Autonomous Databases Research Articles

Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning

Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in NoSQL databases all levels of representation are considered: conceptual, logical, and physical. This is mainly because the latter are mostly schema-less and lack a standard schema design procedure as is the case for SQL databases. In this work, we carry out a systematic literature survey on automatic schema design in both SQL and NoSQL databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions. Our comprehensive analysis demonstrates that, despite substantial progress that has been made, schema design is still a developing field and considerable challenges need to be addressed, notably for NoSQL databases. We highlight the most important findings from the results of our analysis and identify areas for future research work.

Automatic SQL Error Mitigation in Oracle

Despite best coding practices, software bugs are inevitable in a large codebase. In traditional databases, when errors occur during query processing, they disrupt user workflow until workarounds are found and applied. Manual identification of workarounds often relies on a trial-and-error method. The process is not only time-consuming but also requires domain expertise that users are often lacking. In this paper, we propose a framework to automatically mitigate errors that occur during query compilation (including optimization and code generation) without any user intervention. An error is intercepted by the database internally, a workaround is identified for it, and the query is recompiled using the workaround. The entire process remains transparent to the user with the query being executed seamlessly. The proposed technique handles SQL errors during query compilation and provides three types of mitigation strategies - i) quickly failover to one of the readily-available historical plans for the statement ii) apply targeted error-correcting directives (hints) identified from the optimizer context at the time of the error iii) modify the global configuration of the optimizer using hints. This feature has been implemented and will be released in an upcoming version of Oracle Autonomous Database.

BIM dimensions: example of air blower station at wastewater treatment plant

The main goal of research is to analyse the prospects for the development of BIM dimensions (3D-7D) in Russia on the example of Water and wastewater industry (WWI) asset. Justification of goal is the insufficient development of industry-specific BIM systems, allowing for different interpretations of its dimensions. The object of research is the air blower station (ABS), the most energy-intensive asset, which typically consumes 62-85% of the energy of WWTP’s. The method is a hypothesis of 3D-7D modeling of water utility asset, presented for the discussions. ABS compressors reduce costs by regulating the air supply due to lifestyle of the population and seasonal environmental conditions (example of simulation results is present). 3D design visualises variant of the reconstruction of the ABS, implemented according to typical project. 4D planning represent the schedule of energy service company, which provides investments and jobs for: design documentation execution, equipment purchase, installation and commissioning of equipment. 5D costs analyses features of the phase in terms of project expertise. 6D sustainability model in practice differs from prediction or forecasting generated by the simulation model of ABS asset, power consumption will be lower up to real (not simulated) technological loads. 7D management analyses possibility of the life cycle cost estimation as strategic advantage of WWI standard. The paper is based on Russian standards. Designing of 3D models are developing on an irregular basis (proactively) in Russia. The mastering of modeling 3D, 4D, 5D based on individual disciplines (as autonomous databases) is self-sufficient today as WWI tusk. The operational nature of WWI enterprises testifies to the development of elements of 6D-7D models.

GENDER CHARACTERISTICS OF ADVERSE DRUG REACTIONS DEVELOPMENT: EXPERIENCE OF REGIONAL DATABASE ANALYSIS

The aim of the article is the gender characteristics study of the adverse drug reactions (ADRs) development based on the data of the notification forms registered in the regional database ARCADe (Adverse Reactions in Crimea, Autonomic Database), for the period from 2009 to 2018.Materials and methods. The objects of the study were 6903 notification forms about adverse drug reactions recorded in the regional database called ARCADe (Adverse Reactions in Crimea, Autonomic Database) for the period from 2009 to 2018. The classification of drugs for separate pharmacological groups was carried out using the codes of the Anatomical Therapeutic Chemical (ATC) classification system of the World Health Organization (WHO) medicinal products, the instructions data of the State Registers of medicinal preparations used in the Russian Federation and Ukraine (for the cases registered before the entry of the Republic of Crimea into the Russian Federation).Results. A general analysis of the number of cases of the adverse drug reactions (ADRs) development in patients of different genders made it possible to determine that 59.9% (4132 notification forms) of ADRs cases were observed in female patients; 37.7% (2602 cases) – in male patients. In 169 cards (2.4%), information about a patient’s gender was missing. The groups with the largest number of the registered cases of ADRs were antimicrobial agents for a systemic use (2864 cases, 41.5% of the total number of the ADRs registered cases), the drugs affecting the cardiovascular (811 cases, 11.7%) and nervous (734 cases, 10.6%) systems. In each of the presented groups, the incidence rate of ADRs in female patients exceeded that in men.Conclusion. The study of the gender characteristics of the pharmacotherapy safety, carried out on the basis of the notification forms of the ADRs data registered in the Republic of Crimea, confirmed a higher likelihood of developing ADRs in female patients. This may be due to the peculiarities of the pharmacokinetics and pharmacodynamics of drugs in the female body, psychological factors, a more frequent use of drugs by this category of people. The implementation of the drug, taking into account specific features of each gender, can lead not only to better treatment outcomes, but also to increased patients’ compliance.

Study of Safety of Medicinal Products in Pregnant Women in Crimea

According to international epidemiological studies, about 80% of women have to use medicinal products during pregnancy, mainly during the first weeks of organogenesis in the case of an unplanned pregnancy, and for the treatment of chronic diseases or acute conditions developing during pregnancy. Specificity of pharmacokinetics and pharmacodynamics in pregnant women contributes to the development of adverse drug reactions (ADRs), many of which are serious and pose a threat to the life of the patient. The aim of the study was to retrospectively assess the frequency and development of ADRs in pregnant women living in the Republic of Crimea, based on the data in the regional safety database ARCADe (Adverse Reactions in Crimea, Autonomic Database). Materials and methods: the authors analysed spontaneous ADR reports registered in the ARCADe database from 1 January 2009 until 31 December 2018 for the category of patients described as “Pregnant women/childbirth”. Results: during the specified period, 268 ADR cases in pregnant women were added to the database. The most common reasons of ADRs in this category of patients were antibacterials for systemic use (130 cases, 48.5%), agents that have an effect on haematopoiesis and blood (54 cases, 20.15%), and agents that have an effect on the functions of the gastrointestinal tract (29 cases, 10.82%). The study of ADR clinical manifestations revealed a high incidence of local allergic reactions (140 cases, 52.2%), inhibition of haematopoiesis (60 cases, 22.4%), and dyspepsia (36 cases, 13.4%). The analysis of the severity of the registered ADRs demonstrated that in 15 cases (5.6%) the use of the prescribed medicinal product posed a threat to the patient’s life and required urgent pharmacotherapy and discontinuation of the suspected medicine, in 8 cases (3%) it resulted in hospitalisation or prolongation of hospital treatment, and in 3 cases (1.12%) it resulted in the temporary inability to work. Conclusions: the results of the study indicate the need for further retrospective and prospective studies aimed at analysing the safety of medicine use in pregnant women and assessing the risks of toxic effects on the foetus.

OpenGauss

Although learning-based database optimization techniques have been studied from academia in recent years, they have not been widely deployed in commercial database systems. In this work, we build an autonomous database framework and integrate our proposed learning-based database techniques into an open-source database system openGauss. We propose effective learning-based models to build learned optimizers (including learned query rewrite, learned cost/cardinality estimation, learned join order selection and physical operator selection) and learned database advisors (including self-monitoring, self-diagnosis, self-configuration, and self-optimization). We devise an effective validation model to validate the effectiveness of learned models. We build effective training data management and model management platforms to easily deploy learned models. We have evaluated our techniques on real-world datasets and the experimental results validated the effectiveness of our techniques. We also provide our learnings of deploying learning-based techniques.

The safety of antihypertensive drugs. Retrospective analysis of adverse reactions based on a regional database

Objective. To analyze adverse drug reactions (ADR) occuring in patients taking antihypertensive drugs (AHD).Design and methods. We have analyzed 459 cases of ADR caused by AHD and recorded in the regional database (register) called ARCADe (Adverse Reactions in Crimea, Autonomic Database) during 2011–2018 years.Results. Out of all ADR, 304 cases (3,9 4,4 4,9 % of the total number of cases) were associated with AHD affecting renin-angiotensin-aldosterone system,101 (1,2 1,5 1,8 %) — with calcium channel blockers, and 54 cases (0,6 0,8 1,0 %) — with β-blockers. In the majority of cases, the ADRs were attributed to Enalapril (85 cases) and Amlodipine (76 cases). The analysis of the outcomes showed that serious reactions (life-threatening conditions, hospitalization, and disability) occurred in 72 cases. The remaining 387 ADRs were not considered serious. The majority of reported ADRs were unavoidable reactions of mild severity.

Investigation of the Safety of Radiopaque Compounds Based on Notification Cards on Adverse Reactions Registered in the Republic of Crimea

Objective. At the present stage of medicine development, the use of X-ray contrast agents tends to grow constantly and more than 60 million doses of radiopaque compounds (ROCs) are annually used.The objective of the study was to investigate adverse reactions (ARs) arising from the use of ROCs in patients living in the Republic of Crimea.Material and methods. The objects of the study performed were 69 notification cards on ARs to ROCs, which were registered in the regional database (registry) of spontaneous messages called ARCADe (Adverse Reactions in Crimea, Autonomic Database) in 2009–2018.Results. A larger number of cases of ARs identified in the Republic of Crimea were due to the administration of water-soluble low-osmolar ROCs (iohexol, iopromide, iodixanol) to patients for kidney examination. The main clinical manifestations were immediate hypersensitivity reactions. The number of ARs posing a threat to a patient’s life exceeded 30% of all cases of ARs registered in the Republic of Crimea. Twelve patients (17.4%) required hospitalization or its prolongation to relieve an emerging AR; temporary disability due to ARs to ROCs were observed in 2 cases. The measures to reduce the severity of ARs included drug discontinuation and correction in 65 cases (94.2%). A drug suspected of causing ARs was not discontinued in 3 cases (4.3%); however, additional drugs were needed to correct the ARs.Conclusion. Investigating the safety of ROCs on the basis of analyzing the notification cards on ARs registered in the Republic of Crimea in 2009–2018 could confirm the severity and seriousness of these reactions established by other researchers, which requires an individual approach to choosing a ROC, its dose, as well as monitoring of a patient’s health status both during the administration of agents and soon after the end of diagnostic procedures using ROCs.

CONST: Continuous online NoSQL schema tuning

AbstractSelf‐tuning is a feature of autonomic databases that includes the problem of automatic schema design. Automating the schema design process is critical to provide an optimized schema that increases the performance of an application's workload in NoSQL databases. There has been important work on automated design tuning for NoSQL databases. Existing solutions take an offline approach to the schema design problem and leave several important decisions to database administrators. Although offline approaches recommend good and efficient schemas, their analysis is far too heavy‐weight to be run continuously. This paper develops a novel self‐tuning control loop, called CONST, for online monitoring, analysis, and schema tuning a managed NoSQL database system that automatically modify the current schema design reacting to changes in the application's workload. CONST provides components that fulfill IBM's MAPE‐K loop phases to support self‐tuning. We describe an implementation of the proposed CONST loop on top of the Cassandra wide column store and evaluate its performance experimentally. Our results show the low overhead of CONST and demonstrate its ability to tune a schema design in response to changes in the application's workload.

Automated generation of materialized views in Oracle

Automated generation of a right set of materialized views is a challenging task. It is a highly desirable feature for autonomous databases. The selection of materialized views must be based on cost and verifiable in the actual database environment. This paper describes an automated system that generates, selects, verifies, and maintains materialized views in the Oracle RDBMS; it presents a novel technique, called the extended covering sub-expression algorithm, for the automated generation of materialized views. An extensive set of experiments is described that demonstrates the feasibility and efficiency of this approach. This system has been fully implemented and is going to be deployed on the Oracle Autonomous Database on the Cloud.

Retrospective analysis of adverse drug reaction reporting forms associated with penicillin family antibiotics (pcne-drp 9.0) based on drug-related approach

A widespread use of β-lactam antibiotics such as penicillins in practical medicine, and its authorized use in special categories of patients (e.g. children, pregnant and lactating women, the elderly) requires a critical investigation of their safety as well as the obligatory risk assessment before conducting antibacterial pharmacotherapy.The aim of the work was the conduction of a retrospective study of adverse reactions cases, the identification and analysis of drug-related problems (DRP) associated with the use of penicillin family antibiotics.Materials and methods. The objects of the study were adverse drug reactions (ADR) associated with the use of penicillin family antibiotics in inpatient and outpatient facilities, as well as the cases of self-treatment, which were recorded in the official ADR reports and then inputted in the regional (Republic of Crimea) database of spontaneous reports called ARCADe (Adverse Reactions in Crimea, Autonomic Database). The covered period is 2009–2018. The analysis of DRP was carried out using the 9.0 version of the qualification system DRP PCNE (Pharmaceutical Care Network Europe Foundation).Results. The data analysis of ADR reporting forms has revealed that Amoxicillin clavulanate and Amoxicillin were the most frequent cause of ADR. A high incidence of penicillins ADR in pediatric patients (from 0 to 18 years) – 142 cases – has been found. The clinical manifestations of reactions included drug hypersensitivity reactions (309 cases), dyspeptic disorders (28 cases) and disorders of the central nervous system (5 cases). The incidence of serious ADR was 113 cases (33% of the total number of ADR in the study), which indicates a rather high risk of developing severe ADR for penicillins, resulted in a significant decrease in the quality of patients’ lives.Conclusion. The detection of DRP using the PCNE V9.0 approach is a useful and promising tool important to improve the quality of pharmacotherapy and their adherence to treatment. The highest DRP values which were observed for Amoxicillin clavulanate and Amoxicillin, may indicate a high frequency of irrational use of these drugs.List of abbreviations: DRP – drug related problems; ADR – adverse drug reactions; INN – international non-patented name

Construction of integrated cloud computing platform for Japanese autonomous learning and examination

AbstractRegarding autonomous learning, Japan is no special case which characterizes the advancement of Japan's selection tests and school educational plan—especially since World War II—is a particularly focussed spotlight on names, dates, certainties, and figures as opposed to the verbal correspondence of ideas. However, for a couple of excellent establishments, both secondary schools and colleges strenuously stay away from test addresses that approach understudies to develop a composed reaction or even to peruse a section of a huge length. This disregard of the composed word would be inconceivable in social orders like China, Korea, and Vietnam, with their long custom of composing common administration assessments based on the Confucian classics. In this paper, Fuzzy reinforcement Oracle Database Algorithm has been used for changing the information on the board and organization. However, empowering the autonomous database is basic to our prosperity. the autonomous database learning subscription is an all‐computerized learning arrangement which is perfect for cloud directors, cloud engineers, and business experts, who need to get familiar with an autonomous database. This cloud learning subscription shows how the arrangement of a cloud based autonomous database cloud is appropriate for the remaining tasks at hand and a necessity. This is an extraordinary beginning stage for any individual who needs to find out about the main autonomous database in the market.

Adverse drug reactions of local anesthetics used in dentistry

The objects of the study were 122 notification forms about LA ADR recorded in the regional base (Register) of spontaneous reports called ARCADe (Adverse Reactions in Crimea, Autonomic Database). In most cases, ADR was associated with the use of amide LA Lidocaine - 69 cases (56.55% of the total number of cases for LA ADR), less often, ADR was caused by combinations containing Articaine (34 cases, 27.87%). Rare cases of ADR were reported for Novocaine/Procaine (9 cases, 7.38%), Bupivacaine (8 cases, 6.56%) and Mepivacaine (2 cases, 1.64%). The main clinical manifestations of reactions were hypersensitivity-like reactions (38 cases), cardiac and vascular disorders (29 cases) and central nervous system disorders (19 cases). Lack of effectiveness of LA occurred in 13 cases (10.66%). A study of the outcome of ADR revealed a high incidence of life-threatening conditions associated with LA use - 31 cases (25.4%), which indicates the severity of the event and the need to cancel the suspected drug and prescribe additional medications for correction. The need for hospitalization or prolongation of hospitalization was necessary in 7 cases (5.8%), and temporary disability of patients was revealed in 5 cases (4.1%). Of particular interest are 2 cases (1.6%) of the development of a fatal outcome as a result of the suspected anaphylactic shock (1 case) and disorders of the central nervous system (convulsions, development of respiratory failure). The high frequency and severity of unwanted effects resulted from the use of LA requires healthcare professionals to make rational choices and strictly monitor patient safety.

A Novel Optimized Case-Based Reasoning Approach With K-Means Clustering and Genetic Algorithm for Predicting Multi-Class Workload Characterization in Autonomic Database and Data Warehouse System

Data management systems are essential elements for any organization which is dealing with large volume of data now a days. Due to increase in data volume, and its complexities, it has become more challenging job for workload management system to maintain its performance. So, there is a need of such a system that can autonomically deal with such complexities with less or without human involvement. Performance of these systems can be improved by making the systems well-aware about the workload entering into the system. The workload of a prevalent typical database and data warehouse system can be characterized into three types that is Online Transaction Processing (OLTP), Decision Support Systems (DSS) and Mixed type of workload. Currently, autonomic characterization of workload into a binary class such as OLTP and DSS is being carried out as reported in the literature, however, characterizing the workload into three types that refers to a multi-class classification problem is relatively a more challenging task. In this study, we propose a novel optimized Case-based Reasoning (CBR) approach based on clustering for autonomically characterizing the workload into multi-class types before entering into the system. We implement four phases of CBR along with case-base generation and map it to the elements of autonomic MAPE-K model. In Retrieve phase, k-means clustering is used for enhancing retrieval efficiency and workload types predictions are made in Reuse phase. Genetic Algorithm is used in Revise and Adapt phase of CBR. Few autonomic self_* characteristics are incorporated to make it autonomic. We performed various experiments and results show that the proposed model outperforms in prediction as compared to existing approaches. We performed post-hoc test for the validation of results in comparison with other machine learning classifiers using the Friedman test that show that the proposed model stands out as the best classifier.

Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

Data incompleteness becomes a frequent phenomenon in a large number of contemporary database applications such as web autonomous databases, big data, and crowd-sourced databases. Processing skyline queries over incomplete databases impose a number of challenges that negatively influence processing the skyline queries. Most importantly, the skylines derived from incomplete databases are also incomplete in which some values are missing. Retrieving skylines with missing values is undesirable, particularly, for recommendation and decision-making systems. Furthermore, running skyline queries on a database with incomplete data raises a number of issues influence processing skyline queries such as losing the transitivity property of the skyline technique and cyclic dominance between the tuples. The issue of estimating the missing values of skylines has been discussed and examined in the database literature. Most recently, several studies have suggested exploiting the crowd-sourced databases in order to estimate the missing values by generating plausible values using the crowd. Crowd-sourced databases have proved to be a powerful solution to perform user-given tasks by integrating human intelligence and experience to process the tasks. However, task processing using crowd-sourced incurs additional monetary cost and increases the time latency. Also, it is not always possible to produce a satisfactory result that meets the user’s preferences. This paper proposes an approach for estimating the missing values of the skylines by first exploiting the available data and utilizes the implicit relationships between the attributes in order to impute the missing values of the skylines. This process aims at reducing the number of values to be estimated using the crowd when local estimation is inappropriate. Intensive experiments on both synthetic and real datasets have been accomplished. The experimental results have proven that the proposed approach for estimating the missing values of the skylines over crowd-sourced enabled incomplete databases is scalable and outperforms the other existing approaches.

A Session-based Approach to Autonomous Database Tuning

A Session-based Approach to Autonomous Database Tuning

Feedback control loop design for workload change detection in self-tuning NoSQL wide column stores

Database management systems are the main part of information systems that the size and complexity of these systems are increased in recent years. Due to the growing complexity of DBMSs, database administrators (DBAs) face increasingly more problems and challenges, and so managing these systems are difficult and laborious. More over the main part of the total cost of ownership includes the cost of expert database administrator who can manage these large and complicated systems. Autonomic database, by providing self-management functionality, leads to a reduction in the total cost of ownership for the database system. Self-management decisions such as automated schema database tuning are dependent on the database workload. Therefore, one of the important issues in realizing the database automated tuning is workload monitoring and analysis for changes detection and schema re-tuning with this changes. In this paper, a feedback control loop is designed for continuous monitoring and light-weight workload analysis in NoSQL wide column stores. This loop describes a design pattern for the self-tuning feature and it is used to detect workload changes that are necessary for the automated schema database re-tuning. Our concept is based on workload model construction using reconfigurable colored petri-net model. The results of the experiments show the effectiveness of the proposed approach in discovering significant workload changes.

APPLICATION OF DRUG-RELATED PROBLEMS APPROACH TO ANALYSIS OF NON-STEROIDAL ANTI-INFLAMMATORY DRUGS’ SAFETY

A Drug-Related Problem is an event or circumstance involving drug therapy that actually or potentially interferes with desired health outcomes.The aim of the study was the analysis of the adverse drug reactions (ADR) associated with prescription of the non-steroidal anti-inflammatory drugs (NSAIDs) using the DRP PCNE V5.01 qualification system.Materials and methods. The objects of the study were 415 notification forms about adverse drug reactions of NSAIDs recorded in the regional database of spontaneous reports and called ARCADe (Adverse Reactions in Crimea, Autonomic Database) for the period from 1 January 2009 to 31 December of 2018. The study and analysis of the problems associated with drugs were carried out using the qualification system DRP PCNE V5.01 (Pharmaceutical Care Network Europe) 2006 in the modification of Prof. Zimenkovsky.Results. Among other representatives of the NSAID group, Ibuprofen and Diclofenac became the “leaders” in the incidence of ADR. The frequency of ADR cases for Ibuprofen was 142 reports (34.22% of the total number of ADR for NSAIDs), and for Diclofenac it was 90 cases (21.69%). The calculation of DRP values for each of the presented cases made it possible to determine that in 81 (19.51%) and 91 (21.9%) cases, the DRP value was 6 and 7, respectively. DRP values in the range of 8–10 were found in 92 reports. The highest DRPs value was observed after the administration of Parecoxib (13 problems but only one case was found in the database), the DRPs value of Dexketoprofen was 12.5 (95% CI: 7–17) and the DRPs value of Diclofenac combinations was 10 DRPs; 95% CI: 5–17 DRP). The minimum DRPs values were associated with Naproxen, Rofecoxib, and Etoricoxib prescriptions.Conclusion. Using the DRP system in the analysis of NSAIDs, ADRs allow to identify the medicines which have a high risk of causing safety problems, such as Parecoxib, Dexketoprofen and Diclofenac combinations. The prescription of these drugs should be carried out with special cautions and control to the indications and contraindications, the dose and duration of treatment, as well as to a possible interaction of them with concomitant drugs.

Construction of a parametric model of competitive access in relational databases by using a random forest method

We have considered the task on modeling a request execution time in autonomous relational databases with competitive queries. The shortcomings of existing approaches have been specified, which ignore the cost of the share of successive operations in the cooperative access to data in a memory hierarchy. We have examined the issue of the application of relative cost for the implementation of components in the operations of a plan of the query, instead of calculating the predicted time of computation. A technique has been proposed for the formal construction of precedents for a training sample, as well as the approach to building a regression model. The developed modification of the machine learning method random forest is used for calculating the request execution time based on their texts and temporary marks of the start, duration of execution. The constructed parametrical model of competitive access to data is required for obtaining accurate estimates of request execution time when using parallel computations. Models with such characteristics are needed to solve the problems on automated management of a physical data scheme, for building self-identifiable DBMS. The key differences from existing approaches are the application of a request execution time as the target value, accounting the values of predicates and mutual influence of requests that are executed in parallel. To confirm the results obtained, a simulation model has been used based on the widely known test TPC-C. The used function of loss, taking into consideration the regression nature of the model, was the ratio of the sum of modules of difference between the actual and obtained time to the actual time. The check itself was carried out based on a reference sample, generated for the increasing length of training at postponed data. In the course of this study we have proved a possibility to apply the machine learning method random forest for processing statistical data on the execution of SQL queries. The result obtained is promising for such an approach and makes it possible to derive the parametric models of competitive request processing.

INVESTIGATION OF MEDICALLY INDUCED SKIN REACTIONS BASED ON THE ANALYSIS OF REPORTS OF ADVERSE DRUG REACTIONS IN THE REPUBLIC OF CRIMEA (FROM 2009 TO 2016)

Drug hypersensitivity reactions are among the most important problems that arise when using drugs. The occurrence of such reactions in the population is at least 7% and tends to a constant increase. The most frequent manifestations of drug hypersensitivity reactions are medically induced skin lesions.The aimof this research was to study and analyze the cases of development of skin drug reactions on the basis of the reports on the adverse reactions (ADRs) of the drugs, registered in the Republic of Crimea in the period from 2009 to 2016.Materials and methods.The objects of the research were report cards about the adverse reactions, registered in the regional base (registry) of spontaneous messages called ARCADe (Adverse Reactions in Crimea, Autonomic Database) for the period from 2009 to 2016. During the analysis of the report cards, 2,698 cases of the development of skin drug reactions arising in response to the use of drugs in patients were selected. The study of the frequency of occurrence of skin drug reactions in the application of various groups of drugs was carried out taking into account the codes of the Anatomical Therapeutic Chemical (ATC) Сlassification System of drugs of the World Health Organization (WHO).Results.Of the study showed that the development of skin drug reactions was most often associated with the use of antimicrobial agents for internal use, nonsteroidal anti-inflammatory drugs (NSAIDs), drugs for the treatment of diseases of the gastrointestinal tract and agents that affect the nervous system. Among the clinical manifestations of skin drug reactions, generalized and localized rashes prevailed, and itching and hyperemia of the skin were much less common in patients. The analysis of age categories showed that the most frequently medically induced reactions occurred in children from birth to 3 years, as well as in the age group of patients from 46 to 60 years. The risk factors identified in the course of the analysis, were female gender, early childhood and old age, as well as the presence of aggravated drug allergy history.Conclusion.Drug hypersensitivity reactions create certain difficulties in clinical practice related to the diagnosis, treatment and prophylaxis, and may also cause danger to health or life of patients. In this connection, the study of such adverse reactions is the most important task of practical health care and requires direct participation of doctors of all specialties.