Non-prescription drug product monograph drug combination method and apparatus, electronic device

Abstract

The present disclosure relates to a non-prescription drug medicine monograph drug combination method and device, and an electronic device. The method comprises: determining a first target monograph in a plurality of monographs; determining a quantity range and a total number of first active ingredients to obtain a first combination number of a first target drug; determining a first characteristic of the first active ingredients, and determining a second target monograph associated with the first target monograph according to the first characteristic; determining a number of second active ingredients capable of being combined with the first active ingredients to form a second target drug in the second target monograph, and obtaining a respective second combination number according to the first combination number and the number of the second active ingredients in the second target monograph; and outputting the first combination number, the respective second combination number, and / or a total combination number of the first combination number and the respective second combination number. The embodiments of the present disclosure can efficiently and accurately determine the combination number and manner of active ingredients in any one monograph and a threshold-related monograph in a plurality of monographs.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a non-prescription drug combination method and apparatus, and electronic equipment. Background Technology

[0002] Over-the-counter (OTC) drugs are essential for self-health care, characterized by relatively low risk and suitability for self-diagnosis and medication. Countries worldwide often employ simplified review or registration pathways for OTC drug management. In the United States, Canada, and Australia, a monograph-based marketing pathway exists. In this model, regulatory agencies first evaluate the active ingredients of OTC drugs in a specific therapeutic category. For active ingredients with proven safety and efficacy over long-term use, a monograph is created for these ingredients and their corresponding conditions of use. This monograph specifies indications, conditions of use, active ingredient combinations, labeling requirements, etc. Drugs meeting the monograph requirements can be directly registered for marketing without regulatory review, or with a simplified review process, requiring only a declaration of compliance with the monograph for rapid market entry.

[0003] my country has not yet established a management model for over-the-counter (OTC) drug monographs, but this is becoming a trend. To establish my country's own monograph system, a large number of monographs (over 200,000 in the US alone) need to be analyzed. However, current technology relies on manually reading the original monograph texts and individually organizing the information. This manual approach is inefficient, and the results may vary between individuals, leading to low accuracy. Summary of the Invention

[0004] According to one aspect of this disclosure, a method for combining drugs in an over-the-counter pharmaceutical treatise is provided, the method comprising:

[0005] Based on the received first selection information, a first target monograph is determined from multiple monographs, wherein the first selection information includes monograph identification information;

[0006] Determine the range of quantities of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug;

[0007] Determine a first characteristic of the first active ingredient in the first target monograph, and determine at least one second target monograph associated with the first target monograph among a plurality of monographs based on the first characteristic;

[0008] The number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug is determined, and the number of each second combination is obtained based on the number of the first combination and the number of the second active ingredients in each second target monograph.

[0009] Output the number of the first combination, the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination.

[0010] In one possible implementation, the method further includes:

[0011] Output the range of quantities of the first active ingredient that constitutes the first target drug in the first target monograph;

[0012] If the number of target components corresponding to the received quantity setting parameter is within the quantity range, the first target combination number of the first target drug is determined and output based on the number of target components and the total number of the first active ingredients;

[0013] The number of each second target combination is determined and output based on the number of the first target combination and the number of the second active ingredients in each second target monograph.

[0014] In one possible implementation, determining the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug, includes:

[0015] The quantity range is determined based on the component content of the first target drug in the first target monograph, and the total number of the first active ingredient in the first target monograph is counted.

[0016] For each quantity in the range, a corresponding number of combinations is determined, and the numbers of each combination are summed to obtain the first number of combinations of the first target drug.

[0017] In one possible implementation, determining the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug, includes:

[0018] The first target monograph is input into a pre-trained first recognition model, and the quantity range of the first active ingredient, the total number of the first active ingredient in the first target monograph, and the number of the first combination of the first target drug are obtained based on the output of the first recognition model.

[0019] In one possible implementation, determining the first characteristic of the first active ingredient in the first target monograph includes:

[0020] The first target monograph is input into a pre-trained first recognition model, and the first feature of the first active ingredient is obtained based on the output of the first recognition model.

[0021] In one possible implementation, determining at least one second target monograph associated with the first target monograph among a plurality of monographs based on the first feature includes:

[0022] Determine the combination conditions of the active ingredients of the drugs described in each of the multiple monographs;

[0023] Based on the similarity between the first feature and the active ingredients in the combination conditions of each active ingredient, at least one second target monograph associated with the first target monograph is determined.

[0024] In one possible implementation, the method further includes:

[0025] Target information is extracted from multiple monographs according to each preset keyword to establish a basic database, which includes the mapping relationship between preset keywords and target information.

[0026] In one possible implementation, the keywords include at least one of the following: country / region, monograph name, active ingredient, indication, action category, therapeutic category, dosage form, excipient information, specification composition, minimum specification, maximum specification, dosage and administration, minimum single dose, maximum single dose, minimum daily dose, and maximum daily dose.

[0027] In one possible implementation, determining the first target monograph from among multiple monographs based on the received first selection information includes:

[0028] The first target monograph is determined in the basic database based on the received first selection information.

[0029] According to one aspect of this disclosure, a non-prescription drug combination device is provided, the device comprising:

[0030] The first determining module is configured to determine a first target monograph from multiple monographs based on received first selection information, wherein the first selection information includes monograph identification information.

[0031] The second determining module is used to determine the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, so as to obtain the first combination number of the first target drug;

[0032] The third determining module is used to determine a first characteristic of the first active ingredient in the first target monograph, and to determine at least one second target monograph associated with the first target monograph among multiple monographs based on the first characteristic;

[0033] The fourth determining module is used to determine the number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug, and to obtain the number of each second combination based on the number of the first combination and the number of the second active ingredients in each second target monograph.

[0034] The output module is used to output the number of the first combination, the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination.

[0035] According to one aspect of this disclosure, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to perform the method described above.

[0036] According to one aspect of this disclosure, a computer-readable storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement the above-described method.

[0037] This embodiment of the disclosure determines a first target monograph from multiple monographs based on received first selection information, determines the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain a first combination number of the first target drug. This allows for efficient and accurate determination of the number and manner of combinations of active ingredients in any one of the multiple monographs. Furthermore, by determining a first characteristic of the first active ingredient in the first target monograph, at least one second target monograph associated with the first target monograph is determined from the multiple monographs based on the first characteristic; and each second target monograph is determined to have combinations with the first active ingredient to form a first target drug. The number of second active ingredients in a two-target drug is obtained by considering the number of first combinations and the number of second active ingredients in each second target monograph. That is, by using the first characteristics of the first active ingredient in the first target monograph, the number and combination method of active ingredients in other second target monographs associated with the first target monograph can be efficiently and accurately identified. By outputting the number of first combinations, the number of each second combination, and / or the total number of combinations of the first combination and the number of each second combination, it is convenient to evaluate the number of first combinations, the number of each second combination, and / or the total number of combinations of the first combination and the number of each second combination in real time.

[0038] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0039] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure.

[0040] Figure 1 A flowchart of a nonprescription drug combination method according to an embodiment of this disclosure is shown.

[0041] Figure 2 A flowchart of a nonprescription drug combination method according to an embodiment of this disclosure is shown.

[0042] Figure 3 A block diagram of a nonprescription drug combination device according to an embodiment of the present disclosure is shown.

[0043] Figure 4 A block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0044] Figure 5 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0045] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0046] In the description of this disclosure, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this disclosure and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure.

[0047] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise expressly specified.

[0048] In this disclosure, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this disclosure according to the specific circumstances.

[0049] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0050] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0051] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0052] Please see Figure 1 , Figure 1 A flowchart of a nonprescription drug combination method according to an embodiment of this disclosure is shown.

[0053] like Figure 1 As shown, the method includes:

[0054] Step S11: Determine a first target monograph from multiple monographs based on the received first selection information, wherein the first selection information includes monograph identification information;

[0055] Step S12: Determine the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, so as to obtain the first combination number of the first target drug;

[0056] Step S13: Determine a first characteristic of the first active ingredient in the first target monograph, and determine at least one second target monograph associated with the first target monograph among multiple monographs based on the first characteristic;

[0057] Step S14: Determine the number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug, and obtain the number of each second combination based on the number of the first combination and the number of the second active ingredients in each second target monograph.

[0058] Step S15: Output the number of the first combination, the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination.

[0059] This embodiment of the disclosure determines a first target monograph from multiple monographs based on received first selection information, determines the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain a first combination number of the first target drug. This allows for efficient and accurate determination of the number and manner of combinations of active ingredients in any one of the multiple monographs. Furthermore, by determining a first characteristic of the first active ingredient in the first target monograph, at least one second target monograph associated with the first target monograph is determined from the multiple monographs based on the first characteristic; and each second target monograph is determined to have combinations with the first active ingredient to form a first target drug. The number of second active ingredients in a two-target drug is obtained by considering the number of first combinations and the number of second active ingredients in each second target monograph. That is, by using the first characteristics of the first active ingredient in the first target monograph, the number and combination method of active ingredients in other second target monographs associated with the first target monograph can be efficiently and accurately identified. By outputting the number of first combinations, the number of each second combination, and / or the total number of combinations of the first combination and the number of each second combination, it is convenient to evaluate the number of first combinations, the number of each second combination, and / or the total number of combinations of the first combination and the number of each second combination in real time.

[0060] This disclosure does not limit the subject of execution of the method. In some possible implementations, the method can be executed by a terminal device, a server, or other processing devices. The terminal device can be a user equipment (UE), mobile device, user terminal, terminal, handheld device, computing device, or in-vehicle device, etc. Examples of terminals include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, and wireless terminals in vehicle-to-everything (V2X) networks, etc. For example, the server can be a local server or a cloud server.

[0061] In some possible implementations, the method can be implemented by a processing component invoking computer-readable instructions stored in memory. In one example, the processing component includes, but is not limited to, a standalone processor, discrete components, or a combination of processors and discrete components. The processor may include a controller in an electronic device capable of executing instructions, and may be implemented in any suitable manner, for example, by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components. Within the processor, the executable instructions may be executed by hardware circuitry such as logic gates, switches, ASICs, programmable logic controllers, and embedded microcontrollers.

[0062] For example, a user can input first selection information via a keyboard or touchscreen. The input first selection information is transmitted to the execution entity. The execution entity executes the above method to obtain the first combination number of the first target monograph and the second combination number of each second target monograph associated with the first target monograph. It can also obtain the total number of combinations. The execution entity can transmit the above information to the outside world, for example, by displaying it on a screen or sending it to other terminals or servers.

[0063] This disclosure does not limit the specific method by which the first selection information is transmitted to the execution subject. If the input device (such as a keyboard) for the first selection information is directly connected to the execution subject, the first selection signal can be transmitted to the execution subject through an internal signal bus. If the input device for the first selection information is physically isolated from the execution subject, the first selection information can be transmitted through a communication component. For example, the communication component can be configured to facilitate wired or wireless communication between the execution subject and other devices. The execution subject can access a wireless network based on a communication standard, such as WiFi, 2G, or 3G, or a combination thereof, through the communication component. In one exemplary embodiment, the communication component receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component further includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies. Of course, the communication component can also include other short-range communication modules, such as a star-flash module.

[0064] In this disclosure, an over-the-counter (OTC) drug monograph can refer to a paper that specifies the active ingredients of an over-the-counter drug and their safety, efficacy, and other labeling information. If a drug is listed in an OTC drug monograph, the pharmaceutical company can produce and sell the OTC drug product without prior approval from the Food and Drug Administration. This disclosure does not limit the number or source of OTC drug monographs. For example, OTC drug monographs can come from multiple countries and regions such as the United States, Europe, and Australia. As an example, OTC drug monographs may include, for instance, the U.S. OTC human antacid monograph M001, an analgesic-antipyretic active ingredient monograph M013, and human topical antiflatulent monograph M002, etc.

[0065] For example, an active ingredient is a chemical substance in a drug that has an effect on the human body. In addition to active ingredients, drugs also contain excipients.

[0066] This disclosure does not limit the specific content of the first selected information, nor does it limit the specific form of the monograph identification information, as long as the selected monograph identification information can uniquely identify the monograph. For example, the monograph identification information can be a combination of the monograph's ID, code, name, and date.

[0067] This disclosure does not limit the specific implementation of step S11, which involves determining the first target monograph from multiple monographs based on the received first selection information. Those skilled in the art can refer to relevant technical implementations. For example, monograph identification information can be extracted from multiple monographs, and the similarity or matching degree between the monograph identification information in the first selection information and the monograph identification information in other monographs can be calculated. When the similarity or matching degree is 1, the monograph can be confirmed as the first target monograph, where a similarity or matching degree of 1 indicates that the two are completely identical. Of course, this disclosure does not limit the specific method for calculating the similarity or matching degree; those skilled in the art can refer to relevant technical implementations.

[0068] Please see Figure 2 , Figure 2 A flowchart of a nonprescription drug combination method according to an embodiment of this disclosure is shown.

[0069] This disclosure does not limit the specific implementation of step S12, which determines the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug. Those skilled in the art can implement this using appropriate means according to actual circumstances and needs. In one possible implementation, such as... Figure 2 As shown, step S12, which determines the quantity range of the first active ingredient constituting the first target drug in the first target monograph and the total number of the first active ingredients in the first target monograph to obtain the first combination number of the first target drug, may include:

[0070] Step S121: Determine the quantity range based on the component content of the first target drug in the first target monograph, and count the total number of the first active ingredient in the first target monograph;

[0071] Step S122: For each quantity in the quantity range, determine the corresponding number of combinations, and sum the number of combinations to obtain the first number of combinations of the first target drug.

[0072] This embodiment of the disclosure determines the quantity range based on the component content of the first target drug in the first target monograph, and counts the total number of the first active ingredients in the first target monograph. For each quantity in the quantity range, a corresponding number of combinations is determined, and the number of combinations is summed to obtain the first number of combinations of the first target drug. This can efficiently and accurately determine the quantity range of the first active ingredients that make up the first target drug in the first target monograph, as well as the total number of the first active ingredients in the first target monograph, to obtain the first number of combinations of the first target drug.

[0073] This disclosure does not limit the specific implementation of step S121, which involves determining the quantity range based on the component content of the first target drug in the first target monograph and counting the total number of the first active ingredient in the first target monograph. Those skilled in the art can implement this using relevant technical means. For example, semantic analysis can be performed on the first target monograph to extract key information or keyword matching information related to component content, thereby determining the quantity range. Correspondingly, keywords related to component content can be obtained through semantic analysis, and the total number of component contents can be counted. This disclosure does not limit the specific technical means used for semantic analysis, keyword matching, and keyword segmentation; those skilled in the art can implement this using relevant technologies.

[0074] For example, suppose the first target monograph is the U.S. nonprescription human antacid monograph M001, in which the following conditions are established in Part B:

[0075] The antacid drug (first target drug) of this type consists of one or more active ingredients permitted by the monograph, and the content of each ingredient accounts for at least 25% of the total acid neutralizing capacity of the product. According to step S121 (determining the quantity range based on the component content of the first target drug in the first target monograph), it is analyzed that the antacid active ingredient can be composed of up to 4 components, and at least 1 antacid active ingredient is included, that is, the quantity range is [1, 4]. Specifically, the antacid drug (first target drug) can be composed of 1 antacid active ingredient (first active ingredient), or the antacid drug (first target drug) can be composed of 2 antacid active ingredients (first active ingredients), or the antacid drug (first target drug) can be composed of 3 antacid active ingredients (first active ingredients), or the antacid drug (first target drug) can be composed of 4 antacid active ingredients (first active ingredients).

[0076] Through semantic analysis, keyword matching, keyword segmentation, and other technical means, the specific list of antacid active ingredients in antacid drug monograph M001 can be determined to include:

[0077] (a) Aluminum-containing active ingredients: (1) alkaline aluminum carbonate gel, (2) aluminum hydroxide (or as aluminum hydroxide-hexitol stabilized polymer, aluminum hydroxide-magnesium carbonate dry gel, aluminum hydroxide-magnesium trisilicate dry gel, aluminum hydroxide sucrose powder hydrate), (3) dihydroxyaluminum aminoacetate and dihydroxyaluminum aminoacetic acid, (4) aluminum phosphate gel, when used as part of an antacid compound product, and contributing at least 25% to the total acid neutralization capacity; the maximum daily dose is 8 grams, (5) sodium dihydroxyaluminum carbonate.

[0078] (b) Active ingredient containing bicarbonate: bicarbonate ion; maximum daily dose limit is 200 mEq for people under 60 years of age and 100 mEq for people over 60 years of age.

[0079] (c) Bismuth-containing active ingredients: (1) Bismuth aluminate, (2) Bismuth carbonate, (3) Bismuth subcarbonate, (4) Bismuth hypogallate, (5) Bismuth nitrate.

[0080] (d) Calcium-containing active ingredient: calcium, in the form of carbonate or phosphate; maximum daily dose limit of 160 mEq of calcium (e.g., 8 g of calcium carbonate).

[0081] (e) Active ingredient containing citrate: citrate ion, in the form of citric acid or salt; maximum daily dose limit is 8g.

[0082] (f) Glycine (aminoacetic acid).

[0083] (g) Magnesium-containing active ingredients: (1) Magnesium aluminum hydroxide sulfate hydrate, (2) Magnesium aluminum hydroxide, (3) Magnesium aluminosilicate, (4) Magnesium carbonate, (5) Magnesium glycine, (6) Magnesium hydroxide, (7) Magnesium oxide, (8) Magnesium trisilicate, (9) Dry solid milk.

[0084] (h) Phosphorus-containing active ingredients: (1) Aluminum phosphate; maximum daily dose limit is 8g, (2) Elemental or di-type calcium salts; maximum daily dose limit is 2g, (3) Calcium triphosphate; maximum daily dose limit is 24g.

[0085] (i) Potassium-containing active ingredients: (1) Potassium bicarbonate (or potassium carbonate used as an effervescent ingredient); the maximum daily dose limit for people under 60 years of age is 200 mEq of bicarbonate ions, and for people 60 years of age or older it is 100 mEq of bicarbonate ions; (2) Potassium sodium tartrate.

[0086] (j) Sodium-containing active ingredients: (1) Sodium bicarbonate (or sodium carbonate used as an effervescent ingredient); the maximum daily dose limit is 200 mEq of sodium for people under 60 years of age, 100 mEq of sodium for people over 60 years of age, 200 mEq of bicarbonate ions for people under 60 years of age, and 100 mEq of bicarbonate ions for people over 60 years of age. The warning section required by Section 330.1(g) indicates that products containing only sodium bicarbonate powder and intended primarily for non-pharmaceutical purposes do not require "keeping this product and all medicines out of the reach of children".

[0087] (k) Potassium sodium tartrate

[0088] (l) Silicates: (1) Magnesium aluminosilicate, (2) Magnesium trisilicate.

[0089] (m) Active ingredient containing tartaric acid: tartaric acid or its salts; tartrate salts (15g) with a maximum daily dose limit of 200mEq.

[0090] Based on the above information, it can be determined that there are 29 primary active ingredients in the monograph on antacids M001. According to the above text, the quantity range is determined to be 1–4.

[0091] According to step S122 (determine the corresponding number of combinations for each quantity in the quantity range, and sum the number of combinations to obtain the first number of combinations for the first target drug), 1-4 of the 29 first active ingredients in the monograph on antacids M001 are selected, and the first number of combinations of antacids is: C(29,1)+C(29,2)+C(29,3)+C(29,4)=27840.

[0092] In one possible implementation, such as Figure 2 As shown, step S12, which determines the quantity range of the first active ingredient constituting the first target drug in the first target monograph and the total number of the first active ingredients in the first target monograph to obtain the first combination number of the first target drug, may include:

[0093] Step S123: Input the first target monograph into the pre-trained first recognition model, and obtain the quantity range of the first active ingredient, the total number of the first active ingredients in the first target monograph, and the number of first combinations of the first target drug based on the output of the first recognition model.

[0094] In this embodiment, a first recognition model can be pre-trained, and the first target monograph can be input into the pre-trained first recognition model. Based on the output of the first recognition model, the quantity range of the first active ingredient, the total number of the first active ingredients in the first target monograph, and the number of first combinations of the first target drug can be obtained. This can improve the accuracy and efficiency of determining the combination of active ingredients in the monograph. The first recognition model can be implemented based on a large number of monographs during training and can be continuously trained. That is, if new monographs are generated later, the first recognition model can be retrained to update the parameters of the first recognition model, which can further improve the accuracy and efficiency of determining the combination of active ingredients in the monograph.

[0095] This disclosure does not limit the type or implementation method of the first recognition model, nor does it limit its training method. Those skilled in the art can implement it using related technologies. For example, the first recognition model can be implemented based on a feedforward neural network, such as convolutional neural networks (CNN), fully connected neural networks (FCN), and generative adversarial networks (GAN). The first recognition model can also be implemented based on a feedback neural network, such as recurrent neural networks (RNN), long short-term memory networks (LSTM), Hopfield networks, and Boltzmann machines. Of course, the first recognition model can also be implemented based on other deep learning algorithms, and this disclosure does not limit it.

[0096] In one possible implementation, the present disclosure embodiments may set specific parameters in the first identification model to determine the quantity range of the first active ingredient, the total number of the first active ingredients in the first target monograph, and the number of the first combination of the first target drug.

[0097] For example, this first identification model can split the drug component combination logic in a monograph into two parts: general logic and monograph logic. The general logic has high universality and is directly deployed in the code kernel of the first identification model. The monograph logic, on the other hand, represents the combination rules for different monographs and is stored in the attributes of each monograph.

[0098] For example, for monograph logic, the internal composition conditions in a monograph can be defined as an independent variable compose_max, while the external composition conditions can be defined as an object data_ext containing at least two variables. The first variable, data_ext_relations, records the names of the external monographs that can be composed, and the second variable, data_ext_compose, records the external composition conditions. The variables compose_max, data_ext_relations, and data_ext_compose are written separately according to the specific conditions of the monograph.

[0099] Taking monograph M001 as an example, during actual operation, the first identification model can obtain the internal combination condition value (number range) of monograph M001 through the variable compose_max, which is 4. Therefore, the tool will limit the internal combinations to no more than 4 components. Next, data_ext_relations can be used to determine that the external monographs that can be combined with M001 are M013 or M002. Simultaneously, the value in data_ext_compose indicates that only one component from these two monographs can be externally combined. In this way, the system can derive all possible combinations for monograph M001.

[0100] By parameterizing the internal and external conditions of a monograph, researchers can quickly add and modify monographs simply by adjusting the parameters, without having to redevelop the system, thus improving efficiency and reducing costs.

[0101] This disclosure does not limit the specific implementation of step S13, which determines the first characteristic of the first active ingredient in the first target monograph. In one possible implementation, step S13, which determines the first characteristic of the first active ingredient in the first target monograph, may include:

[0102] The first target monograph is input into a pre-trained first recognition model, and the first feature of the first active ingredient is obtained based on the output of the first recognition model.

[0103] Of course, other implementation methods can also be used to achieve step S13 of determining the first characteristic of the first active ingredient in the first target monograph. For example, semantic analysis, keyword identification and segmentation can be performed on the first target monograph to determine the characteristics of the first active ingredient in the first target monograph, such as the category of active ingredient, the category of drug, or the number of times keywords are repeated in the description of active ingredient or drug (the same keyword with a high number of repetitions or keywords with similar semantics can be selected), thereby determining its first characteristic. For example, in the non-prescription human anti-antacid drug monograph M001, through analysis, it is found that its drug is an anti-antacid drug and its active ingredient is an anti-antacid active ingredient, so the first characteristic can be determined to be "anti-antacid".

[0104] Part B of this monograph on antacids, M001, also specifies the conditions for combining antacids with non-antacid active ingredients:

[0105] Antacids can contain any recognized safe and effective analgesic ingredient if they are only indicated for related symptoms such as headaches and acid reflux and are sold in oral solution form.

[0106] Antacids can contain any recognized safe and effective anti-gas ingredient if they are only indicated for gas symptoms associated with heartburn, stomach acid, or acid dyspepsia.

[0107] It is evident that the antacid active ingredient in monograph M001 can be combined with the active ingredients in other monographs to obtain other drugs.

[0108] In one possible implementation, such as Figure 2 As shown, step S13, which determines at least one second target monograph associated with the first target monograph among multiple monographs based on the first feature, may include:

[0109] Step S131: Determine the combination conditions of the active ingredients of the drug recorded in each of the multiple monographs;

[0110] Step S132: Determine at least one second target monograph associated with the first target monograph based on the similarity between the first feature and the active ingredients in the combination conditions of each active ingredient.

[0111] This disclosure embodiment determines the combination conditions of active ingredients of the drug described in each of the plurality of monographs, and determines at least one second target monograph associated with the first target monograph based on the similarity between the first feature and the active ingredients in each combination condition. This can efficiently and accurately determine at least one second target monograph associated with the first target monograph based on the similarity between the first feature and the active ingredients in each combination condition.

[0112] For example, acetaminophen, as defined in Section M013.10(a) of Monograph M013 on analgesics and antipyretics, may be combined with any antacid ingredient defined in Section M001.11 of Monograph M001 of OTC Monograph M001 or any combination of antacids permitted under Section M001.10(a) of Monograph M001 of OTC Monograph M001, provided that the finished product meets all the requirements of Section M001.10 of Monograph M001 of OTC Monograph M001 and is labeled in accordance with Section M013.60(b)(2). The combination conditions of analgesics and antipyretics active ingredients and non-analgesics and non-antipyretics active ingredients in Monograph M013 on analgesics and antipyretics were determined by semantic analysis: the combination of acetaminophen and antacids. Aspirin, as defined in Section M013.10(b)(1) of the Analgesic-Antipyretic Monograph M013, may be combined with any antacid ingredient defined in Section M001.11 of the OTC Monograph M001 or any combination of antacids permitted under Section M001.10(a) of the OTC Monograph M001, provided that the finished product complies with the requirements of Section M001.10 of the OTC Monograph M001, is sold in solution form, and has labeling instructions in accordance with Section M013.60(b)(4). The combination conditions for analgesic-antipyretic active ingredients and non-analgesic-non-antipyretic active ingredients in the Analgesic-Antipyretic Monograph M013 were determined by semantic analysis: the combination of aspirin and antacids. That is, based on step S131, the combination conditions of active ingredients of the drugs recorded in each of the multiple monographs are determined. It can be determined that the combination conditions of active ingredients in the analgesic-antipyretic monograph M013 include "a combination of acetaminophen and an antacid" and "a combination of aspirin and an antacid". And through the similarity calculation of antacidity (first feature) and "antacid" in the combination conditions of active ingredients in the analgesic-antipyretic monograph M013 including "a combination of acetaminophen and an antacid" and "a combination of aspirin and an antacid", it is found that the similarity between antacidity (first feature) and "antacid" is high. Therefore, it can be determined that the analgesic-antipyretic monograph M013 is a second target monograph associated with the non-prescription human antacid drug monograph M001 (step S132 determines at least one second target monograph associated with the first target monograph based on the similarity between the first feature and the active ingredients in each combination condition of active ingredients).

[0113] For example, according to step S14 (determining the number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug, and obtaining the number of each second combination based on the number of the first combination and the number of the second active ingredients in each second target monograph), for the analgesic-antipyretic monograph M013, it can be determined that the second active ingredients include acetaminophen and aspirin, one of which can be combined with an antacid. Then, the possibilities of combining with the antacid in the non-prescription human antacid monograph M001 (the number of second combinations) are: 2*[C(29,1)+C(29,2)+C(29,3)+C(29,4)]=55680.

[0114] Similarly, it can be determined that the human topical antiflatulent drug monograph M002 is also a second target monograph associated with the non-prescription human antacid drug monograph M001. The human topical antiflatulent drug monograph M002 contains a second active ingredient that can be combined with the first active ingredient: dimethyl silicone oil. Therefore, the possible combinations with antacids (number of second combinations) are: 1*[C(29,1)+C(29,2)+C(29,3)+C(29,4)]=27840.

[0115] Of course, the second recognition model can also be pre-trained in this embodiment. By inputting the first feature of the first active ingredient in the first target monograph and the multiple monographs into the trained second recognition model, the second target monograph associated with the first target monograph can be quickly identified. The number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug can be determined by the second recognition model. The number of each second combination is obtained according to the number of the first combination and the number of the second active ingredients in each second target monograph.

[0116] This disclosure does not limit the type or implementation method of the second recognition model, nor does it limit its training method. Those skilled in the art can implement it using related technologies. For example, the second recognition model can be implemented based on a feedforward neural network, such as convolutional neural networks (CNN), fully connected neural networks (FCN), and generative adversarial networks (GAN). The second recognition model can also be implemented based on a feedback neural network, such as recurrent neural networks (RNN), long short-term memory networks (LSTM), Hopfield networks, and Boltzmann machines. Of course, the second recognition model can also be implemented based on other deep learning algorithms, and this disclosure does not limit it.

[0117] After obtaining the number of each second combination, the embodiments of this disclosure can obtain the total number of combinations of the number of the first combination and the number of each second combination. For example, the total number of combinations corresponding to the three monographs on non-prescription human antacids M001, analgesic-antipyretic active ingredients M013, and human topical antiflatulent drugs M002 is 27840+55680+27840=111360.

[0118] Step S15 outputs the number of the first combination (including the monograph identification information and the correspondence between the number of combinations), the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination, for example, to the display interface, so that users can quickly understand the combination situation and make drug combination decisions.

[0119] Of course, the embodiments of this disclosure can also determine the specific combination of each active ingredient and output the combination method, and the embodiments of this disclosure do not limit this.

[0120] The embodiments disclosed herein do not limit the specific display method and interaction method of the display interface. Those skilled in the art can design it according to the actual situation and needs. For example, the three monographs on non-prescription human antacids M001, analgesics-antipyretics active ingredients M013, and human topical antiflatulents M002 are still used as examples.

[0121] First, checkboxes are associated with the 29 active ingredients in the monograph on non-prescription human antacids M001. A mapping is established one-to-one between the 29 checkboxes in the display interface and the 29 active ingredients in the monograph on non-prescription human antacids M001, and the results are counted. The result is recorded as Outcome1. When the number of checkboxes is 0, the count is 0, and Outcome1 is displayed as "Not selected"; when the number of checkboxes is greater than or equal to 1 and less than or equal to 4, Outcome1 is displayed as "Combinable"; when the number of checkboxes is greater than 4, Outcome1 is displayed as "Not combinable".

[0122] Secondly, the two active ingredients in the monograph on the effective components of analgesics and antipyretics M013 are associated with checkboxes. A one-to-one mapping is established between the two checkboxes in the display interface and the two active ingredients in the monograph on the effective components of analgesics and antipyretics M013, and the count is recorded. The result is recorded as Outcome2. When the number of checkboxes is 0, the count is 0 and the Outcome2 result is "not selected"; when the number of checkboxes is equal to 1, the Outcome2 result is "combinable"; when the number of checkboxes is greater than 1, the Outcome2 result is "not combinable".

[0123] Next, check the box associated with one active ingredient in the monograph M002 on topical anti-bloating drugs for human use, and count the results. The result is recorded as Outcome3. When the number of checks is 0, the count is 0, and the Outcome3 result is "not selected"; when the number of checks is equal to 1, the Outcome3 result is "combinable".

[0124] Then, the total number of combinations of active ingredients within monograph M001 (number of first combinations) and the total number of combinations of active ingredients between monographs M001 and M013, and between M001 and M002 (number of second combinations) are defined. This result is denoted as Outcome4. The following conditions are set:

[0125] 1. If OUTCOME1 is "Not Selected", then output "Antacid ingredient not selected".

[0126] 2. If OUTCOME1, OUTCOME2, and OUTCOME3 are not "not selected", then output "Antacids can only be combined with one type of drug".

[0127] 3. If OUTCOME1 is "Not composable", then output "Not composable".

[0128] 4. If OUTCOME1 is "Combinable", OUTCOME2 is "Combinable", and OUTCOME3 is "Not Selected", then output "Combinable".

[0129] 5. If OUTCOME1 is "Combinable", OUTCOME3 is "Combinable", and OUTCOME2 is "Not Selected", then output "Combinable".

[0130] 6. If OUTCOME1 is "Combinable", and both OUTCOME2 and OUTCOME3 are "Not Selected", then output "Combinable".

[0131] 7. Otherwise, output "Not combinable".

[0132] In one possible implementation, such as Figure 2 As shown, the method may further include:

[0133] Step S100: Extract target information from multiple monographs according to each preset keyword, and establish a basic database. The basic database includes the mapping relationship between preset keywords and target information.

[0134] In one possible implementation, the keywords include at least one of the following: country / region, monograph name, active ingredient, indication, action category, therapeutic category, dosage form, excipient information, specifications, minimum specification, maximum specification, dosage and administration, minimum single dose, maximum single dose, minimum daily dose, maximum daily dose, etc.

[0135] This disclosure does not limit the language type of the monographs. For monographs from the United States, Australia, and Canada, they can be translated into post-processing or processed directly. This disclosure, through the above keywords, can accurately and efficiently establish a database of monographs from various countries and regions worldwide.

[0136] In one possible implementation, step S11, which determines the first target monograph from among multiple monographs based on the received first selection information, may include:

[0137] The first target monograph is determined in the basic database based on the received first selection information.

[0138] This embodiment of the disclosure extracts target information from multiple monographs according to each preset keyword, establishes a basic database, and determines the first target monograph in the basic database based on the received first selection information, which can improve the matching speed and accuracy of the first target monograph.

[0139] In one possible implementation, such as Figure 2 As shown, the method may further include:

[0140] Step S16: Output the quantity range of the first active ingredient constituting the first target drug in the first target monograph;

[0141] Step S17: If the number of target components corresponding to the received quantity setting parameter is within the quantity range, determine and output the first target combination number of the first target drug based on the number of target components and the total number of the first active ingredients.

[0142] Step S18: Determine and output the number of each second target combination based on the number of the first target combination and the number of the second active ingredients in each second target monograph.

[0143] This disclosure embodiment can determine and display in real time the number and / or combination method of the first active ingredient in the first target monograph according to the user's needs, and determine and display in real time the number of second target combinations of the second active ingredient and the first active ingredient in each second target monograph associated with the first target monograph, thereby providing the user with accurate combination possibility data, assisting the user in drug combination, and improving drug development efficiency.

[0144] This disclosure establishes a method for extracting, analyzing, storing, statistically analyzing, and accessing information from monographs. It eliminates the need for manual reading and transcription of each original text, reducing information bias, increasing the convenience of information retrieval, and providing intuitive and clear statistical results. Particularly in monograph statistics, this disclosure eliminates the need to list all possible combinations of components (US monographs alone have over 200,000 possible combinations) to determine the likelihood of such combinations, thus improving the efficiency of monograph statistics.

[0145] It is understood that the various method embodiments mentioned above in this disclosure can be combined with each other to form combined embodiments without violating the principle and logic. Due to space limitations, this disclosure will not elaborate further. Those skilled in the art will understand that in the above methods of specific implementation, the specific execution order of each step should be determined by its function and possible internal logic.

[0146] In addition, this disclosure also provides a drug combination device, electronic device, computer-readable storage medium, and program for non-prescription drugs, all of which can be used to implement any of the drug combination methods for non-prescription drugs provided in this disclosure. The corresponding technical solutions and descriptions are described in the corresponding descriptions in the method section and will not be repeated here.

[0147] Please see Figure 3 , Figure 3 A block diagram of a nonprescription drug combination device according to an embodiment of the present disclosure is shown.

[0148] like Figure 3 As shown, the device includes:

[0149] The first determining module 10 is configured to determine a first target monograph from multiple monographs based on received first selection information, wherein the first selection information includes monograph identification information.

[0150] The second determining module 20 is used to determine the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, so as to obtain the first combination number of the first target drug.

[0151] The third determining module 30 is used to determine a first characteristic of the first active ingredient in the first target monograph, and to determine at least one second target monograph associated with the first target monograph among a plurality of monographs based on the first characteristic;

[0152] The fourth determining module 40 is used to determine the number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug, and to obtain the number of each second combination based on the number of the first combination and the number of the second active ingredients in each second target monograph.

[0153] The output module 50 is used to output the number of the first combination, the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination.

[0154] This embodiment of the disclosure determines a first target monograph from multiple monographs based on received first selection information, determines the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain a first combination number of the first target drug. This allows for efficient and accurate determination of the number and manner of combinations of active ingredients in any one of the multiple monographs. Furthermore, by determining a first characteristic of the first active ingredient in the first target monograph, at least one second target monograph associated with the first target monograph is determined from the multiple monographs based on the first characteristic; and each second target monograph is determined to have combinations with the first active ingredient to form a first target drug. The number of second active ingredients in a two-target drug is obtained by considering the number of first combinations and the number of second active ingredients in each second target monograph. That is, by using the first characteristics of the first active ingredient in the first target monograph, the number and combination method of active ingredients in other second target monographs associated with the first target monograph can be efficiently and accurately identified. By outputting the number of first combinations, the number of each second combination, and / or the total number of combinations of the first combination and the number of each second combination, it is convenient to evaluate the number of first combinations, the number of each second combination, and / or the total number of combinations of the first combination and the number of each second combination in real time.

[0155] In one possible implementation, the output module is further configured to: output the quantity range of the first active ingredient constituting the first target drug in the first target monograph;

[0156] In one possible implementation, the second output module is further configured to: if the number of target components corresponding to the received quantity setting parameter is within the quantity range, determine and output the first target combination number of the first target drug based on the number of target components and the total number of the first active ingredients;

[0157] In one possible implementation, the second output module is further configured to: determine and output the number of each second target combination based on the number of the first target combination and the number of the second active ingredients in each second target monograph.

[0158] In one possible implementation, determining the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug, includes:

[0159] The quantity range is determined based on the component content of the first target drug in the first target monograph, and the total number of the first active ingredient in the first target monograph is counted.

[0160] For each quantity in the range, a corresponding number of combinations is determined, and the numbers of each combination are summed to obtain the first number of combinations of the first target drug.

[0161] In one possible implementation, determining the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug, includes:

[0162] The first target monograph is input into a pre-trained first recognition model, and the quantity range of the first active ingredient, the total number of the first active ingredient in the first target monograph, and the number of the first combination of the first target drug are obtained based on the output of the first recognition model.

[0163] In one possible implementation, determining the first characteristic of the first active ingredient in the first target monograph includes:

[0164] The first target monograph is input into a pre-trained first recognition model, and the first feature of the first active ingredient is obtained based on the output of the first recognition model.

[0165] In one possible implementation, determining at least one second target monograph associated with the first target monograph among a plurality of monographs based on the first feature includes:

[0166] Determine the combination conditions of the active ingredients of the drugs described in each of the multiple monographs;

[0167] Based on the similarity between the first feature and the active ingredients in the combination conditions of each active ingredient, at least one second target monograph associated with the first target monograph is determined.

[0168] In one possible implementation, the device further includes:

[0169] A module is established to extract target information from multiple monographs according to each preset keyword, and to establish a basic database, which includes the mapping relationship between preset keywords and target information.

[0170] In one possible implementation, the keywords include at least one of the following: country / region, monograph name, active ingredient, indication, action category, therapeutic category, dosage form, excipient information, specification composition, minimum specification, maximum specification, dosage and administration, minimum single dose, maximum single dose, minimum daily dose, and maximum daily dose.

[0171] In one possible implementation, determining the first target monograph from among multiple monographs based on the received first selection information includes:

[0172] The first target monograph is determined in the basic database based on the received first selection information.

[0173] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0174] This disclosure also proposes a computer-readable storage medium storing computer program instructions that, when executed by a processor, implement the above-described method. The computer-readable storage medium may be a non-volatile computer-readable storage medium.

[0175] This disclosure also proposes an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the above-described method.

[0176] This disclosure also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.

[0177] Electronic devices can be provided as terminals, servers, or other forms of devices.

[0178] Please see Figure 4 , Figure 4 A block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0179] For example, electronic device 800 can be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, and other terminals.

[0180] Reference Figure 4The electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0181] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0182] Memory 804 is configured to store various types of data to support the operation of electronic device 800. Examples of this data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0183] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0184] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0185] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0186] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0187] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 may detect the on / off state of electronic device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include an optical sensor, such as a complementary metal-oxide-semiconductor (CMOS) or charge-coupled device (CCD) image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0188] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, second-generation mobile communication technology (2G), or third-generation mobile communication technology (3G), or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0189] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0190] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 804 including computer program instructions that can be executed by a processor 820 of an electronic device 800 to perform the above-described method.

[0191] Please see Figure 5 , Figure 5 A block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0192] For example, electronic device 1900 can be provided as a server. (See reference...) Figure 5 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0193] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output (I / O) interface 1958. Electronic device 1900 can operate on an operating system stored in memory 1932, such as Microsoft Server operating system (Windows Server). TM Apple's graphical user interface-based operating system (Mac OSX) TM ), a multi-user, multi-process computer operating system (Unix) TM Linux is a free and open-source Unix-like operating system. TM ), the open-source Unix-like operating system (FreeBSD) TM (or similar.)

[0194] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of an electronic device 1900 to perform the above-described method.

[0195] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0196] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, (but not limited to) electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0197] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0198] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0199] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0200] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0201] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0202] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0203] The computer program product can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0204] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for combining drugs in a non-prescription drug formulation, characterized in that, The method includes: Based on the received first selection information, a first target monograph is determined from multiple monographs, wherein the first selection information includes monograph identification information; Determine the range of quantities of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug; Determine a first characteristic of the first active ingredient in the first target monograph, and determine at least one second target monograph associated with the first target monograph among a plurality of monographs based on the first characteristic; The number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug is determined, and the number of each second combination is obtained based on the number of the first combination and the number of the second active ingredients in each second target monograph. Output the number of the first combination, the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination.

2. The method according to claim 1, characterized in that, The method further includes: Output the range of quantities of the first active ingredient that constitutes the first target drug in the first target monograph; If the number of target components corresponding to the received quantity setting parameter is within the quantity range, the first target combination number of the first target drug is determined and output based on the number of target components and the total number of the first active ingredients; The number of each second target combination is determined and output based on the number of the first target combination and the number of the second active ingredients in each second target monograph.

3. The method according to claim 1, characterized in that, Determining the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug, includes: The quantity range is determined based on the component content of the first target drug in the first target monograph, and the total number of the first active ingredient in the first target monograph is counted. For each quantity in the range, a corresponding number of combinations is determined, and the numbers of each combination are summed to obtain the first number of combinations of the first target drug.

4. The method according to claim 1 or 3, characterized in that, Determining the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, to obtain the first combination number of the first target drug, includes: The first target monograph is input into a pre-trained first recognition model, and the quantity range of the first active ingredient, the total number of the first active ingredient in the first target monograph, and the number of the first combination of the first target drug are obtained based on the output of the first recognition model.

5. The method according to claim 1, characterized in that, The determination of the first characteristic of the first active ingredient in the first target monograph includes: The first target monograph is input into a pre-trained first recognition model, and the first feature of the first active ingredient is obtained based on the output of the first recognition model.

6. The method according to claim 1 or 5, characterized in that, The step of determining at least one second target monograph associated with the first target monograph among multiple monographs based on the first feature includes: Determine the combination conditions of the active ingredients of the drugs described in each of the multiple monographs; Based on the similarity between the first feature and the active ingredients in the combination conditions of each active ingredient, at least one second target monograph associated with the first target monograph is determined.

7. The method according to claim 1, characterized in that, The method further includes: Target information is extracted from multiple monographs according to each preset keyword to establish a basic database, which includes the mapping relationship between preset keywords and target information.

8. The method according to claim 7, characterized in that, The keywords include at least one of the following: country / region, monograph name, active ingredient, indication, action category, therapeutic category, dosage form, excipient information, specifications, minimum specification, maximum specification, dosage and administration, minimum single dose, maximum single dose, minimum daily dose, and maximum daily dose.

9. The method according to claim 7, characterized in that, The step of determining the first target monograph from multiple monographs based on the received first selection information includes: The first target monograph is determined in the basic database based on the received first selection information.

10. A non-prescription drug combination device, characterized in that, The device includes: The first determining module is configured to determine a first target monograph from multiple monographs based on received first selection information, wherein the first selection information includes monograph identification information. The second determining module is used to determine the quantity range of the first active ingredient constituting the first target drug in the first target monograph, and the total number of the first active ingredients in the first target monograph, so as to obtain the first combination number of the first target drug; The third determining module is used to determine a first characteristic of the first active ingredient in the first target monograph, and to determine at least one second target monograph associated with the first target monograph among multiple monographs based on the first characteristic; The fourth determining module is used to determine the number of second active ingredients in each second target monograph that can be combined with the first active ingredient to form a second target drug, and to obtain the number of each second combination based on the number of the first combination and the number of the second active ingredients in each second target monograph. The output module is used to output the number of the first combination, the number of each second combination, and / or the total number of combinations of the number of the first combination and the number of each second combination.

11. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the nonprescription drug combination method according to any one of claims 1 to 9.

12. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the non-prescription drug combination method according to any one of claims 1 to 9.

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