Information processing device, information processing method, and program

Abstract

To provide an information processing device capable of effectively supporting acquisition of a chemical material.SOLUTION: An information processing device includes: a data input unit that receives an input of data transmitted from a user terminal; a model creation unit that creates a prediction model based on the data input via the data input unit; an extraction unit that performs search using the prediction model and extracts a target chemical material; and a connection unit that connects the user terminal to a product information site of the target chemical material extracted by the extraction unit. The model creation unit may create the prediction model by performing machine learning of a correspondence between a chemical structure of a substance as the data and a property of the substance.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] Patent Document 1 discloses a technique of searching for manufacturing conditions using a prediction model and determining, as the manufacturing conditions of a product, the manufacturing conditions that satisfy a predetermined criterion.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For example, experimental conditions can be searched using the above prediction model, and appropriate experimental conditions can be extracted. However, the burden of obtaining chemical materials such as reagents that conform to the extracted experimental conditions may increase.

[0005] Therefore, in one aspect, an object of the present invention is to provide an information processing apparatus or the like that can effectively assist in obtaining chemical materials.

Means for Solving the Problems

[0006] In one aspect, a data input unit that receives input of data transmitted from a user terminal, a model creation unit that creates a prediction model based on the data input via the data input unit, an extraction unit that performs a search using the prediction model and extracts chemical materials, a connection unit that connects the user terminal to a product information site of the chemical materials extracted by the extraction unit, An information processing apparatus is provided that includes

Advantages of the Invention

[0007] On one hand, according to the present invention, the acquisition of chemical materials can be effectively supported.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Embodiments for Carrying Out the Invention

[0009] FIG. 1 is a diagram showing a configuration example of an information processing system having the information processing apparatus of the present embodiment.

[0010] As shown in FIG. 1, the information processing system includes an information processing apparatus 10 as a server and a user terminal 20. The information processing apparatus 10 provides data analysis in the chemical field and machine learning cloud services to the user who uses the user terminal 20. In addition, the information processing apparatus 10 provides a service to assist the user in obtaining necessary chemical materials. In the present disclosure, "chemical materials" include, in addition to reagents used in chemical analysis, experiments, research and development, inspections, etc., industrial chemicals and industrial raw materials used in the manufacture of various products. Furthermore, "chemical materials" include drugs and pharmaceuticals used in the fields of biochemistry and medicine. Hereinafter, an example of assisting in obtaining reagents as "chemical materials" will be mainly described, but "chemical materials" are not limited to the examples.

[0011] In the example of FIG. 1, the information processing system further includes a database 30 for identifying purchasable reagents and a sales server 40 for providing a service for purchasing reagents. Note that the data stored in the database 30 and the service provided by the sales server 40 can be appropriately changed according to the type of "chemical materials".

[0012] As shown in FIG. 1, the information processing apparatus 10 includes a data input unit 11 that receives the input of data transmitted from the user terminal 20, a model creation unit 12 that creates a prediction model based on the data input via the data input unit 11, an extraction unit 13 that performs a search using the prediction model and extracts a target reagent, a connection unit 14 that connects the user terminal 20 to the product information site of the target reagent extracted by the extraction unit 13, and a storage unit 15 that stores various data such as input data from the user, the prediction model, and prediction results using the prediction model.

[0013] A program corresponding to the functions of the data input unit 11, the model creation unit 12, the extraction unit 13, and the connection unit 14 is installed in the information processing apparatus 10. Further, a program corresponding to the function of connecting to the information processing apparatus 10, the user interface, and other functions necessary for receiving the services provided by the information processing apparatus 10 is installed in the user terminal 20.

[0014] FIG. 2 is a diagram showing an example of the hardware configuration of the information processing apparatus shown in FIG. 1.

[0015] In the example shown in FIG. 2, the information processing apparatus 10 includes a CPU (Central Processing Unit) 111, a GPU (Graphics Processing Unit) 111A, a RAM (Random Access Memory) 112, a ROM (Read Only Memory) 113, an auxiliary storage device 114, a drive device 115, and a communication interface 117 connected by a bus 119, and a wired transceiver 118A and a wireless transceiver 118B connected to the communication interface 117.

[0016] The GPU 111A performs various processes described later.

[0017] The auxiliary storage device 114 is, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and constitutes the storage unit 15 together with the RAM 112 and the ROM 113.

[0018] The wired transceiver unit 118A includes a transceiver unit capable of communicating using a wired network.

[0019] The wireless transceiver unit 118B is a transceiver unit capable of communicating using a wireless network. The wireless network may include a wireless communication network of a mobile phone, the Internet, a VPN (Virtual Private Network), a WAN (Wide Area Network), etc. Further, the wireless transceiver unit 118B may include a near-field communication (NFC) unit, a Bluetooth (registered trademark) communication unit, a Wi-Fi (Wireless-Fidelity, registered trademark) transceiver unit, an infrared transceiver unit, etc.

[0020] The wired transceiver unit 118A and the wireless transceiver unit 118B constitute, for example, the connection unit 14 shown in FIG. 1.

[0021] Note that the information processing apparatus 10 may be connectable to a recording medium 116. The recording medium 116 stores a predetermined program. The program stored in this recording medium 116 is installed in the auxiliary storage device 114 etc. via the drive device 115. The installed predetermined program can be executed by the CPU 111 of the information processing apparatus 10. For example, the recording medium 116 may be a recording medium that optically, electrically, or magnetically records information, such as a CD (Compact Disc)-ROM, a flexible disk, a magneto-optical disk, etc., or a semiconductor memory that electrically records information, such as a ROM, a flash memory, etc. Note that the recording medium 116 does not include a carrier wave.

[0022] Next, the operation of the information processing system will be described.

[0023] The data input unit 11 receives the input of data transmitted from the user terminal 20. The data is used as learning data for constructing a prediction model.

[0024] The content of the data received by the data input unit 11 can be arbitrary, but the data includes the chemical structure of the substance and the properties of the substance. Further, the data received by the data input unit 11 includes the conditions of the experimental data and the results associated with the conditions.

[0025] The model creation unit 12 creates a prediction model based on the data input via the data input unit 11. The algorithm for creating the prediction model can be arbitrary. For example, the model creation unit 12 can use the data input via the data input unit 11 as learning data and create a prediction model through machine learning using feature quantities.

[0026] For example, when the purpose is molecular design, the model creation unit 12 uses the chemical structure of the substance and the physical properties (characteristics) of the substance input via the data input unit 11 as learning data to create a prediction model. In this case, the prediction model is created as a learned model that takes the chemical structure of the substance as input data and outputs the physical properties of the substance as prediction data. The data format of the chemical structure as input data can be arbitrary. For example, it may be a character string according to the SMILES notation.

[0027] Further, for example, the model creation unit 12 performs machine learning on the experimental conditions input via the data input unit 11 and the experimental results associated with the conditions to create a prediction model. In this case, the prediction model is created as a learned model that takes the experimental conditions as input data and outputs the experimental results as prediction data.

[0028] Specifically, in the case of an experiment for material design, for example, the model creation unit 12 uses, as learning data, experimental conditions including a raw material formulation recipe and physical properties of the composite obtained with the formulation recipe, and creates a prediction model. The raw material formulation recipe is, for example, in the case of material design, information including the chemical structure and mixing ratio of the raw materials. The data format of the chemical structure of the raw materials is arbitrary, but may be, for example, a character string according to the SMILES notation. Also, when the chemical structure of the raw materials such as industrial raw materials is not clarified, the raw materials may be selected based on information on physical properties and characteristics values such as heat resistance and flexibility disclosed by the raw material manufacturer or the like. In such a case, the raw material formulation recipe can be the selection, combination, and mixing ratio of the raw materials having the physical properties and characteristics values.

[0029] The extraction unit 13 performs a search using the prediction model created by the model creation unit 12.

[0030] For example, the extraction unit 13 sequentially inputs the chemical structure of a substance as input data to the prediction model, and searches for a chemical structure such that the physical properties of the substance output as prediction data are good. Further, the extraction unit 13 extracts, as a target reagent, a substance having a chemical structure such that the physical properties of the substance are good.

[0031] Also, the extraction unit 13 sequentially inputs the experimental conditions as input data to the prediction model, and searches for a chemical structure such that the result of the experiment output as prediction data is good. Further, the extraction unit 13 extracts, as a target reagent, a substance used under experimental conditions such that the result of the experiment is good.

[0032] The search algorithm in the extraction unit 13 is arbitrary, but for example, by determining the next candidate as input data based on the output prediction data, the search may be repeated until desirable prediction data is obtained.

[0033] The description method of the chemical structure handled by the extraction unit 13 may be the SMILES notation.

[0034] The target reagent extracted by the extraction unit 13 can be limited to reagents that can be purchased (obtained). For example, the extraction unit 13 can access an existing database 30 (Fig. 1) that stores purchasable reagents and target only the reagents within the database 30 for search. In this case, for example, the chemical structure of the substance input into the prediction model can be limited to the chemical structures of the reagents within the database 30. Also, for example, the experimental conditions input into the prediction model can be limited to those using the reagents within the database 30.

[0035] Note that the database 30 can be prepared, for example, by a seller or reagent manufacturer that sells reagents, or a service provider using the information processing device 10 can prepare it by receiving data from such a seller or reagent manufacturer. The data format indicating the chemical structure of the reagent specified by the database 30 is arbitrary, but for example, it may be a character string according to the SMILES notation. By matching the description method of the chemical structure handled by the extraction unit 13 with the description method of the chemical structure of the reagent specified by the database 30, it becomes easier to search for reagents within the database 30.

[0036] The extraction unit 13 may perform a search within a range not limited to purchasable reagents. In this case, reagents that are not purchasable are also extracted as target reagents. However, this extraction result can be useful information for the user. Also, even when the target reagent is not purchasable, the user can purchase a reagent that is similar to the target reagent, for example, has an approximate chemical structure and is purchasable, and use it in the experiment.

[0037] The search results obtained by the extraction unit 13 are used by the user in any form. For example, based on the search results, the user can determine the materials (including reagents) and conditions to be used in the next experiment, and the new materials and conditions are applied to the next experiment by the user. Further, the new materials and conditions, and the corresponding experimental results are input again via the data input unit 11 and reflected in the prediction model created by the model creation unit 12. Thereby, the accuracy of the prediction model is improved, and more refined search results can be obtained in the extraction unit 13. By repeating such a series of operations, the user can efficiently search for desirable materials and experimental conditions.

[0038] The extraction unit 13 may extract a single reagent or a plurality of reagents as the target reagent. When extracting a plurality of reagents, the extraction unit 13 may attach information such as a priority order to the target reagent to be extracted based on the output value of the prediction model.

[0039] The connection unit 14 connects the user terminal 20 to a sales server 40 (Fig. 1) that provides a product information site for purchasing the target reagent extracted by the extraction unit 13.

[0040] For example, the connection unit 14 performs a predetermined display on the display screen of the user terminal 20 in a manner that allows the user terminal 20 to be connected to the product information site by a simple operation (for example, a click operation) of the user on the display screen of the user terminal 20. The user can access the product information site (sales server 40) only by operating the display screen of the user terminal 20.

[0041] The connection unit 14 may distinguish pages and the like within the product information site that is the connection destination according to the type of the target reagent extracted by the extraction unit 13. For example, when the pages within the product information site differ depending on the attributes of the reagent (for example, substrate, solvent, reactant, additive, etc.) or the chemical structure, the connection unit 14 can connect the user terminal 20 to the page corresponding to the target reagent.

[0042] In addition, when it is possible to connect to a plurality of product information sites, the connection unit 14 can select a product information site from which the target reagent can be purchased and connect the user terminal 20 to the site.

[0043] According to this embodiment, since the user can easily access the product information site of the reagent, the burden of obtaining the reagent can be effectively reduced. For example, based on the experimental data at hand, the user can create a prediction model, search for materials, determine the materials to be considered next based on the search results, and purchase them. By repeating such a series of operations in a cycle using the service provided by the information processing apparatus 10, the most appropriate material can be finally selected from a huge number of candidates. According to this embodiment, not only can the reagent required for the experiment be easily determined, but also the reagent can be easily purchased. Therefore, the labor involved in purchasing the reagent can be reduced, and the time required to complete the experiment can be shortened.

[0044] As described above, according to this embodiment, since the connection unit for connecting the user terminal to the product information site of the target chemical material extracted by the search unit is provided, it is possible to effectively assist the user in obtaining the target chemical material. Although each embodiment has been described in detail above, the present invention is not limited to a specific embodiment, and various modifications and changes are possible within the scope described in the claims. Also, it is possible to combine all or a plurality of the components of the above-described embodiments.

Explanation of Reference Numerals

[0045] 10 Information processing apparatus 11 Data input unit 12 Model creation unit 13 Extraction unit 14 Connection unit 15 Storage unit

Claims

1. A data input unit that receives the input of data transmitted from a user terminal; A model creation unit that creates a prediction model based on the data input via the data input unit; An extraction unit that performs a search using the prediction model and extracts a target chemical material; A connection unit that connects the user terminal to a product information site of the target chemical material extracted by the extraction unit; An information processing apparatus comprising the above.

2. The information processing apparatus according to claim 1, wherein the model creation unit performs machine learning on the correspondence between the chemical structure of a substance as the data and the properties of the substance, and creates the prediction model.

3. The information processing apparatus according to claim 1, wherein the data is experimental data, and the model creation unit performs machine learning on the correspondence between the experimental conditions and the experimental results of the experimental data, and creates the prediction model.

4. The information processing apparatus according to claim 1, wherein the extraction unit extracts, based on a database of chemical materials, a chemical material that can be purchased through the product information site as the target chemical material.

5. A data input step of receiving the input of data transmitted from a user terminal; A model creation step of creating a prediction model based on the data input via the data input step; An extraction step of performing a search using the prediction model and extracting a target chemical material; A connection step of connecting the user terminal to a product information site of the target chemical material extracted by the extraction step; An information processing method comprising the above.

6. A data input step of receiving the input of data transmitted from a user terminal; A model creation step of creating a prediction model based on the data input via the data input step; An extraction step of performing a search using the prediction model to extract a target chemical material; A connection step of connecting the user terminal to a product information site of the target chemical material extracted in the extraction step; A program for causing a computer to execute.

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