RU2593577C1 - Method of determining medicinal interactions and limitations to use of drugs with the help of structured knowledge base - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: invention relates to medicine, namely to creation of an information and search system upon interaction and contraindications of drugs. Using one or more processors the steps are initiated, on which a graph is oriented, in which the peaks are data entities containing multiple concepts interrelated with multiple ribs characterizing relations between the said entities, herewith the entities include at least data on the active substances (AS), pharmacological groups (FG), anatomical-therapeutic-chemical classifications (ATC), dosage forms (DF), methods of administration (MA), personal features of the body (PF), trade names of medications (TN) and pharmacological actions (FA); weight relations between the information entities are formed and the obtained ontology structure is saved in the machine-readable memory of the said electronic computing device or an external device communicating with the said electronic computing device used as a tool for data search.

EFFECT: inventions group allows to expand functional capabilities of a medical information system due to complex analysis of data on drug interactions and use limitations taking into account personal features of a patient, methods of administration and dosages of medications.

30 cl, 7 dwg

Description

FIELD OF TECHNOLOGY

The claimed invention relates to the field of creating a search structure built on the basis of many ontologies, used as a tool for searching data, in particular for searching interactions and restrictions on the use of various drugs.

BACKGROUND

A portable electronic device is known to assist a patient in the selection of medications (CN201111051 Y, XIAMEN UNIVERSITY [CN], 09/03/2008), which contains a database containing information about the possibility of using drugs based on data known from general information.

The disadvantages of this solution are the lack of assessment of the interaction of the active ingredients of the drug, the impossibility of analyzing the degree of drug interactions, as well as restrictions on the application, taking into account the patient’s personal characteristics, methods of administration and dosage of the prescribed drugs.

A known system for the diagnosis of drugs (JP 2004202075 A, HIGASHI NIHON MEDICOM KK [JP], 07/22/2004), which is an information system configured to analyze drug interactions.

The disadvantages of this system are the limited accuracy of data analysis, since the analysis process is carried out only on well-known drug data, not including additional data sources, such as: scientific articles, research reports, etc., also this system does not analyze the drug interaction of directly acting substances of drugs, does not analyze drug interactions taking into account data on the patient’s personal characteristics, does not take into account the route of administration and dosage of the prescribed drugs, and also does not determine restrictions on the use.

The Pharmacist Pro software application is known, which can automatically analyze the prescription sheet for the presence of drug interactions after adding another drug, displays the current drug drug interactions, provides an additional description for each drug drug interaction with links to authoritative publications and clinical trials (https: // itunes.apple.com/en/app/farmacevt-pro-proverka-sovmestimosti/id666172182?mt=8).

The disadvantages of this application are the inability to assess the degree of drug interactions and restrictions on the use of drugs, taking into account the personal characteristics of the patient, the prescribed dosage form and dosage, and the insufficient degree of reliability of the information.

The DrugChecker Interactions application is known, which is a directory of drug interactions that checks the compatibility of generic drugs online for any number of drugs taken at the same time, with the determination of the severity of the interaction.

The disadvantages of this system are the limited accuracy of data analysis, since the analysis process is carried out only on well-known data on drugs, not including additional data sources, such as: scientific articles, research reports, etc., also this system does not analyze the drug interaction directly acting substances of drugs, does not analyze drug interactions taking into account data on the patient’s personal characteristics, does not take into account the route of administration and dosage of the prescribed drugs, and also does not determine restrictions on the use.

The Pharmacist Pro software application is known, which can automatically analyze the prescription sheet for the presence of drug interactions after adding another drug, displays the current drug drug interactions, provides an additional description for each drug drug interaction with links to authoritative publications and clinical studies (proverka-sovmestimosti / id666172182? mt = 8).

The disadvantages of this application are the inability to assess the degree of drug interactions and restrictions on the use of drugs, taking into account the personal characteristics of the patient, the prescribed dosage form and dosage, and the insufficient degree of reliability of the information.

The DrugChecker Interactions application is known, which is a directory of drug interactions that checks the compatibility of generic drugs online for any number of drugs taken at the same time, with the determination of the severity of the interaction (rchENLite).

The disadvantages of this application are the inability to assess the degree of restrictions on use, taking into account the personal characteristics of the patient, the method of administration and dosage of the drug, as well as the insufficient degree of reliability of the information.

Known expert system "Drug Interaction", which is a system of analysis of drug interactions. Depending on the volume and degree of generalization of the presented informative information, all the rules describing the results of the interaction are divided into five levels:

a) - drug + drug

b) - drug + group of drugs

c) - group of drugs + group of drugs

d) - property (mechanism) + property (mechanism)

e) is a meta-rule for deriving the final spectrum of the changing effects of each of the interacting drugs.

The rules are expressed as an IF-TO statement. Rules may also be of the form IF-AND-TO-AND. In this case, a different number of “I” constituent elements is possible, which in some specific cases of the rule presentation can be combined with the “OR” logical element, as shown in the following example of the inference rule: IF drug A is used with drug B, and drugs are taken simultaneously, AND reception occurs on one route of administration OR reception occurs on different routes of administration, THEN should be expected: an increase in the effect of drug A And an increase in the effect of drug B.

The disadvantages of this solution are the impossibility of assessing the degree of drug interactions and restrictions on the use of drugs, taking into account the personal characteristics of the patient, the methods of administration and dosage of the prescribed drugs, and the insufficient degree of reliability of the information.

SUMMARY OF THE INVENTION

The task to which the claimed invention is directed is to create an information retrieval system built on the basis of a search structure for medical ontologies containing information about drugs, which makes it possible to determine the degree, nature, result and reliability of drug interactions and restrictions for use, taking into account the initial patient data containing information about personal characteristics of the patient’s body, methods of administration and dosages of prescribed drugs.

To obtain reliable data on the interaction of drugs, as well as assess their undesirable interaction both with each other and for the body of a particular patient, based on its physiological characteristics, methods of administration and dosage, it is necessary to use a lot of information that reveals various features of certain drugs, in particular, active substances, which are a key link for any drug. It is necessary to apply an organized structure for storing and searching information from a multitude of data arrays - information entities created using ontologies, with the possibility of evaluating and analyzing it, which in turn served as the creation of the claimed invention.

The technical result is to expand the functionality of the medical information retrieval system, due to a comprehensive analysis of data on drug interactions and restrictions on use (degree, nature, result and reliability), taking into account the initial patient data containing information about the patient’s personal characteristics, methods of administration and dosages of prescribed drugs.

The technical result is achieved due to the method of creating a search structure for interactions and contraindications for medicines, performed on an electronic computing device using one or more processors that initiate the stages in which:

- form a directed graph in which the vertices are informational entities containing many concepts connected by many edges characterizing the relationships between the mentioned entities, and the formation of entities includes:

- creation of an information entity containing data on active substances (DV);

creation of an information entity containing data on pharmacological groups (FG);

- creation of an information entity containing data on the anatomical-therapeutic-chemical classifications (ATX);

- creation of an information entity containing data on dosage forms (LF);

- creation of an information entity containing data on methods of application (SP);

- the creation of an information entity containing information about the source data of the patient (PO);

- the creation of an information entity containing data on the trade names of medicines (TN);

- the creation of an information entity containing data on pharmacological actions (PD);

- carry out the formation of weighted relationships between the above informational entities, the relationships being the interactions between the active substances and / or groups of drugs, and the restrictions on the use;

and

- save the resulting search structure in a machine-readable memory of said electronic computing device or an external device associated with said electronic computing device. In a particular embodiment of the claimed invention, interactions between active substances and / or groups of drugs are formed for entities of DV, FG, ATX.

In a private embodiment of the claimed invention, communication restrictions on the use are formed for entities of DV, PO, FG, ATX.

In a particular embodiment of the claimed invention, interactions between active substances and groups of drugs are formed between entity concepts such as: DV-DV, DV-FG, FG-FG, DV-ATX, ATX-ATX, FG-ATX, FD-FD.

In a private embodiment of the claimed invention, a clarifying relationship is formed between such entities as: types of drug interactions (TV), pathological signs (PP), SP, software, literary sources (IST) and a repository of textual descriptions of characters and interaction mechanisms.

In a particular embodiment of the claimed invention, at least one further refinement relationship for at least one restriction connection is further formed.

In a private embodiment of the claimed invention, a clarifying relationship is formed between the interaction interaction between the active substances and / or groups of drugs and such entities as: TV, PP, SP, PO, IST and a repository of textual descriptions of drug interactions.

In a particular embodiment of the claimed invention, unidirectional bonds are additionally formed between the entities of DV, VT, LF of the form DV-TH, DV-LF and TH-LF.

In a private embodiment of the claimed invention, each of the entities, such as: FG, ATX, PO, SP, LF, is a classifier with a tree structure.

In a particular embodiment of the claimed invention, the concepts within each entity of FG, ATX, PO, SP, LF are interconnected by generic bonds of the type Hyperimony-Hyponym.

In a private embodiment of the claimed invention, computer-readable memory is selected from the group of RAM, ROM, EEPROM flash memory, HDD, HDD SSD, CD-, DVD-, Blue-Ray magnetic disks or combinations thereof.

In a particular embodiment of the claimed invention, unidirectional bonds are additionally formed between the entities of DV, VT, LF of the form DV-TH, DV-LF and TH-LF.

In a private embodiment of the claimed invention, each of the entities, such as: FG, ATX, PO, SP, LF, is a classifier with a tree structure.

In a particular embodiment of the claimed invention, the concepts within each entity of FG, ATX, PO, SP, LF are interconnected by generic bonds of the type Hyperimony-Hyponym.

In a private embodiment of the claimed invention, computer-readable memory is selected from the group of RAM, ROM, EEPROM flash memory, HDD, HDD SSD, CD-, DVD-, Blue-Ray magnetic disks or combinations thereof.

The claimed technical result is also due to the method of searching for the interaction of drugs using the aforementioned search structure embodied on an electronic computing device containing the stages in which:

- accept a user request containing data of at least the names of the two drugs;

- carry out a data search in accordance with the user request in the entities of DV and VT;

- determine at least one active substance from the essence of DV for each drug product according to a user request;

- determine the level of evidence of the interaction of interrelated active substances;

- determine the priority of the relationship of interaction based on the distance between a pair of interconnected active substances, the degree of interaction and the level of evidence;

and

- give the result of the drug interaction for a pair of interconnected DV based on the priority of the interaction link.

In a particular embodiment of the claimed invention, the user request further comprises data on the dosage form and / or dosage and / or method of administration of the drug and / or patient information.

In a particular embodiment of the claimed invention, the patient information includes: age, and / or gender, and / or height, and / or weight, and / or disease information, and / or pregnancy information, and / or gestational age, and / or allergy information.

In a particular embodiment of the claimed invention, in addition to each active ingredient detected, a dosage form, dosage and route of administration are determined by searching the relationships between the concepts of the essence of DV-LF, DV-SP.

In a particular embodiment of the claimed invention, the relationships between the active substances of an interacting pair are determined by the relationships between the entity concepts DV-DV, DV-FG, DV-ATX, FG-FG, FG-ATX, ATX-ATX.

The claimed technical result is also achieved due to the method of searching for restrictions on the use of funds using the aforementioned search structure embodied on an electronic computing device containing stages in which:

- accept a user request containing data of at least the name of one drug and data about the patient;

- carry out a data search in accordance with the user request in the entities of DV and VT;

- determine at least one active substance from the essence of DV for at least one name of the medicinal product according to a user request;

- determine for each active ingredient found pharmacological groups and anatomical-therapeutic-chemical classifications using entities of FG and ATX, as well as their parent groups by generic relationships within the entities of FG and ATX;

- determine the relationship of restrictions on the use between at least one active substance and the source data of the patient by searching the relationship of the concepts of the essence of DV-PO, FG-PO, ATX-PO;

- determine at least one restriction to use from the essence of software for at least one found active substance from the essence of DV;

- determine the degree of restriction for use for at least one active substance, depending on the initial patient data from the essence of the software;

- determine the distance between the interconnected at least one DW and at least one PO, depending on the number of generic relationships in the entities of the FG and ATX between them;

- determine the level of evidence of at least one connection restrictions to use between at least one active substance and at least one software from an interconnected pair of DV-software;

- determine the priority of the relationship of restrictions on use between at least one active substance of the active ingredient and at least one software according to the degree of restriction to use, the level of evidence of limitations to use, and also the distance between the interconnected elements

and

- give the result of the restriction to the use of at least one medicinal product and at least one restriction to use based on the priority of the connection restrictions to use.

In a private embodiment of the claimed invention, the user request further comprises data on the dosage form and / or dosage and / or method of administration of the drug.

In a private embodiment of the claimed invention, patient data includes: age, and / or gender, and / or height, and / or weight, and / or disease information, and / or pregnancy information, and / or gestational age, and / or allergy information.

In a particular embodiment of the claimed invention, in addition to each active ingredient detected, the dosage form, dosage and route of administration are determined by searching through the relationships of the concepts of the essence of DV-LF, DV-SP.

In a particular embodiment of the claimed invention, the interactions between the active substances and the patient's initial data, DV-PO, are determined by analyzing the relationships of the concepts of the essence of DV-PO, FG-PO, ATX-PO.

In a particular embodiment of the claimed invention, additionally, for each active substance, conditions for restriction to use (UO) and initial data restricting use (VET) are determined.

In a private embodiment of the claimed invention, the level of evidence of restrictions on the use of active substances is determined depending on the presence of evidence of the explanation of the chemical or pharmacological nature of the restriction on use, as well as on the authority of the literary source of IST.

BRIEF DESCRIPTION OF THE DRAWINGS

In FIG. 1 shows the graph structure of the claimed search structure.

In FIG. Figure 2 shows the type of weighted relationship that specifies interactions.

In FIG. 3 shows a type of weighted relationship specifying contraindications.

In FIG. 4 shows a variant of the scheme for determining distances (4 steps) between pairs of active substances.

In FIG. 5 shows a variant of the scheme for determining distances (1 step) between pairs of active substances.

In FIG. 6 shows a variant of the scheme for determining distances (4 steps) between the active substance and the corresponding contraindication.

In FIG. 7 shows a variant of the scheme for determining distances (1 step) between the active substance and the corresponding contraindication.

DETAILED DESCRIPTION OF THE INVENTION

In FIG. 1 shows a general view of a search structure made in the form of a directed graph 100, which is used to search for data and the interaction between information entities - data warehouses. The vertices of column 100 are information entities containing information about various fields of knowledge, presented in the form of many concepts. Concepts are medical terms that reflect individual concepts, for example, pharmacological groups, ATX groups, active substances, trade names, dosage forms, methods of application, pharmacological actions, pathological signs, age and gender groups and other signs related to the personal characteristics of the body, which are initial data of the patient.

Connections between vertices indicate relationships between entities and form the edges of graph 100. Each concept has its own unique ID, name and may have synonyms. For example, “anti-adhesive”, “analgesic”, “uterotonizing”, “fungistatic”, “secretomotor”, etc. are concepts within the essence of “Pharmacological actions”.

In a preferred embodiment of the claimed invention, graph 100 is constructed from such entities as active substances (DV) 110, pharmacological groups (FG) 120, anatomical and therapeutic chemical classifications (ATX) 130, dosage forms (LF) 140, methods of use (SP ) 150, initial patient data (PO) 160, trade names (TN) 170 and pharmacological actions (PD) 180.

The edges of graphs can be divided into four main types: 1) generic relations of the type Hyperonym - hyponym; 2) communications describing affiliation; 3) weighted relationships describing the phenomena; and 4) specifying relationships.

Unidirectional connections are formed between the entities, providing interaction between the entities. Between entities DV 110, PO 160, ATX 130 and FG 120, weight bonds 111 and 112 are additionally formed. Weight bonds can be of two types: bond 111 - interactions between active substances and groups of drugs and bond 112 - restrictions on use. Weighted links 111 are formed between entities ДВ 110, ФГ 120 and АТХ 130. Also weighted links 111 are formed for individual entities, within an entity, for example, for entities ДВ 110, ФГ 120 and АТХ 130. Weighted links 112 of restrictions for use are formed for entities ДВ 110 , FG 120, ATX 130 and PO 160. Weighted links 111 form the following relationships between entities: DV-DV, DV-FG, FG-FG, DV-ATX, ATX-ATX, FG-ATX, these weighted links 111 are bidirectional. Weighted relationships 112 form relationships between entities, such as: DV-PO, FG-PO, ATX-PO. Weighted relationships determine the procedure for accessing data between entities when using the claimed medical information base of knowledge. Weight links 112 are unidirectional.

Concepts interconnected by generic ties form entity classifiers in the form of a tree, these entities are: FG 120, ATX 130, PO 160, SP 150, LF 140, types of drug interactions (TB) 210 and pathological signs (1111) 220 (see Fig. 2). Data in entities ДВ 110, ТН 170 and ФД 180 are grouped into separate lists and do not form a birch tree.

In FIG. 2 and FIG. Figure 3 shows the clarifying bonds that are formed for weight bonds 111 and 112 in the analysis of interactions between active substances, as well as contraindications for the patient. In FIG. 2 depicts the principle of building bonds in the refinement of interactions between active substances. For weighted links 111, a series of clarifying links 113 is formed between the entities of TV 210, PP 220, SP 150, PO 160, literary sources (IST) 230 and a repository of textual descriptions of characters and mechanisms of interaction or contraindications 240. Using the appeal to the essence of TV 210, the character is determined the interaction of the active elements 250 and 260, when referring to the essence of PP 220, the clinical result of the interaction of the active elements 250 and 260 is determined: syndromes, symptoms, reactions, conditions, etc. Under the active elements 250, 260 are meant active substances, or a pharmacological group, or a chemical group. Using the essence of SP 150, the conditions are determined under which interaction with the active element 250 or 260 occurs. Using the essence of software 160, personalization of interaction (PVZ) or contraindications (nosology and personal characteristics of the body) for each of the elements 250 and 260 are determined. Essence IST 230 is a data warehouse containing information on published scientific papers in which there is fundamental evidence of the interaction of the active elements 250 and 260. Position 270 denotes the parameter "d", Evidence shows otorrhea interactions or contra parameter "a" (position 280) indicates the degree of interaction or contraindications.

The level of evidence “d” 270 depends on the presence of facts of confirmation (explanation) of the chemical or pharmacological nature of the interaction, as well as on the authority of the literary source.

¥ - an unconditional level of evidence. There is a fundamental explanation of the nature of the interaction. The chemical formula of the compounds and the chemical process (reaction) of interaction are known. The known mechanism of the pharmacological action of the compounds and the nature of the pharmacological interaction. Most often, this level of evidence is characteristic of pharmaceutical and pharmacokinetic interactions, which are based on a physicochemical nature.

The source can be textbooks on pharmacology, teaching aids, clinical recommendations, reference books, encyclopedias, monographs.

A - a very high level of evidence. Information is confirmed by official sources, well-known and confirmed by many years of clinical practice, however, can not be explained fundamentally. Most often, this level of evidence is characteristic of pharmacodynamic interactions, which are caused by much more complex mechanisms.

The source of information can be textbooks on pharmacology, reference books, encyclopedias, teaching aids, clinical guidelines, monographs (with the author and affiliation to the publication).

B - high level of evidence. The information is confirmed by the results of meta-analyzes and systematic reviews, the results of large randomized controlled trials, large epidemiological studies, long-term clinical observation involving a large number of patients (≥1000), as well as the results of pharmacological studies.

The source of information can be systematic reviews, meta-analyzes, officially published clinical data, including observational epidemiological and pharmacological studies, literature reviews, original and review articles (with the author and affiliation to the publication).

C is the average level of evidence. The information is confirmed by the results of small randomized controlled trials in which statistics are built on a small number of patients (less than 1000), pharmacological studies, clinical observations and the experience of reputable experts.

The source may be a scientific publication, article, literature review, presentation, lecture (with the author, possibly without belonging to the publication).

D - low level of evidence. The information was developed by a group of experts by consensus on a specific problem, based on opinions or clinical experience.

The source can be a faceless Internet resource without links to official publications, an unidentified Internet resource without an author, without belonging to the publication.

X is a very low level of evidence. Unproven assumption, expert opinion. There is no confirmation in the literature.

Unknown source of information (link may be missing).

In FIG. Figure 3 shows the principle of building connections when specifying contraindications to the administration of the active substance by a specific patient, depending on his personal characteristics. For weighted relationships 112, clarifying relationships 113 are built that organize the interaction between the entities of SP 150, IST 230, a repository of textual descriptions of characters and mechanisms of interaction or contraindications 240 and entity PO 290, which stores data on the personal characteristics of the body, such as gender and age groups, racial groups, pathological conditions, hereditary factors, etc. For each active element 250 or 260, a weight relationship 112 is built, with the help of which the presence of the corresponding one or more contraindications is determined from the essence of PO 160 for the corresponding active element 250 or 260, and the mentioned contraindication depends on the initial data of the patient. The value of the weight relationship 112 — the relationship of contraindications and risks, depends, like the weight relationship 111, on the parameters “a” 270 and “d” 280. By forming a refinement relationship 113 between the weight relationship 112 and the nature of SP 150, the method of administration and dosage (SCP) of the corresponding active element 250 or 260. Using the clarifying relationship FROM the essence of PO 160, the initial data of the patient are determined.

Consider the principle of accessing the claimed medical search structure. The search structure implemented on the electronic computing device receives user request data containing the names of the drugs entered through a special search line, or directly in the task field, where you can add the dosage form, dosage and method of drug administration. If necessary, the user can enter the initial data of the patient: age, gender, height, weight, underlying disease, concomitant diseases, the presence of pregnancy and gestational age, breastfeeding, the presence of allergies to certain drugs, professional affiliation. Fields indicating the presence of pregnancy and breastfeeding are allowed for input, if the gender is female, and the age is more than 15 years. The gestation period may be indicated if pregnancy is indicated. Information about the main and concomitant illness is entered into the corresponding text fields through the search bar. At the end of information input, user data is transmitted to the server for further processing. When the data arrives at the server, the system searches the list of injected drugs (taking into account the morphology and possible spelling errors) in the DV and VT entities, with the search priority in the DV entity, thus, the drug is first searched by the DV entity, and if the result is negative , then the search continues among the data of the essence of VT. For each trade name, the active substances are found by the relationships between the entities DV-> VT. Moreover, one trade name in the case of a combined dosage form will have more than one active substance. Further, the system checks the dosage form indicated by the user, the dosage and the route of administration of the prescribed drugs for each DV, respectively, using the links DV-> LF, TH-> LF, LF-> SP, if such information was entered by the user.

When determining the interaction between the drugs entered in the user request, the names of at least two drugs are determined. Then, data is searched in accordance with a user request in the entities DV 110 and TH 170, at least one active substance is determined from the essence of DV 110 for each drug according to a user request, pharmacological groups and anatomical and therapeutic are determined for each active substance found -chemical classifications using entities FG 120 and ATX 130, as well as their parent groups according to generic relationships within entities FG 120 and ATX 130. For each active substance, op edelyayutsya his group (FG, ATC) and all of their parents in the tree of of generic relations. The interactions between the mentioned active substances are determined, and a search is carried out for all possible relationships that determine the interactions (interaction 111 interaction) between a pair of interconnected active substances and the degree of evidence of interaction of the active substances. The degree of interaction between the DW 250, 260 depends on the CVI and the degree of evidence of the data - "d" 270 (Fig. 2). Price of 1 step = 1, i.e. the more steps, the more points; price of evidence: from 0 (unconditional degree) to 6 (very low degree). The level of evidence is determined based on the source of information and the availability of fundamental evidence of the presence of interaction. In addition, for each active substance, the dosage form, dosage and route of administration are determined by searching on the substances DV 110, LF 140, TN 170, SP 150. By means of qualifying bonds 113, UVZ and PVZ are determined.

In FIG. 4, FIG. 5 shows variants of schemes for determining the distances between the active substances DV1 and DV2 (250, 260). The number of bonds in the tree classifiers FG 120 and ATX 130 is calculated, which binds the interacting active substances 250 and 260.

When determining contraindications to the use of drugs and the risks of undesirable consequences for the patient, the following steps of the method are carried out.

A user request is received containing at least one drug name and patient data. Data is searched in accordance with a user request in the entities DV 110 and TH 170, based on the search, at least one active substance is determined from the essence of DV 110 for at least one drug name according to the user request.

Next, for each found active substance, pharmacological groups and anatomical-therapeutic-chemical classifications are determined using entities FG 120 and ATX 130, as well as their parent groups according to the genus-specific relationships within entities FG 120 and ATX 130.

The interactions between at least one active substance and the personal characteristics of the patient’s organism are determined by searching the entities DV 110 - ON 160, at least one contraindication is revealed from the essence ON 160 for at least one found active substance from the essence of DV 110. A search is carried out for all possible connections that determine contraindications and risks to use (connection of contraindications 112) between the elements found, using the links DV-> PO, FG-> PO, ATX-> PO.

The degree of contraindication “a” 280 is determined for at least one active substance depending on the personal characteristics of the patient from the essence of PO 160. The distance between the interconnected at least one DV 110 and at least one contraindication from the essence is determined PO 160, depending on the number of generic relationships in the entities of FG 120 and ATX 130 between them. Determine the level of evidence "d" 270 of at least one

contraindications for at least one active substance from an interconnected DV-PO group, price of 1 step = 1, i.e. the more steps, the more points. The price of the level of evidence: from 0 (unconditional degree) to 6 (very low degree).

The weighting coefficient of contraindications is determined on the basis of the distance between the interconnected at least one active substance from the essence of DV 110 and at least one contraindication from the essence of PO 160, the degree of evidence of contraindications and the degree of contraindication. The level of evidence of contraindication "d" 270 is determined by referring to the essence of IST 230, and each source of information is assigned a weight coefficient that is taken into account when calculating the final score for the found data source.

If specifying signs (dosage form, dosage, route of administration and / or initial patient data) were indicated when prescribing the drug, then when searching for a contraindication relationship to the corresponding active substance, clarifying links 113: AMR and RFP are taken into account.

In FIG. Figures 6–7 show schemes for determining the distances between the active substance 250 and the associated contraindication from the essence of PO 160. For each analyte of the active substance, for example, DV1 250, all its groups are determined by the entities FG 120 and ATX 130, as well as all their parents in the tree classifiers by generic relations. The distance between the active substance 250 and its associated at least one contraindication PO1 161, PO2 162, PO3 163 depends on the number of generic relationships between entities.

In a particular embodiment, the dosage form, dosage, and method of application may also be added to any of the drugs entered in the request. After determining the drug using the query to the entities of TN 170 or DV 110, it is possible to select a dosage form, which is carried out using the connection with the essence of LF 140. The list of acceptable forms is determined by the connection TH-> LF or DV-> LF with the priority of the search for the essence of TN 170. This means that initially the search for a dosage form is carried out on the basis of TH 170, using the links TH-> LF. If the result is negative, then the search is carried out by the essence of DV 110, using the connections between the entities of DV-> LF. Next, you can determine the dosage of the drug from the list of possible dosages for this combination, which is carried out using the relationships between the concepts of essences DV-> LF or TH-> LF. The system can determine the method of application using a query to the essence of SP 150 for the above combination of drugs and dosage form, using the relationship LF-> SP. In this case, all acceptable methods of application from the essence of SP 150 are determined and all child elements of the essence of SP 150 are displayed, from which the preferred method of drug administration is selected.

The above methods for determining the interaction between active substances, determining contraindications for active substances, and determining substitutions for drugs are performed on an electronic computing device, moreover, the search for the knowledge base can be performed both on the user side and on the server device side. The structure of the knowledge base 100, providing the execution of the process of searching and analyzing data, is created using electronic computing means, such as, for example, a processor or microprocessor, and is stored in a machine-readable memory of an electronic computing device or an external device associated with the said electronic computing device.

Machine-readable memory is selected from the group: RAM, ROM, EEPROM flash memory, HDD, SSD, CD-, DVD-, Blue-Ray magnetic disks, or combinations thereof.

The system "learns" and can be improved independently, processing incoming information and statistics on doctor's prescriptions. In addition, the system can take into account expert opinions and adjust the level of evidence of this or that knowledge depending on the number of “votes”. The system enables the user to make changes to its content (to a certain circle of users with the appropriate qualifications) with the obligatory verification and approval of the moderator. If the system does not find the name of the drug, it gives information that the drug was not found with a proposal to add it to the system, so the system will be filled with new names, which will subsequently be supplemented with the necessary characteristics by the system moderator. The system analyzes its own errors and notifies the moderator of the need to make changes if, for example, a user of the system ignores the recommendation and writes out a prescription with an “error”.

If contraindications for use and risks of possible adverse reactions for the patient are detected, the system displays this information characterizing the essence of the adverse reaction, respectively, for example, contraindications for use during pregnancy, lactation, etc. In parallel with adverse interactions, the system identifies favorable interactions with substances that are not included in the checked list, checks for conflicts with each of the elements in the list, and if there are no negative links, it recommends including it in the list of prescriptions in order to improve the quality of treatment (for example, for reduce the risk of adverse reactions). The user also has the ability to enter information clarifying the features of the regimen of the drug, a different dosage, dosage form, route of administration or special instructions.

A computer-based information system built on the basis of the medical knowledge base 100 allows you to implement the function of automatically generating a prescription. At the user's request, a verified list of drugs can be issued in the form of one or more recipes. Drugs are analyzed by the system for relevance to the list of such type of drugs as psychotropic, narcotic or general list with the help of a request to the corresponding data warehouses. If the request entered by the user contains psychotropic and / or narcotic drugs, then the system initiates the generation of a special form on which data on one name of the psychotropic and / or narcotic drug is entered, taking into account the requirements for registration. The drugs of the general list are made out in one list (on one form no more than 10 drugs) indicating the dosage, dosage form, route of administration and mode of administration. The system offers the function of translating all the names of prescribed drugs into the form of international nonproprietary names (according to the current legislation). If the system does not determine the active substance, it allows the user to fill in the empty fields manually, to determine the form of the form for discharge. When integrated into the medical information system (MIS), the general fields relating to data about the clinic, doctor and patient are automatically filled.

The claimed information system can be implemented on various types of computers, such as: personal computer, laptop, mainframe, smartphone, tablet, PDA, phablet, thin client, etc.

The claimed search structure of medical information about the interaction and contraindications of drugs 100 can be built on a central computing device, for example, a computer-based server, and provide the ability to search data for a wide range of users using wired or wireless data transfer methods, such as: the Internet, Internet, Wi-Fi, LAN, WAN, WLAN, etc. The computing server containing the search structure 100 may be a cloud data storage.

The information on the implementation of the claimed invention set forth in these materials of the application should not be interpreted as limiting other, private embodiments of the claimed invention that do not go beyond the disclosure of information of the application, and which should be obvious to a person skilled in the art having the usual qualifications, which calculated the claimed technical solution.

The claimed group of inventions can be widely used in the field of healthcare, namely, to provide centralized information for medical personnel about drug interactions, to analyze contraindications for patients, to select replacement drugs and to automatically generate prescriptions.

Claims (30)

1. A method of creating a search structure for interactions and contraindications for medicines performed on an electronic computing device, the method comprising the steps of:
- form a directed graph in which the vertices are informational entities containing many concepts connected by many edges characterizing the relationships between the mentioned entities, and the formation of entities includes:
- creation of an information entity containing data on active substances (DV);
- creation of an information entity containing data on pharmacological groups (FG);
- creation of an information entity containing data on the anatomical-therapeutic-chemical classifications (ATX);
- creation of an information entity containing data on dosage forms (LF);
- creation of an information entity containing data on methods of application (SP);
- the creation of an information entity containing information about the source data of the patient (PO);
- the creation of an information entity containing data on the trade names of medicines (TN);
- the creation of an information entity containing data on pharmacological actions (PD);
- carry out the formation of weighted relationships between the above information entities, and the relationship is the relationship of the interaction between the active substances and / or groups of drugs and communication restrictions on use;
and
- save the resulting search structure in a machine-readable memory of said electronic computing device or an external device associated with said electronic computing device. 2. The method according to p. 1, characterized in that the bonds of interactions between the active substances and / or groups of drugs are formed for the entities DV, FG, ATX. 3. The method according to p. 1, characterized in that the constraints on the use are formed for the entities DV, PO, FG, ATX. 4. The method according to p. 2, characterized in that the entities are formed as: DV-DV, DV-FG, FG-FG, DV-ATX, ATX-ATX, FG-ATX, FD-FD. 5. The method according to p. 3, characterized in that the entities are formed as: DV-PO, FG-PO, ATX-PO. 6. The method according to p. 4, characterized in that the connections are bidirectional. 7. The method according to p. 5, characterized in that the connections are unidirectional. 8. The method according to p. 4, characterized in that at least one further clarifying relationship is formed for at least one interaction interaction between the active substances and groups of drugs. 9. The method according to p. 8, characterized in that the clarifying relationship is formed between such entities as: interaction characteristics, including types of drug interactions and interaction results (TV), dosage types and pathological signs (PP), SP, software, literary sources (IST) and a repository of textual descriptions of characters and interaction mechanisms. 10. The method according to p. 5, characterized in that it is additionally formed at least one clarifying relationship for at least one communication restrictions to use. 11. The method according to p. 10, characterized in that the clarifying relationship connects such entities as: TV, PP, SP, PO, IST, a repository of textual descriptions of drug interactions. 12. The method according to p. 1, characterized in that additionally formed unidirectional relationships between the concepts of the entities of DV, TH, LF type DV-TH, DV-LF and TH-LF. 13. The method according to p. 1, characterized in that each entity, such as: FG, ATX, PO, SP, LF is a classifier with a woody structure. 14. The method according to p. 13, characterized in that the concepts within the entities are interconnected by generic relationships of the type Hyperimony-Hyponyms. 15. The method according to p. 1, characterized in that the machine-readable memory is selected from the group: RAM, ROM, EEPROM flash memory, HDD, hard drive SSD, magnetic disks CD-, DVD-, Blue-Ray, or a combination thereof. 16. A method for searching for drug interactions using a search structure created according to any one of paragraphs. 1-15 and embodied on an electronic computing device, comprising stages in which:
- accept a user request containing data of at least the names of the two drugs;
- carry out a data search in accordance with the user request in the entities of DV and VT;
- determine at least one active substance from the essence of DV for each drug according to a user request;
- determine for each active ingredient found pharmacological groups and anatomical-therapeutic-chemical classifications using entities of FG and ATX, as well as their parent groups by generic relationships within the entities of FG and ATX;
- determine for each active ingredient found pharmacological actions using the essence of PD;
- determine the relationship of interaction between the aforementioned active substances;
- identify pairs of interconnected active substances;
- determine the distance between a pair of interconnected active substances, depending on the number of generic bonds in the entities of FG and ATX between them;
- determine the degree of interaction of interconnected active substances;
- determine the level of evidence of the interaction of interrelated active substances;
- determine the priority of the relationship of interaction based on the distance between a pair of interconnected active substances, the degree of interaction and the level of evidence;
and
- give the result of the drug interaction for a pair of interconnected DV based on the priority of the interaction link. 17. The method according to p. 16, characterized in that the user request further comprises data on the dosage form and / or dosage, and / or the method of administration of the drug, and / or information about the patient. 18. The method according to p. 17, characterized in that the patient information includes: age, and / or gender, and / or height, and / or weight, and / or disease information, and / or information about pregnancy, and / or gestational age and / or allergy information. 19. The method according to p. 18, characterized in that, in addition, for each identified active substance, the dosage form, dosage and method of administration are determined by searching the relationships between the concepts of the essence of DV-LF, DV-SP. 20. The method according to p. 16, characterized in that the relationships between the active substances of the interacting pair are determined by the relationships between the concepts of the entities DV-DV, DV-FG, DV-ATX, FG-FG, FG-ATX, ATX-ATX. 21. The method according to p. 16, characterized in that in addition for each interacting pair of active substances determine the conditions of interaction (UVZ) and personalization of interaction (PVZ). 22. The method according to p. 16, characterized in that in addition to each interacting pair of active substances determine the type and result of the interaction (TV and PP). 23. The method according to p. 16, characterized in that the level of evidence of the interaction of interconnected active substances is determined depending on the presence of evidence of the chemical or pharmacological nature of the interaction, as well as on the authority of the literary source of IST. 24. The method of searching for contraindications to the use of drugs using the search structure created according to any one of paragraphs. 1-15 and embodied on an electronic computing device, comprising stages in which:
- accept a user request containing data of at least the name of one drug and data about the patient;
- carry out a data search in accordance with the user request in the entities of DV and VT;
- determine at least one active substance from the essence of DV for at least one name of the medicinal product according to a user request;
- determine for each active ingredient found pharmacological groups and anatomical-therapeutic-chemical classifications using entities of FG and ATX, as well as their parent groups by generic relationships within the entities of FG and ATX;
- determine the relationship of restrictions on the use between at least one active substance and the source data of the patient by searching the relationship of the concepts of the essence of DV-PO, FG-PO, ATX-PO;
- determine at least one restriction to use from the essence of software for at least one found active substance from the essence of DV;
- determine the degree of restriction for use for at least one active substance, depending on the initial patient data from the essence of the software;
- determine the distance between the interconnected at least one DW and at least one PO, depending on the number of generic relationships in the entities of the FG and ATX between them;
- determine the level of evidence of at least one connection restrictions to use between at least one active substance and at least one software from an interconnected pair of DV-software;
- determine the priority of the relationship of restrictions on use between at least one active substance of the active ingredient and at least one software according to the degree of restriction to use, the level of evidence of limitations to use, and also the distance between the interconnected elements
and
- give the result of the restriction to the use of at least one medicinal product and at least one restriction to use based on the priority of the connection restrictions to use. 25. The method according to p. 24, characterized in that the user request further comprises data on the dosage form and / or dosage and / or method of administration of the drug. 26. The method according to p. 24, wherein the patient data includes: age, and / or gender, and / or height, and / or weight, and / or disease information, and / or pregnancy information, and / or gestational age and / or allergy information. 27. The method according to p. 25, characterized in that, in addition, for each identified active substance, the dosage form, dosage and method of administration are determined by searching the relationship of the concepts of the essence of DV-LF, DV-SP. 28. The method according to p. 24, characterized in that the interactions between the active substances and the initial patient data DV-PO are determined by analysis of the relationships of the entities DV-PO, FG-PO, ATX-PO. 29. The method according to p. 28, characterized in that in addition to each active substance determine the conditions of restriction to use (UO) and the initial patient data, limiting the use of (VET). 30. The method according to p. 24, characterized in that the level of evidence of restrictions on the use of active substances is determined depending on the availability of evidence of the chemical or pharmacological nature of the restrictions on use, as well as on the authority of the literary source of IST.

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