Method and apparatus for calculating individualized probabilities of drug side effects

Abstract

The individualized drug side effect probability calculation method of the computing device according to an embodiment of the present disclosure, as a method performed by the computing device at each step, can include the following steps: confirming a drug taken by a subject; confirming a side effect experience input by the subject according to the drug taken by the subject; and calculating a probability of occurrence of a side effect of the subject related to the drug based on the side effect experience of the subject.

Description

Technical Field

[0001] This disclosure relates to a method and apparatus for calculating the individualized probability of drug side effects, and more specifically, to a method and apparatus for calculating the probability of drug side effects based on an individual's drug use experience. Background Technology

[0002] Individuals may take prescription medications from hospitals or take multiple medications based on their own judgment or the advice of a pharmacist.

[0003] A medication has the potential to cause various side effects for the user, but this is a statistical probability before an individual takes the medication. In reality, each individual taking the medication has an equal probability of experiencing side effects. However, if there is a history of taking the same medication multiple times in the past, the probability of experiencing side effects at a specific point in time may actually vary from person to person, depending on whether they have experienced side effects in the past.

[0004] That is, among different individuals taking the same drug with the same statistical probability of side effects, some users may eventually experience the corresponding side effects, while others may not. Even if the statistical probability of a particular component of the drug is high, a particular user may have the physical condition to avoid the side effects of the drug.

[0005] However, when taking medications composed of multiple herbs or multiple medications to treat an ailment, it is difficult for each individual to know which drug or ingredient caused the side effects they experienced. Therefore, in order to avoid experiencing the same side effects, it becomes difficult to avoid the drugs or ingredients that cause them.

[0006] When a prescription is obtained from a hospital, the individual can inform the doctor about any side effects they have experienced, and the doctor can exclude medications that may cause side effects from the prescription. However, there is a problem that it is difficult to apply this to all medications that an individual is taking.

[0007] While existing technologies exist to exclude medications with side effects experienced by an individual from prescriptions, as mentioned above, it is difficult for individuals taking multiple medications to know which medication caused the corresponding side effects, making it difficult to apply these technologies when taking medications not prescribed by a doctor.

[0008] Recently, although attempts have been made to calculate the probability of drug side effects based on individual genes or individual physiological characteristics, there is currently no officially recognized technology for calculating the probability of individual side effects, and individuals are difficult to access both economically and methodologically.

[0009] Therefore, even if it is not a scientifically accurate probability equivalent to the gold standard, individuals need to have easy access to technology that allows them to easily obtain drugs that are more likely to cause side effects for them. Summary of the Invention

[0010] Technical issues

[0011] One embodiment of this disclosure provides a method and apparatus for calculating the probability of drug side effects based on an individual's drug use experience.

[0012] Another embodiment of this disclosure provides a method and apparatus for calculating the probability of occurrence of personalized drug side effects based on the occurrence or non-occurrence of side effects during individual drug administration.

[0013] Another embodiment of this disclosure provides a method and apparatus for calculating the probability of drug side effects based on the intensity of side effects during individual drug use, previous periods of use, etc.

[0014] The technical problems to be solved by this invention are not limited to those mentioned above. Those skilled in the art can clearly understand other technical problems not mentioned below from the following description, and these can be further clarified through the embodiments of this invention. Furthermore, it can be seen that the technical problems and advantages to be solved by this invention can be achieved through the means and combinations thereof shown in the claims.

[0015] Technical solution

[0016] According to an embodiment of the present disclosure, a method for calculating the probability of individualized drug side effects using a computing device may include the following steps as each step is performed by the computing device: identifying the drug taken by the subject; identifying the subject's experience of side effects based on the drug taken by the subject; and calculating the probability of side effects occurring in the subject related to the drug based on the subject's experience of side effects.

[0017] A computing apparatus for calculating a personalized probability of drug side effects according to an embodiment of the present disclosure includes: a processor; and a memory, functionally connected to the processor and storing at least one code that is executed in the processor, wherein the memory may store code that, when executed in the processor, is the processor's actions of: identifying a drug taken by a subject, identifying experiences of side effects input from the subject based on the subject's taking of the drug, and calculating the probability of occurrence of drug-related side effects based on the subject's experiences of side effects.

[0018] Technical effect

[0019] The method and apparatus for calculating the probability of drug side effects according to an embodiment of the present disclosure can make it easy for individuals to identify drugs or drug components that are more likely to cause side effects for them.

[0020] A method and apparatus for calculating the probability of drug side effects according to an embodiment of the present disclosure can prevent secondary harm caused by side effects by excluding the possible side effects of drugs taken by an individual.

[0021] According to an embodiment of the present disclosure, a method and apparatus for calculating the probability of drug side effects can identify drugs or drug components that are highly likely to cause side effects in an individual among a variety of drugs taken.

[0022] The effects of the present invention are not limited to those mentioned above, and those skilled in the art will clearly understand other effects not mentioned below through the description below. Attached Figure Description

[0023] Figure 1 This is a diagram illustrating the environment in which a method and apparatus for calculating the probability of drug side effects based on an individual's drug use experience, according to an embodiment of the present disclosure, are implemented.

[0024] Figure 2 This is a block diagram illustrating the configuration of a user terminal according to an embodiment of the present disclosure.

[0025] Figure 3 This is a block diagram illustrating the configuration of a server apparatus according to an embodiment of the present disclosure.

[0026] Figure 4 This is a flowchart illustrating a method for calculating the probability of drug side effects according to an embodiment of the present disclosure.

[0027] Figure 5 This is a flowchart illustrating a method for calculating the probability of drug side effects according to an embodiment of the present disclosure.

[0028] Figure 6 This is a diagram used to briefly illustrate drug side effect information in a drug side effect database according to an embodiment of the present disclosure.

[0029] Figure 7 Is and Figure 8 This is a graph illustrating an individual's experience of side effects, used to illustrate a method for calculating the probability of drug side effects occurring according to an embodiment of the present disclosure.

[0030] Figure 9 This is a diagram illustrating the interface of a user terminal according to an embodiment of the present disclosure. Detailed Implementation

[0031] The embodiments disclosed in this specification will now be described in detail with reference to the accompanying drawings. However, regardless of the drawing numbers, identical or similar components will be assigned the same reference numerals, and repeated descriptions will be omitted. The suffixes "module" and "part" used in the following description are assigned or used interchangeably only for ease of completing the specification and do not inherently have a distinguishing meaning or function. Furthermore, in describing the embodiments disclosed in this specification, detailed descriptions of related known technologies are omitted if they are considered to obscure the essence of the embodiments disclosed in this specification. Moreover, the drawings are only for the purpose of facilitating understanding of the embodiments disclosed in this specification. The technical concepts disclosed in this specification are not limited by the drawings and should be understood to include all modifications, homogenizations, or substitutions within the scope of the present invention.

[0032] Ordinal terms such as "first" and "second" may be used to describe multiple constituent elements, but the constituent elements are not limited by these terms. The terms are used only to distinguish one constituent element from another.

[0033] When it is mentioned that a constituent element is "combined" or "connected" with another constituent element, it should be understood that although it may be directly combined or directly connected with another constituent element, there may be other constituent elements in between. Conversely, when it is mentioned that a constituent element is "directly combined" or "directly connected" with another constituent element, it should be understood that there are no other constituent elements in between.

[0034] Reference Figure 1 The environment for implementing a method or apparatus for calculating the probability of occurrence of drug side effects according to an embodiment of the present disclosure will be described.

[0035] In this instruction manual, the terms "pharmaceutical preparation," "drug," and "medicine" can refer to drugs composed of a single ingredient or a combination of ingredients, and do not have different meanings.

[0036] In this instruction manual, "taking" includes not only oral administration, but also administration via injection, patch administration, topical application of ointment, and injection through the nasal cavity or ocular mucosa.

[0037] The method or apparatus for calculating the probability of drug side effects according to embodiments of this disclosure can be implemented using a user terminal or a server device, and the following description is based on the premise of implementation on a server device, but it should be noted that it can also be implemented in a user terminal.

[0038] The environment for implementing a method or apparatus for calculating the probability of occurrence of drug side effects according to an embodiment of the present disclosure may include a user terminal 100 and a server device 200. Where a database including statistical side effect probability information of drugs is implemented using a separate device, a drug side effect database device 300 may be included.

[0039] Users can input the medication they are taking, whether they have experienced any side effects after taking the medication, and the types of side effects that occurred, through user terminal 100.

[0040] Reference Figure 9 When a user inputs the medication 910 they are taking into the user terminal 100, the server device 200 can obtain the corresponding drug's components or related side effects 920 from the drug side effect database 300 and provide them to the user terminal 100. The user can select from the provided side effects whether they have experienced any or not. The server device 200 updates the probability of side effects occurring for the user based on the selected occurrence and type of side effects, specifically for the medication taken or its components.

[0041] Server device 200 obtains statistical side effect probabilities of the medication or its components taken by the user from database 300 or its own specific database, and sets these probabilities as the user's initial individualized side effect probabilities for the corresponding medication or its components. The server device 200 recalculates (updates) the individualized side effect probabilities whenever the user experiences medication use. Server device 200 also considers experiences without side effects when recalculating the individualized side effect probabilities.

[0042] Server device 200 can receive specific drugs or ingredients from user terminal 100 and provide personalized drug side effect probabilities for them.

[0043] When the probability of side effects for a specific drug exceeds a preset threshold or the number of side effects occurs exceeds a preset consecutive number of times, the server device 200 can provide this information to the user terminal 100.

[0044] User terminal 100 obtains individualized drug side effect probabilities for a specific drug or ingredient from server device 200, and the user can confirm this when purchasing the specific drug. Alternatively, when prescribing, dispensing, or selling drugs to a specific patient at a pharmacy or hospital terminal, individualized drug side effect probabilities can be provided for that specific patient's specific drug or ingredient, and drugs with a higher probability of side effects for that patient can be excluded.

[0045] Reference Figure 2The composition of user terminal 100 is explained.

[0046] User terminal 100 may include an interface for communicating with server device 200.

[0047] The communication interface may include a wireless communication unit 110 or a wired communication unit.

[0048] The wireless communication unit 110 may include at least one of the following: a broadcast receiving module 111, a mobile communication module 112, a wireless internet module 113, a short-range communication module 114, and a location information module 115.

[0049] The mobile communication module 112 transmits and receives radio signals with at least one of a base station, an external terminal, and a server in a mobile communication network constructed according to technical standards or communication methods used for mobile communication (e.g., Global System for Mobile communication, Code Division Multiple Access, Code Division Multiple Access 2000, Enhanced Voice-Data Optimized or Enhanced Voice-Data Only, Wideband Code Division Multiple Access, High Speed ​​Downlink Packet Access, High Speed ​​Uplink Packet Access, Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), etc.).

[0050] The wireless internet module 113 refers to a module used for wireless internet connectivity, which can be built into or externally mounted on the user terminal 100. The wireless internet module 113 is implemented to transmit and receive wireless signals in a communication network based on wireless internet technology.

[0051] Wireless Internet technologies include, for example, Wireless LAN (WLAN), Wi-Fi, Wi-Fi Direct, Digital Living Network Alliance (DLNA), Wireless Broadband (WiBro), World Interoperability for Microwave Access (WiMAX), High Speed ​​Downlink Packet Access (HSDPA), High Speed ​​Uplink Packet Access (HSUPA), Long Term Evolution (LTE), and Long Term Evolution-Advanced (LTE-A).

[0052] The short-range communication module 114 refers to a module used for short-range communication, utilizing Bluetooth. TM It uses at least one of the following technologies to support short-range communication: Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, Near Field Communication (NFC), Wi-Fi, Wi-Fi Direct, and Wireless Universal Serial Bus.

[0053] The location information module 115 serves as a module for obtaining the location (or current location) of the user terminal 100. Representative examples include a Global Positioning System (GPS) module or a Wi-Fi module. For instance, when the terminal uses a GPS module, the location of the user terminal 100 can be obtained using signals transmitted by GPS satellites.

[0054] In one embodiment, the user terminal 100 may include an input unit 120 for inputting the user's drug type, side effect type, etc.

[0055] The input unit 120 may include a camera 121, a microphone 122 for receiving audio signals, and a user input unit 123 for receiving information from the user.

[0056] User input unit 123 may include a mechanical input unit (or, mechanical keys, buttons, dome switches, scroll wheels, scroll wheel switches, etc.) and a touch input unit. As an example, the touch input unit may be implemented using virtual keys, soft keys, or visual keys displayed on the touch screen through software processing, or using touch keys located outside the touch screen.

[0057] In one embodiment, the user terminal 100 may include an output unit 150 for conveying information to the user.

[0058] The output unit 150, which is used to generate outputs related to vision, hearing or touch, may include at least one of a display unit 151, a sound output unit 152, a tactile module 153, and a light output unit 154.

[0059] The display unit displays (outputs) information processed at the user terminal 100. For example, the display unit may display the types of side effects of a drug or its ingredients provided from the server device 200 that are related to a medication taken by the user.

[0060] The sound output unit 152 may include at least one of a receiver, a speaker, and a buzzer.

[0061] User terminal 100 may include an interface section 160 that performs functions to access various external devices connected to user terminal 100. Interface section 160 may include at least one of a wired / wireless data port, a memory card port, a port for connecting a device equipped with an identification module, an audio input / output (I / O) port, and a headphone port.

[0062] In addition, the user terminal 100 also includes a sensing unit 140, a processor 180, and a power supply unit 190.

[0063] Reference Figure 3 The configuration of a server apparatus 200 according to an embodiment of the present disclosure will be described.

[0064] Server device 200 can store the object's physical information, the diagnosis name (or diagnosis code) of the object's prescription, the type of medication taken or the types of ingredients contained in the medication, the dosage and time of taking each medication, and whether or not side effects were experienced when taking each medication, or the types of side effects.

[0065] Server device 200 can store statistical side effect information of drugs or ingredients contained in drugs, and drug ingredient information.

[0066] Server device 200 can store medical information, prescription information, or physical information, including the patient's diagnosis name (which may be a diagnosis code).

[0067] The information stored in server device 200 is implemented as a separate external database or by utilizing storage device 240, which is part of server device 200.

[0068] The server device 200, based on information provided by the user terminal 100 via the communication interface 230, including the type of medication taken by the user, whether or not side effects occurred, and the types of side effects, utilizes the drug's component information and statistical side effect information of the drug or its components to enable the processor 210 to calculate the user's individualized probability of drug side effects.

[0069] The processor 210 of the server device 200 can calculate the individualized probability of drug side effects for a user based not only on the occurrence of side effects after the user takes the drug, but also on the absence of side effects. In this case, different algorithms for calculating the individualized probability of drug side effects for a user can be applied to each other.

[0070] The algorithm for calculating the probability of individualized drug side effects for a user can be implemented using hardware, software, or a combination of hardware and software, and if part or all of the algorithm is implemented using software, one or more instructions constituting the algorithm can be stored in memory 220.

[0071] Reference Figure 4 A method for calculating individualized drug side effect probabilities according to an embodiment of the present disclosure will be described.

[0072] As mentioned above, the method for calculating individualized drug side effect probabilities can be implemented in a user terminal, but the following description is based on the premise that it is implemented in a server device.

[0073] Server device 200 confirms the medication the user inputs in user terminal 100 (S110). The medication can be a single-ingredient medication or a medication composed of multiple ingredients, and can be multiple medications taken at the same time or within a certain time period. The medication can be identified by the camera device of user terminal 100, by recognizing the product name on the product packaging, or by recognizing codes such as two-dimensional codes on the product packaging, or by the product name entered by the user. Furthermore, server device 200 can use similar methods to confirm the diagnosis name or diagnosis code printed before the prescription, or connect to a separate medical information system (OCS, HIS, EMR) to confirm the diagnosis name or diagnosis code.

[0074] Server device 200 can confirm whether the user has experienced side effects or side effects including side effects due to taking the medication (S120).

[0075] The server device 200 calculates the probability of side effects occurring for a user taking a single medication based on the user's side effect experience (S130). In the case of a user taking the medication for the first time, the server device 200 obtains information about the medication or its components from a database. Figure 6 The statistics show the probability of side effects, which is set as the basic probability of side effects for the user of the drug, and the probability of drug side effects is calculated based on the confirmed side effect experience of the user.

[0076] Side effect experiences include the absence of side effects. The server device 200 also reflects the user's experience of not experiencing side effects after taking a specific medication, and calculates the probability of drug side effects based on the user's side effect experiences. Therefore, whenever the user inputs experience of taking the same medication or experience of taking a medication containing the same ingredients, that is, for all experiences including whether side effects occurred or did not occur after taking the medication, the server device 200 updates the user's probability of side effects for the medication or the ingredients contained in the medication.

[0077] Server device 200 applies different algorithms to calculate the probability of side effects occurring for a user of a drug, based on whether or not a user has experienced side effects after taking the drug, and this is described in detail below.

[0078] Reference Figure 5 The specific method S130 for calculating the probability of individualized drug side effects according to an embodiment of the present disclosure will be described.

[0079] The server device 200 applies different algorithms to calculate the probability of side effects occurring for a user after taking a drug, based on whether or not the user has experienced side effects. If no side effects occur (S131 No), the probability of side effects occurring for the user can be reduced for the drug or its components (S132).

[0080] In this context, when using a drug composed of compound ingredients or taking multiple drugs, the server device 200 can reduce the probability of side effects occurring for each ingredient. In one embodiment, when taking various drugs simultaneously, the algorithm for increasing or decreasing the probability of a specific side effect includes averaging the increase or decrease after dividing by the number of drugs taken, or reflecting the situation by assigning a weighted value to the previous probability of side effects.

[0081] If a user takes a specific medication for the first time and no side effects occur, the server device 200 obtains information such as... Figure 6 The statistical probability of side effects shown is set as the basic probability of side effects for the user regarding this medication. For example, refer to... Figure 6 The statistical probability of side effects occurring for symptom 1 of component A is 10%, and the statistical probability of side effects occurring for symptom 2 is 5%. Then, the server device 200 can multiply the basic side effect probability by a preset disincentive constant reflecting the user's experience of not experiencing a side effect. The disincentive constant can be less than 1 and can be determined experimentally.

[0082] For example, if the inverse compensation constant is 0.5 and no side effects occur after the user takes the medicine containing ingredients A and B for the first time, the server device 200 can calculate that the probability of the user experiencing side effects of symptom 1 related to ingredient A is 5% (=10%×0.5), the probability of experiencing side effects of symptom 2 is 2.5% (=5%×0.5), and the probability of experiencing side effects of symptom 1 related to ingredient B is 10% (=20%×0.5).

[0083] Subsequently, if no side effects occur again after taking the same medication, the server device 200 recalculates (updates) the side effect probability for each symptom of ingredients A and B based on the previously calculated side effect probability for the user and using the same inverse compensation constant.

[0084] Reference Figure 5 and Figure 7 (a) Explains the method for calculating the probability of a user's side effects occurring in the event of side effects.

[0085] exist Figure 7(a) If a user experiences side effects after taking a specific medication containing ingredients A and B for the first time, the server device 200 can confirm the user's condition (S133). The server device 200 can confirm the prescription information recording the patient's disease code in an electronic medical record (EMR) server, or confirm it through user input. An EMR server includes not only medical record management servers managed by public institutions, but also medical record management servers or transmission servers managed by private institutions for sharing or transmitting medical records from various hospitals. As described above, the user can recognize the disease code printed on the prescription or directly input the disease code through the camera device of the user terminal 100.

[0086] Server device 200 can confirm the user's symptoms of illness (S134), obtain the medication taken by the patient, or such Figure 6 The server device 200 calculates the statistical probability of side effects for the indicated medications and compares them (S135). If the user's illness symptoms and the side effects of the medication are the same, the server device 200 can exclude the side effect experience from the user's drug side effect probability calculation. Therefore, it can eliminate the possibility of incorrect side effect probability calculation due to the user mistaking their illness symptoms for side effects caused by the medication.

[0087] If the symptoms of a user's illness differ from the side effects of the medication they are taking, the server device 200 can increase the probability of the user's side effects according to the ingredients of the medication they are taking (S136).

[0088] In the event that a user takes a specific medication for the first time and experiences side effects, the server device 200 can obtain information such as... Figure 6 After calculating the statistical probability of side effects and setting it as the basic probability of side effects for users who are not exposed to the drug, the server device 200 can multiply the basic probability of side effects by a preset incentive constant that reflects the user's experience of side effects. The incentive constant can be greater than 1 and can be determined experimentally.

[0089] For example, when the compensation constant is 1.5, Figure 7 (a) This section describes the occurrence of symptoms 1 and 2 after a user's first use of a medication containing ingredients A and B. The server device 200 can calculate that the probability of symptom 1 occurring as a side effect of ingredient A is 15% (=10%×1.5), the probability of symptom 2 occurring as a side effect of ingredient A is 7.5% (=5%×1.5), and the probability of symptom 1 occurring as a side effect of ingredient B is 30% (=20%×1.5). Symptom 2 is not a statistically significant side effect of ingredient B, therefore its probability of occurrence can be disregarded.

[0090] The following methods are explained: such as Figure 7 (a) Users such as those who take the same medication containing ingredients A and B again, or take other medications containing ingredients A and B, if Figure 7 (b) As shown in the case where symptom 1 occurs but symptom 2 does not occur, the probability of drug side effects is recalculated (updated).

[0091] With a compensation constant of 1.5 and an inverse compensation constant of 0.5, Figure 7 (b) After a user takes the medication containing ingredients A and B again, they experience symptom 1 but not symptom 2. Server device 200 uses an inverse compensation constant and a compensation constant to update the drug side effect probability for the user with respect to the stored side effect probabilities of ingredients A and B.

[0092] For example, server device 200 can calculate the probability of symptom 1 occurring as 22.5% (=15%×1.5) for component A, the probability of symptom 2 occurring as 3.75% (=7.5%×0.5) for component A, and the probability of symptom 1 occurring as 45% (=30%×1.5) for component B. Symptom 2 is not a statistically significant side effect of component B, therefore its probability of occurrence does not need to be calculated.

[0093] right Figure 7 (b) Explain the method for updating the probability of drug side effects after a user takes another medication containing ingredient A. The following methods will be explained: such as... Figure 7 (b) Users such as those who take other medications containing ingredients A and C again, such as Figure 8 As shown in (b), in the case where symptom 1 occurs but symptom 2 does not occur, the probability of drug side effects is recalculated (updated).

[0094] For the current user "A", a compensation constant of 1.5 can be applied to the individualized side effect probability of 22.5% for symptom 1 of the stored ingredient A, and the individualized side effect probability can be updated to 33.75%. An inverse compensation constant of 0.5 can be applied to the individualized side effect probability of 3.75% for symptom 2 of the stored ingredient A, and the individualized side effect probability can be updated to 1.875%. Furthermore, when ingredient C, contained in drug "b", is being reused for the first time, a compensation constant of 1.5 is applied to the statistical side effect probability of 10% for symptom 1 of ingredient C, thereby calculating an individualized side effect probability of 15% for ingredient C.

[0095] In another embodiment, if the database does not contain statistical side effect probability values ​​for the drug or the ingredients contained in the drug, in the implementation, the initial value can be set to any specific constant value (which may be very small).

[0096] By using the methods described above, the more experiences a user accumulates of taking different drugs with overlapping components, the more personalized the probability of side effects can be obtained, and based on this, drugs that need to be avoided can be identified.

[0097] In another embodiment, the server device 200 sets a compensation constant to be different for each ingredient based on the statistical probability of side effects of the drug or the ingredients contained in the drug.

[0098] For example, the statistical probability of side effects of the ingredients contained in a drug, such as Figure 6 In the case shown, the compensation constant for symptom 1 of component A can be set lower than the compensation constant for symptom 1 of component B. Therefore, for multiple components with different side effect symptoms, different statistical probabilities can be reflected, thereby obtaining an individualized probability of side effect occurrence.

[0099] In another embodiment, the server device 200 may set different compensation constants based on the number of consecutive times a user experiences the same side effects after taking the same ingredient.

[0100] For example, server device 200 can set the compensation constant for experiencing symptom 1 of component A twice consecutively to be greater than the compensation constant for the first experience of symptom 1 of component A. Therefore, the more experiences of taking different drugs accumulate, the more precisely individualized the probability of side effects can be obtained.

[0101] In another embodiment, the server device 200 may set different compensation constants for each other based on the intensity of the side effects of the user manager.

[0102] For example, server device 200 can set the compensation constant for experiencing symptom 1 of component A at intensity 2 to be greater than the compensation constant for experiencing symptom 1 of component A at intensity 1. Server device 200 can provide user terminal 100 with an interface that allows users to select the intensity of side effects they experience. Therefore, the more accumulated experiences of taking the medication, the more precisely individualized the probability of side effects occurring can be obtained.

[0103] In another embodiment, if the server device 200 determines that a previously taken drug has a blood concentration above a certain level, i.e., if it determines that the previously taken drug remains in the body, it can exclude it from the experience of calculating the probability of drug side effects.

[0104] For example, server device 200 confirms when a user previously took a medication containing ingredient A, calculates the blood concentration of ingredient A based on preset user health information, and excludes experiences that occur even if side effects are present if the blood concentration exceeds a preset baseline, thus preventing such experiences from being used to calculate the probability of drug side effects. Therefore, it is possible to exclude situations where repeated use of a drug due to previous medication increases the probability of drug side effects.

[0105] The above disclosure can be implemented as computer-readable code on a medium that records a program. A computer-readable medium can include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable media include hard disk drives (HDDs), solid-state drives (SSDs), silicon disk drives (SDDs), ROM, RAM, CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, etc.

[0106] Furthermore, the program may be specifically designed and configured for this disclosure, or may be known to those skilled in the art of computer software. Examples of programs include not only machine language code created using a compiler, but also high-level language code that can be executed by a computer using an interpreter.

[0107] In this disclosure (especially within the scope of the claims), the term "described" and similar descriptive terms are used in both the singular and plural forms. Furthermore, where a range is described in this disclosure, the application of individual values ​​belonging to the range is included, as is the description of each individual value constituting the range in the detailed description of the invention (unless otherwise stated).

[0108] If the steps constituting the method according to this disclosure are not described in an obvious order or a reverse order, the steps may be performed in an appropriate order. This disclosure is not necessarily limited by the order in which the steps are described. Throughout this disclosure, all examples or exemplary terms (e.g., etc.) are used merely to illustrate the disclosure in detail, and the scope of this disclosure is not limited to the examples or exemplary terms unless limited by the scope of the claims. Furthermore, it will be understood by those skilled in the art to which this invention pertains that the method of this disclosure can be configured within the scope of the claims, including various modifications, combinations, and alterations, or equivalents thereof, depending on design conditions and factors.

[0109] Therefore, the ideas of this disclosure should not be limited to the embodiments described above, and the scope of the subsequent claims, as well as all equivalent or modified scopes, should fall within the scope of this disclosure.

Claims

1. A method for calculating the probability of drug side effects using a computing device, comprising the following steps as each step is performed by the computing device: The medication taken by the confirmed individual; Confirm the side effects experienced by the subject based on the administration of the medication; The probability of occurrence of side effects related to the drug in relation to the subject is calculated based on the subject's experience with such side effects. in, The steps for calculating the probability of the occurrence of the side effect of the object include the following steps: The first disease diagnosed in the subject was confirmed. Confirm the first symptom of the first disease; and The calculation of the probability of occurrence of the side effect of the drug for the subject, based on whether the first symptom is consistent with the side effect, or whether it is reflected in the subject.

2. The personalized drug side effect probability calculation method of the computing device according to claim 1, wherein, The step of calculating the probability of occurrence of the side effect of the subject in relation to the drug includes the following steps: updating the probability of occurrence of the side effect whenever the subject inputs an experience of taking the drug.

3. The personalized drug side effect probability calculation method of the computing device according to claim 2, wherein, The step of updating the probability of occurrence of the side effect includes the following steps: updating the probability of occurrence of the side effect based on the experience of the subject not experiencing any side effects after taking the drug.

4. The personalized drug side effect probability calculation method of the computing device according to claim 2, wherein, The step of updating the probability of occurrence of the side effects includes the following steps: based on whether the side effects occurred after the subject took the drug, different algorithms are applied to update the probability of occurrence of the side effects for the subject.

5. The personalized drug side effect probability calculation method of the computing device according to claim 1, wherein, The step of calculating the probability of occurrence of the side effect of the subject based on whether the first symptom and the side effect are consistent includes the following steps: In cases where the first symptom is inconsistent with the side effect, at least one ingredient contained in the medicine is identified; Confirm whether the side effects of the first ingredient contained in the drug obtained from the drug database are consistent with the side effects input by the object; as well as If the side effects of the first symptom are consistent with the side effects of the subject, the probability of the subject experiencing the side effects of the first ingredient is increased.

6. The personalized drug side effect probability calculation method of the computing device according to claim 5, wherein, The step of increasing the probability of the occurrence of the side effects of the first ingredient in the object includes the following steps: increasing the probability of the occurrence of the side effects of the first ingredient in the object based on the statistical probability of the side effects of the first ingredient contained in the drug obtained from a drug database.

7. The personalized drug side effect probability calculation method of the computing device according to claim 5, wherein, The step of increasing the probability of the occurrence of the side effects of the object on the first component includes the following steps: increasing the probability of the occurrence of the side effects of the object on the first component based on the consecutive number of times the object has experienced the occurrence of the side effects on the first component.

8. The personalized drug side effect probability calculation method of the computing device according to claim 5, wherein, The steps to increase the probability of the occurrence of the side effects of the first component on the object include the following steps: Confirm the intensity of the side effect input by the object; and The probability of the side effects occurring in the object against the first ingredient is increased based on the intensity of the side effects.

9. The personalized drug side effect probability calculation method of the computing device according to claim 1, wherein, The step of calculating the probability of occurrence of the side effect for the subject based on whether the first symptom and the side effect are consistent includes the following steps: In cases where the first symptom is inconsistent with the side effect, at least one ingredient contained in the medicine is identified; Confirm whether the side effects of the first ingredient contained in the drug obtained from the drug database are consistent with the side effects input by the object; as well as The blood drug concentration caused by the previous use of the first ingredient is calculated based on the time elapsed since the subject previously took the drug containing the first ingredient and the subject's physical information, and the probability of the subject's side effects is calculated based on the blood drug concentration.

10. The personalized drug side effect probability calculation method of the computing device according to claim 1, wherein, The step of calculating the probability of occurrence of the side effects of the subject includes the following steps: reducing the probability of occurrence of the side effects of the subject against at least one ingredient contained in the drug, provided that no side effects occur as a result of taking the drug.

11. A computing device, comprising: processor; as well as A memory, functionally connected to the processor, stores at least one piece of code that is executed in the processor. The memory stores code that, when executed in the processor, causes the processor to: Confirm the medication taken by the individual. Confirm the side effects experienced by the subject based on their experience with the medication. Based on the subject's experience with the side effects, the probability of the subject experiencing side effects related to the drug is calculated. The memory also stores code that, when executed in the processor, causes the processor to reflect, or not reflect, the probability of the occurrence of the side effect of the drug on the object based on whether the first symptom of the first disease suffered by the object is consistent with the side effect.

12. The computing device according to claim 11, wherein, The memory also stores code that, when executed in the processor, causes the processor to update the probability of the side effects occurring each time the object inputs an experience of taking the drug.

13. The computing device according to claim 12, wherein, The memory also stores code that, when executed in the processor, causes the processor to apply different algorithms to update the probability of the side effects occurring in the subject based on whether or not a side effect occurs after the subject takes the drug.

14. The computing device according to claim 11, wherein, The memory also stores code that, when executed in the processor, causes the processor to increase the probability of the occurrence of the side effect of the first ingredient in the object when the first symptom is inconsistent with the side effect and the side effect of at least one ingredient contained in the drug is consistent with the side effect of the object.

15. The computing device according to claim 11, wherein, The memory also stores code that, when executed in the processor, causes the processor to reduce the probability of the occurrence of the side effects of at least one ingredient contained in the drug for the object, provided that the side effects of the drug are not caused by input from the object.

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