method according to any one of clauses 1 to 5, in the obtaining information indicating a difference in the efficacy, initial susceptibility of the drug is obtained by extracting the image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples different from each other in the exposure time of the bacteria, and comparing one image with another among the image data subset. 
     With such a configuration, the initial susceptibility of the drug is obtained, and thus, an indicator of the timing of determining a drug administration result can be provided. 
     (Clause 7) 
     In the examination method according to any one of clauses 1 to 6, in the determining the efficacy of the drug, the efficacy of the drug against the bacteria is determined by inputting the image data of the plurality of samples different in the condition into a determination model trained by machine learning. 
     (Clause 8 ) 
     In the examination method according to clause 7, the determining the efficacy of the drug includes extracting a feature amount about the bacteria included in the samples. 
     (Clause 9) 
     In the examination method according to clause 7, the determination model includes a convolutional neural network. 
     (Clause 10 ) 
     In the examination method according to any one of clauses 1 to 9, the plurality of samples are obtained by supplying a test solution including the bacteria to each of a plurality of flow paths formed in a device, the drug being arranged in each of the plurality of flow paths. 
     With such a configuration, the plurality of samples can be obtained simply by supplying the test solution to the flow paths, and thus, the samples can be easily prepared. 
     (Clause 11) 
     A program according to one aspect is a program for examining efficacy of a drug against bacteria based on an image data set, the image data set being obtained by capturing an image of each of a plurality of samples, each of the plurality of samples being obtained by bringing a drug into contact with the bacteria, the plurality of samples being different from each other in at least one condition of a drug type, a drug concentration and exposure time of the bacteria to the drug. The program causes the processor to perform the functions of: determining a minimum inhibitory concentration of the drug against the bacteria; obtaining information indicating a difference in the efficacy of the drug due to being different in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug; and outputting an examination result list that shows the minimum inhibitory concentration and the information indicating the difference in the efficacy. 
     With such a configuration, additional information, i.e., the information indicating the difference in the efficacy of the drug due to being different in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug, is obtained. Furthermore, the examination result list that shows the information indicating the difference in the efficacy of the drug and the minimum inhibitory concentration is output, and thus, the user can identify the effective drug and check the difference in the efficacy about the identified drug at the same time. 
     (Clause 12) 
     A destination of the examination result list includes at least one of a printer, a display device, a processor different from the processor that performs the above-described program, and a storage device communicably connected to the processor that performs the above-described program. 
     (Clause 13) 
     An examination system according to one aspect includes the processor that performs the program as recited in clause 11 or 12. 
     (Clause 14) 
     The examination system according to clause 13 may further comprise an image capturing device that captures an image of each of the plurality of samples, the plurality of samples being different from each other in the at least one condition of the drug type, the drug concentration and the exposure time of the bacteria to the drug, to thereby obtain image data. In this case, the function of determining a minimum inhibitory concentration includes the function of determining the minimum inhibitory concentration based on the image data. 
     (Clause 15) 
     In the examination system according to clause 13 or 14, the function of obtaining information indicating a difference in the efficacy includes the function of obtaining the information indicating the difference in the efficacy, by extracting an image data subset from among the obtained image data set of the plurality of samples, the image data subset being for samples including the drug determined as being effective, and comparing one image with another among the image data subset in accordance with a prescribed criterion. 
     (Clause 16) 
     A computer readable medium according to one aspect has the program as recited in clause 11 or 12 stored therein in a non-transitory manner. 
     While the embodiment of the present disclosure has been described, it should be understood that the embodiment disclosed herein is illustrative and non-restrictive in every respect. The scope of the present disclosure is defined by the terms of the claims and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.