DEVELOPMENT OF CODI (CO-DRUG INTERACTION) SOFTWARE AS DRUGS PRESCRIPTION ANALYSIS

Objective: This study intends to design software algorithms, which is called Co-Drug Interaction (CODI), that able to analyse drug interactions in prescription and recommendations for further correction by replacing active substances based on the E-book Drug Interaction Facts and provide drug information features. Methods: The research used data collection and conversed into programming languages. Java language programme choosed to build the entire application as its considerable free of charge and recognizable interface to use. The reference book is also used to help in prescribing and evaluating the reliability and efficiency of the software. Result: The evaluations were performed by analyzing 30 groups of medicine based on 2 diseases, which are hypertension and diabetes mellitus. Conclusion: The algorithm design and evaluation are in accordance with the planned output.

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IDENTIFIKASI DRUG RELATED PROBLEMS PADA PASIEN AUTIS DI RUMAH SAKIT X KOTA YOGYAKARTA

Jurnal Kefarmasian Akfarindo ◽

10.37089/jofar.v0i0.52 ◽

2019 ◽

pp. 30-40

Author(s):

Ruri Renggani Sandra ◽

Della Midi Wardhani ◽

Woro Supadmi

Keyword(s):

Autism Spectrum Disorders ◽

Drug Interaction ◽

Herb–Drug Interactions: Worlds Intersect with the Patient at the Center

Medicines ◽

10.3390/medicines8080044 ◽

2021 ◽

Vol 8 (8) ◽

pp. 44

Author(s):

Mary Beth Babos ◽

Michelle Heinan ◽

Linda Redmond ◽

Fareeha Moiz ◽

Joao Victor Souza-Peres ◽

...

Keyword(s):

Drug Interaction ◽

Case Report ◽

Drug Interactions ◽

Clinical Studies ◽

Drug Information ◽

Case Reports ◽

Full Information ◽

Information Need ◽

Herbal Products ◽

Reduce Risk

This review examines three bodies of literature related to herb–drug interactions: case reports, clinical studies, evaluations found in six drug interaction checking resources. The aim of the study is to examine the congruity of resources and to assess the degree to which case reports signal for further study. A qualitative review of case reports seeks to determine needs and perspectives of case report authors. Methods: Systematic search of Medline identified clinical studies and case reports of interacting herb–drug combinations. Interacting herb–drug pairs were searched in six drug interaction resources. Case reports were analyzed qualitatively for completeness and to identify underlying themes. Results: Ninety-nine case-report documents detailed 107 cases. Sixty-five clinical studies evaluated 93 mechanisms of interaction relevant to herbs reported in case studies, involving 30 different herbal products; 52.7% of these investigations offered evidence supporting reported reactions. Cohen’s kappa found no agreement between any interaction checker and case report corpus. Case reports often lacked full information. Need for further information, attitudes about herbs and herb use, and strategies to reduce risk from interaction were three primary themes in the case report corpus. Conclusions: Reliable herb–drug information is needed, including open and respectful discussion with patients.

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Research on General Programming Environment Technology Based on Web

MATEC Web of Conferences ◽

10.1051/matecconf/201823201040 ◽

2018 ◽

Vol 232 ◽

pp. 01040

Author(s):

Liu Yu

Keyword(s):

Programming Languages ◽

Hot Spot ◽

Local Environment ◽

Programming Environment ◽

Online Experiments ◽

C Language ◽

Java Language ◽

Online Platforms ◽

Education Industry ◽

Programming Solution

As the MOOC develops, many users have begun to gradually like and get used to programming learning on the MOOC platform, so virtual online experiments have become a hot spot in the online programming education industry, which is also known as online IDE or online programming environment. Compared with the traditional programming environment, the online programming environment does not require a complicated establishment of local environment, making it easy to be used. At the same time, the online programming environment can also be integrated into the MOOC for learning, and can also be combined with OJ for evaluation. However, the existing online programming environment usually only supports few programming languages, such as C language and Java language. Even some online platforms only have the online compiling function with one language. Based on the above phenomena, this paper will propose a general online programming solution. And based on the idea, a platform that supports multi-language online compiling function is built through simple code writing and the construction of server environment.

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Hybrid Java: The creation of a Hybrid Programming Environment

Irish Journal of Technology Enhanced Learning ◽

10.22554/ijtel.v5i1.67 ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Mark Noone ◽

Aidan Mooney ◽

Keith Nolan

Keyword(s):

Programming Languages ◽

Programming Language ◽

Visual Programming ◽

First Year ◽

Programming Environment ◽

Programming Environments ◽

Hybrid Programming ◽

Java Language ◽

The Creation ◽

Visual Programming Language

This article details the creation of a hybrid computer programming environment combining the power of the text-based Java language with the visual features of the Snap! language. It has been well documented that there exists a gap in the education of computing students in their mid-to-late teenage years, where perhaps visual programming languages are no longer suitable and textual programming languages may involve too steep of a learning curve. There is an increasing need for programming environments that combine the benefits of both languages into one. Snap! is a visual programming language which employs “blocks” to allow users to build programs, similar to the functionality offered by Scratch. One added benefit of Snap! is that it offers the ability to create one’s own blocks and extend the functionality of those blocks to create more complex and powerful programs. This will be utilised to create the Hybrid Java environment. The development of this tool will be detailed in the article, along with the motivation and use cases for it. Initial testing conducted will be discussed including one phase that gathered feedback from a pool of 174 first year Computer Science students. These participants were given instructions to work with the hybrid programming language and evaluate their experience of using it. The analysis of the findings along with future improvements to the language will also be presented.

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BIM as support for design process with fire safety regulations

International Journal of Occupational and Environmental Safety ◽

10.24840/2184-0954_001.001_0004 ◽

2017 ◽

Vol 1 (1) ◽

pp. 39-48

Author(s):

L. Sanches ◽

J. G. F. Abdalla ◽

M. A. S. Hippert

Keyword(s):

Design Process ◽

Fire Safety ◽

Parametric Design ◽

Algorithm Design ◽

Digital Tool ◽

Safety Standards ◽

Safety Regulations ◽

Design Software ◽

Legal Constraints

Based on a case study this research aims to answer if it is possible to, automatically, materialize fire safety standards in 3D forms using algorithmic-design software and also, to analyse means, methods and requirements for its creation. First, with a short literature review it was possible to approach the concepts of BIM and parametric design as well as its use throughout design process, this review was extended to fire safety standards seeking to understand how it defines architectural details in Brazilian state of Minas Gerais. Finally, a digital tool was developed using software Windows Excel and Rhinoceros/Grasshopper, and a set simulations were made to validate its use. The study showed it is possible to achieve results similar to the ones obtained by conventional methods; therefore, the use of legal constraints as parameters on an algorithm design software may bring more flexibility to design process as it can fasten the design choices validation.

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DRUG-DRUG INTERACTION;

The Professional Medical Journal ◽

10.29309/tpmj/2017.24.03.1551 ◽

2017 ◽

Vol 24 (03) ◽

pp. 357-365

Author(s):

Hina Hasnain ◽

Huma Ali ◽

Farya Zafar ◽

Ali Akbar Sial ◽

Kamran Hameed ◽

...

Keyword(s):

Patient Outcome ◽

Adverse Event ◽

Drug Interaction ◽

Drug Interactions ◽

Multidisciplinary Approach ◽

Drug Information ◽

Drug Effects ◽

Information Provision ◽

Drug Drug Interaction ◽

Drug Order

Drug-drug interaction (DDI) is a specific type of adverse event, which developsdue to multiple regimen therapy, and that may lead to significant hospitalization and death.Clinical and economic impact of drug interactions are increasingly accredited as a chiefconcern in critical care. Potentiating effects of DDIs in intensive care units are far more criticaldue to complex medications regimen, high risk severely ill population and associated metabolicand physiological disturbances which can impede drug effects. Pharmacist contribution isclassified as clarification of drug order, appropriate drug information provision, and advice forsubstitute treatment. A multidisciplinary approach is very necessary in developing a pharmacotherapeuticregimen designed to optimize patient outcome and minimize any potential dugdrug interactions. This review encompasses the prevalence, categorization, significance interm of patient safety and prescription efficacy, clinical and economic burdens, national andinternational data comparisons related to drug-drug interactions.

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Evaluation of resources for analyzing drug interactions

Journal of the Medical Library Association JMLA ◽

10.5195/jmla.2016.142 ◽

2017 ◽

Vol 104 (4) ◽

Author(s):

Risha I. Patel, PharmD ◽

Robert D. Beckett, PharmD, BCPS

Keyword(s):

Clinical Pharmacology ◽

Drug Interaction ◽

Drug Interactions ◽

Dietary Supplement ◽

Drug Information ◽

Cross Sectional Study ◽

Information Resources ◽

Ease Of Use ◽

Sectional Study ◽

Cross Sectional

Objective: The research sought to evaluate seven drug information resources, specifically designed for analyzing drug interactions for scope, completeness, and ease of use, and determine the consistency of content among the seven resources.Methods: A cross-sectional study was conducted where 100 drug-drug and drug-dietary supplement interactions were analyzed using 7 drug information resources: Lexicomp Interactions module, Micromedex Drug Interactions, Clinical Pharmacology Drug Interaction Report, Facts & Comparisons eAnswers, Stockley’s Drug Interactions (10th edition), Drug Interactions Analysis and Management (2014), and Drug Interaction Facts (2015). The interaction sample was developed based on published resources and peer input. Two independent reviewers gathered data for each interaction from each of the 7 resources using a common form.Results: Eighty-two drug-drug and 18 drug-dietary supplement interactions were analyzed. Scope scores were higher for Lexicomp Interactions (97.0%), Clinical Pharmacology Drug Interaction Report (97.0%), and Micromedex Drug Interactions (93.0%) compared to all other resources (p<0.05 for each comparison). Overall completeness scores were higher for Micromedex Drug Interactions (median 5, interquartile range [IQR] 4 to 5) compared to all other resources (p<0.01 for each comparison) and were higher for Lexicomp Interactions (median 4, IQR 4 to 5), Facts & Comparisons eAnswers (median 4, IQR 4 to 5), and Drug Interaction Facts (4, IQR 4 to 5) compared to all other resources, except Micromedex (p<0.05 for each comparison). Ease of use, in terms of time to locate information and time to gather information, was similar among resources. Consistency score was higher for Micromedex (69.9%) compared to all other resources (p<0.05 for each comparison).Conclusions: Clinical Pharmacology Drug Interaction Report, Lexicomp Interactions, and Micromedex Drug Interactions scored highest in scope. Micromedex Drug Interactions and Lexicomp Interactions scored highest in completeness. Consistency scores were overall low, but Micromedex Drug Interactions was the highest.

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A Comparison of Tertiary Drug Resources’ Consistency Regarding Drug-Drug Interactions of Adjunctive Analgesics

Journal of Pharmacy Technology ◽

10.1177/8755122520951331 ◽

2020 ◽

pp. 875512252095133

Author(s):

Andrew Lang ◽

Michael A. Veronin ◽

Justin P. Reinert

Keyword(s):

Health Care ◽

Drug Interaction ◽

Drug Interactions ◽

Patient Care ◽

Health Care Providers ◽

Drug Information ◽

Interaction Analysis ◽

Information Resources ◽

Care Providers ◽

Drug Drug Interaction

Background: Health care providers routinely rely on tertiary drug information resources to affirm knowledge or proactively verify the safety and efficacy of medications. Though all patient care areas are affected, the reliability of these resources is perhaps nowhere as poignant as it is in high-acuity settings, including the emergency department and the intensive care unit. As providers seek to identify adjunctive analgesics for acute pain in these areas, they must be able to rely on the integrity to whichever resource their institution has granted access. Objective: To determine the congruency of drug-drug interaction information found on 3 tertiary drug resources. Methods: A drug-drug interaction analysis was conducted on Micromedex, Lexicomp, and Medscape. Adjunctive analgesics included dexmedetomidine and ketamine, which were compared with the intravenous opioid products morphine, fentanyl, and hydromorphone. Results: Significant discrepancies were appreciated with regard to the severity of drug-drug interactions. In addition, the heterogeneity in which reaction severity and likelihood are described by each respective resource makes direct comparisons difficult. Interaction warnings for dexmedetomidine and fentanyl included a “major interaction” from Micromedex, whereas Lexicomp did not identify a risk and Medscape only recommended increased monitoring on the grounds of respiratory and central nervous system depression. Conclusions: Health care providers must remain vigilant when reviewing tertiary drug information resources. Pharmacists possess the training and skills necessary to assist interdisciplinary medical teams in providing optimal patient care through evaluating and applying the information gleaned from these resources.

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Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data

Therapeutic Advances in Drug Safety ◽

10.1177/20420986211041277 ◽

2021 ◽

Vol 12 ◽

pp. 204209862110412

Author(s):

Levin Thomas ◽

Sumit Raosaheb Birangal ◽

Rajdeep Ray ◽

Sonal Sekhar Miraj ◽

Murali Munisamy ◽

...

Keyword(s):

Drug Interaction ◽

Drug Interactions ◽

Molecular Modelling ◽

Molecular Level ◽

Drug Information ◽

Potential Drug ◽

African Countries ◽

Antitubercular Drugs ◽

Tuberculosis Patients ◽

Drug Drug Interaction

Introduction: Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug–drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs. Methods: We assessed the potential drug–drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug–drug interactions found from the Micromedex drug interaction checker database at a molecular level. The integrated knowledge derived from Micromedex and computational data was collated and curated for predicting potential drug–drug interactions between repurposed COVID-19 and antitubercular drugs. Results: A total of 91 potential drug–drug interactions along with their severity and level of documentation were identified from Micromedex between repurposed COVID-19 drugs and antitubercular drugs. We identified 47 pharmacodynamic, 42 pharmacokinetic and 2 unknown DDIs. The majority of our molecular modelling results were in line with drug–drug interaction data obtained from the drug information software. QT prolongation was identified as the most common type of pharmacodynamic drug–drug interaction, whereas drug–drug interactions associated with cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) inhibition and induction were identified as the frequent pharmacokinetic drug–drug interactions. The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs. Conclusion: Predicting these potential drug–drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug–drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug–drug interaction studies. Plain Language Summary Introduction: Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients predicted to be infected with COVID-19 during this period, there is a higher risk for the occurrence of medication interactions between the medicines used for COVID-19 and tuberculosis. Hence, identifying and managing these interactions is vital to ensure the safety of patients undergoing COVID-19 and tuberculosis treatment simultaneously. Methods: We studied the major medication interactions that could likely happen between the various medicines that are currently given for COVID-19 and tuberculosis treatment using the medication interaction checker of a drug information software (Micromedex®). In addition, thorough molecular modelling was done to confirm and understand the interactions found from the medication interaction checker database using specific docking software. Molecular docking is a method that predicts the preferred orientation of one medicine molecule to a second molecule, when bound to each other to form a stable complex. Knowledge of the preferred orientation may be used to determine the strength of association or binding affinity between two medicines using scoring functions to determine the extent of the interactions between medicines. The combined knowledge from Micromedex and molecular modelling data was used to properly predict the potential medicine interactions between currently used COVID-19 and antitubercular medicines. Results: We found a total of 91 medication interactions from Micromedex. Majority of our molecular modelling findings matched with the interaction information obtained from the drug information software. QT prolongation, an abnormal heartbeat, was identified as one of the most common interactions. Our findings suggest that antitubercular medicines, mainly rifampin and second-line agents, suggest high alert and scrutiny while prescribing with the repurposed COVID-19 medicines. Conclusion: Our current study highlights the need for further well-designed studies confirming the current information for recommending safe prescribing in patients with both infections.

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Identifying Common Methods Used by Drug Interaction Experts for Finding Evidence About Potential Drug-Drug Interactions: Web-Based Survey (Preprint)

10.2196/preprints.11182 ◽

2018 ◽

Author(s):

Amy J Grizzle ◽

John Horn ◽

Carol Collins ◽

Jodi Schneider ◽

Daniel C Malone ◽

...

Keyword(s):

Drug Interaction ◽

Health Outcomes ◽

Drug Interactions ◽

Knowledge Base ◽

Drug Information ◽

Search Strategies ◽

Current Evidence ◽

Potential Drug ◽

Convenience Sample ◽

Web Based

BACKGROUND Preventing drug interactions is an important goal to maximize patient benefit from medications. Summarizing potential drug-drug interactions (PDDIs) for clinical decision support is challenging, and there is no single repository for PDDI evidence. Additionally, inconsistencies across compendia and other sources have been well documented. Standard search strategies for complete and current evidence about PDDIs have not heretofore been developed or validated. OBJECTIVE This study aimed to identify common methods for conducting PDDI literature searches used by experts who routinely evaluate such evidence. METHODS We invited a convenience sample of 70 drug information experts, including compendia editors, knowledge-base vendors, and clinicians, via emails to complete a survey on identifying PDDI evidence. We created a Web-based survey that included questions regarding the (1) development and conduct of searches; (2) resources used, for example, databases, compendia, search engines, etc; (3) types of keywords used to search for the specific PDDI information; (4) study types included and excluded in searches; and (5) search terms used. Search strategy questions focused on 6 topics of the PDDI information—(1) that a PDDI exists; (2) seriousness; (3) clinical consequences; (4) management options; (5) mechanism; and (6) health outcomes. RESULTS Twenty participants (response rate, 20/70, 29%) completed the survey. The majority (17/20, 85%) were drug information specialists, drug interaction researchers, compendia editors, or clinical pharmacists, with 60% (12/20) having >10 years’ experience. Over half (11/20, 55%) worked for clinical solutions vendors or knowledge-base vendors. Most participants developed (18/20, 90%) and conducted (19/20, 95%) search strategies without librarian assistance. PubMed (20/20, 100%) and Google Scholar (11/20, 55%) were most commonly searched for papers, followed by Google Web Search (7/20, 35%) and EMBASE (3/20, 15%). No respondents reported using Scopus. A variety of subscription and open-access databases were used, most commonly Lexicomp (9/20, 45%), Micromedex (8/20, 40%), Drugs@FDA (17/20, 85%), and DailyMed (13/20, 65%). Facts and Comparisons was the most commonly used compendia (8/20, 40%). Across the 6 attributes of interest, generic drug name was the most common keyword used. Respondents reported using more types of keywords when searching to identify the existence of PDDIs and determine their mechanism than when searching for the other 4 attributes (seriousness, consequences, management, and health outcomes). Regarding the types of evidence useful for evaluating a PDDI, clinical trials, case reports, and systematic reviews were considered relevant, while animal and in vitro data studies were not. CONCLUSIONS This study suggests that drug interaction experts use various keyword strategies and various database and Web resources depending on the PDDI evidence they are seeking. Greater automation and standardization across search strategies could improve one’s ability to identify PDDI evidence. Hence, future research focused on enhancing the existing search tools and designing recommended standards is needed.

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