Drug Names Research Articles

МАРКЕТИНГОВЫЙ АНАЛИЗ АССОРТИМЕНТА ОСНОВНЫХ МОНОПРЕПАРАТОВ, ПРИМЕНЯЕМЫХ ДЛЯ ТЕРАПИИ РАССТРОЙСТВ СНА

In recent years, many studies have noted that the number of occurrence of various sleep disorders is increasing among the population, while such problems as self-medication, untimely access to a doctor, the presence of concomitant diseases, the development of acute forms of disorders into chronic ones are highlighted, all this affects the quality and life expectancy of the population and makes it relevant to study pharmacotherapy of drugs for the treatment of these disorders in the field of pharmaceutical care [1-6; 11]. The purpose of the study was to establish a list and conduct a marketing analysis of the assortment of the main groups of monopreparations used for the treatment of sleep disorders presented on the domestic pharmaceutical market for their subsequent use in more extensive comprehensive marketing research in the context of sleep disorder therapy. The materials for the study were data from the State Register of Medicines and regulatory documents reflecting the attitude of objects to accounting and control of their sale on the market. The following methods were used: comparisons, systematization, grouping, statistics, as well as structural and assortment analyses. The article presents the results of a study of the Russian market of monopreparations of this orientation. The systematization of the main monopreparations was carried out, as a result, 7 groups were identified, which include 25 international nonproprietary names of medicines represented by 78 trade names, the proportion of manufactured drugs within each group and relative to the total number of trade names were calculated. The next step was to analyze the conditions for the release of drugs, their inclusion in lists reflecting accounting and control during implementation in accordance with regulatory documentation. In conclusion, it is noted that the obtained ranking data and the corresponding calculations will serve as a basis for further research in the field of the pharmaceutical market of drugs used for sleep disorders.

Adverse events associated with parenteral nutrition support therapy: A pharmacovigilance study.

Parenteral nutrition (PN) plays a crucial role in nutrition support therapy, yet data on related adverse events (AEs) in practical settings are scarce. To address this, we analyzed AE signals associated with PN treatment from the United States Food and Drug Administration Adverse Event Reporting System (FAERS) database. We extracted data from the FAERS database, covering the period from the first quarter (Q1) of 2004 to Q1 of 2024. Drug names and AEs were standardized. We then conducted disproportionality analyses using four different algorithms to evaluate the association between PN and its associated AEs. We collected a total of 48,890,925 reports from the FAERS database, of which 1642 involved PN-related AEs. After categorization, we identified 21 system organ classes (SOCs), and hepatobiliary disorders were the only significant SOC across all four algorithms. At the preferred term (PT) level, we identified 99 PTs that showed significant disproportionality in all four algorithms. Fat overload syndrome, fatty acid deficiency, parenteral nutrition-associated liver disease (PNALD), Malassezia infection, and Pantoea agglomerans infection were the most prominent PTs. In addition, several potential new AE signals included nervous, cardiac, immune, psychiatric, blood, renal, urinary, and eye disorders. Our study identified several common and rare PN-related AEs reported in the FAERS database. Patients and healthcare providers should remain vigilant about these AEs. Understanding the risks of PN therapy and establishing practical procedures can help reduce AEs.

Polypharmacy in Older Patients with Multimorbidity: The Agreement Between Patient and General Practitioner-Reported Drugs Observed in a Pilot cRCT.

Polypharmacy (≥5 drugs) increases the risk of discrepancies between patient- and general practitioner (GP)-reported drugs, leading to adverse outcomes. This explorative analysis assesses the agreement between patient- and GP-reported drugs under the influence of a paper-based patient portfolio in a pilot cluster randomized controlled trial (cRCT). Complete data were available for 68 patients aged 65 or older (26 were female), with multimorbidity, polypharmacy, and at least one hospitalization in the past year. Agreement was assessed for drug name and strength level. Differences between the intervention and control group (IG/CG) and comparisons between two time points (six-month interval) stratified according to gender were analyzed using Wilcoxon and Mann-Whitney U tests (α = 5%). To evaluate the reasons for discrepancies, the agreement of active pharmaceutical ingredients (APIs) and anatomical therapeutic chemical (ATC) groups was analyzed. At baseline, the agreement was 72.1% for the IG and 73.9% for the CG. Inclusion of the reported drug strength reduced the agreement in both groups (IG 66.7%, CG 60.0%). Agreement for the IG decreased statistically significantly after six months (-5.4%). ATC groups B, C, and H had the highest agreement, while N, R, and Z had the lowest. Large discrepancies in the drugs reported, due to the APIs and the corresponding ATC group, were observed.

Antihypertensive therapy in patients with arterial hypertension and concomitant diseases in real clinical practice (according to the National Registry of Arterial Hypertension, 2019-2022)

Arterial hypertension (AH) remains the leading risk factor associated with cardiovascular diseases (CVDs), cerebrovascular disease and chronic kidney disease. About 70% of patients with AH who are on monotherapy cannot achieve blood pressure (BP) targets, and therefore all quidelines for the management of AH have recently recommended prescribing combination therapy (PCT). In real clinical practice (RCP), there remains significant uncertainty in the effectiveness and rationality of therapy, despite the wide availability of antihypertensive drugs (AHD) and the presence of recommendations for a stepwise approach to prescribing combinations of specific groups of AHD in different clinical situations. Analyze the real ongoing antihypertensive therapy, including the PCT; international nonproprietary names of drugs and their dosages in RCP; compliance of therapy with clinical recommendations; changing trends in the PCT. An analysis was carried out of the data from the register of AH, the compliance of treatment in different clinical groups of patients and the achievement of BP and low-density lipoprotein cholesterol targets in the sample of 2019-2022 (n=5012). The prescription of AHD and achievement of targets values were assessed in accordance with current clinical guidelines for the management of AH and hypercholesterolemia. Data from 2010 (n=7782) and 2020 (n=3061) were analyzed to assess the dynamics of prescription of monotherapy and PCT. The greatest increase in the number of AHD was observed in patients with hypertension in combination with coronary heart disease, heart failure, and atrial fibrillation. In a small group of patients with hypertension without other CVDs, the recommended combinations of AHD were not prescribed; preference was given to angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and β-adrenoblocker (β-AB). PCT mainly differed from the recommended combinations by the wider use of drugs from the β-AB group. The PCT of recommended drugs was highest in patients with hypertension and coronary artery disease - more than 90%, hypertension and heart failure in 56.2%, hypertension and atrial fibrillation - 33.3%, hypertension and chronic kidney desease - 19.6%. Achievement of BP and low-density lipoprotein cholesterol targets was insufficient in all analyzed groups. Among the international nonproprietary names of drugs, the most frequently prescribed are the following: bisoprolol, metoprolol, lisinopril, perindopril, losartan, spironolactone, amlodipine, torasemide, indapamide, hypochlorothiazide, moxonidine. The prescribed daily dosages were closer to the initial recommended ones. By 2020, the prescription of PCT with β-AB and a more uniform prescription of various combinations will come to the fore, while PCT in 2010 is characterized by the presence of one or two leaders combinations. The described features of prescribing AHD partially reproduce clinical recommendations for the management of AH. Differences in therapy provided in RCP may be associated with an attempt to intensify the treatment of hypertension in patients with other concomitant CVDs. At the same time, analysis of combinations and dosages of prescribed drugs suggests the presence of wide opportunities for further escalation of therapy. The presented data can provide insight into current patterns of antihypertensive therapy prescription in patients in RCP and lay the foundation for optimizing therapy in different categories hypertensive patients.

Integration of FAERS, DrugBank and SIDER Data for Machine Learning-based Detection of Adverse Drug Reactions

AbstractTraditionally, disproportionality analysis (DPA) methods are employed for signal detection in pharmacovigilance, but these methods utilize only a limited portion of the data available from spontaneous event reports (SERs). This research aims to enhance signal detection by applying machine learning (ML) methods that can leverage additional data. We create a dataset by integrating SER data from the FDA Adverse Event Reporting System (FAERS) with biological and chemical data from DrugBank, and information on known adverse drug reactions (ADRs) from Side Effect Resource (SIDER). The known ADRs from SIDER are used to label the dataset for ML training. Using the AutoML library TPOT, ML models are trained on this dataset. Our findings indicate that ML models, even when trained with the same features as DPA methods, achieve higher recall and precision. Moreover, incorporating additional features related to drugs and events significantly boosts the performance of ML models. Analysis using the explainable AI (XAI) technique SHAP reveals that the drug name, event name, and fifth-level ATC code are the most influential features for model predictions. These ML models offer a promising alternative or supplement to conventional DPA methods for signal detection in pharmacovigilance.

Patient-friendliness of ChatGPT responses: NSCLC targeted therapy.

231 Background: Non-small cell lung cancer (NSCLC) targeted therapies are complex, often requiring extensive patient education beyond what can be conveyed in a single provider visit. Given the average US reading level is at the 8th grade, and many patients seek additional information online, it is vital to evaluate the readability of online resources. This study aims to determine the patient friendliness of information provided by AI chatbots like ChatGPT in explaining NSCLC targeted therapies compared to other commonly accessed sources. Methods: This analysis included targeted therapies approved by the FDA for EGFR-mutated NSCLC: Afatinib, Erlotinib, Osimertinib, Dacomitinib, and Gefitinib. Information sources included ChatGPT 4, ChatGPT 3.5, the Patient Information section of the FDA label, and the Google featured snippet. Each version of ChatGPT was queried 10 times for each individual therapy – “My doctor is suggesting starting therapy with (Drug Name). What can I expect with this medication?”. All responses, labels, and snippets were examined by Microsoft Word for word count (WC) and Flesch Reading Ease Score (FRES), which considers average sentence length and number of syllables per word to assess readability. Data analysis was performed using ANOVA in SAS. Results: Across all therapies, Mean FRES for ChatGPT 4 was 31.21, ChatGPT 3.5 26.69, FDA labels 50.78, and Google snippets 33.1. Mean WC for ChatGPT 4 was 312.54, ChatGPT 3.5 355.78, FDA labels 1220, and Google snippets 42. Significant differences in FRES were found among sources for Afatinib (p-value <0.0001), Erlotinib (p-value 0.0206), Osimertinib (p-value <0.0001), Dacomitinib (p-value 0.0125), and Gefitinib (p-value <0.0001). Significant differences in WC were also found among sources for Afatinib (p-value <0.0001), Erlotinib (p-value <0.0001), Osimertinib (p-value <0.0001), and Gefitinib (p-value 0.0045). No significant difference in WC was found for Dacomitinib (p-value 0.2807). Conclusions: While the FDA label provided the most readable information, none of the sources aligned with the average 8th-grade reading level in the US, indicating a gap in accessible patient education for NSCLC targeted therapies. Notably, readability varies significantly between ChatGPT versions, affecting accessibility for users of the free version, ChatGPT 3.5. Although ChatGPT responses are more succinct compared to the verbose FDA labels, their higher education-level readability presents a barrier to comprehension. This study highlights the need for further research into optimizing AI-generated patient education materials to be both accurate and comprehensible at appropriate reading levels, thereby improving health communication strategies.

Application of bone perforation in the surgery of medication-related osteonecrosis of the jaw in stage Ⅱ.

This study aimed to explore the effect of surgery combined with bone perforation for treating stage Ⅱ medication-related osteonecrosis of the jaw (MRONJ). A total of 21 patients with stage Ⅱ mandibular MRONJ who underwent surgical treatment from June 2020 to June 2023 were included in this study. Retrospective analysis was conducted on their clinical data, including gender, age, primary disease, drug name and administration method, pre-surgery drug cessation, and prognosis. The cohort comprised 14 males and 7 females, with an average age at onset of 68.33±10.74 years. According to the guidelines of the American Association of Oral and Maxillofacial Surgeons, the included patients had stage Ⅱ mandibular MRONJ. The treatment approach consisted of partial mandibulectomy combined with bone perforation techniques, ensuring tension-free suturing of soft tissues. Follow-up was performed regularly, and the curative effect was evaluated. The SF-12 health survey was used to assess the quality of life for all patients before and after surgery. A total of 21 patients were followed up for 8-38 months after surgery, and the mucosal healing of 17 patients was good (80.95%). The postoperative quality of life score (83.62±5.90) was significantly higher than that before operation (63.67±4.70, P<0.05). Surgery combined with bone perforation te-chnique is an effective treatment method with high success rate in refractory stage Ⅱ MRONT patients.

The cost of doing business: Drug costs in federally sponsored cancer clinical trials.

10 Background: Federally sponsored cancer clinical trials (FS-CCTs) address a broad set of clinical cancer research questions that are avoided by industry sponsors, including combining treatment modalities, examining whether approved drugs may work in other cancers, or examining de-escalation therapy. FS-CCTs routinely extend the lives of patients with cancer and inform treatment guidelines. However, FS-CCTs must often be conducted in partnership with industry sponsors since the cost of drugs is high and cannot be paid for by the government. This limits the independence of FS-CCTs. We aimed to examine the drug costs for trials with federal sponsorship. Methods: We included all US-based cancer treatment trials registered in ClinicalTrials.gov that examined pharmaceuticals and/or biological products and started from 2018-2022. Trials with any NIH or other federal sponsorship (as the sole, lead, or other sponsor) were included. Drug names and number of enrollments per arm and drug were extracted from ClinicalTrials.gov and study protocols. The Wholesale Acquisition Cost (WAC) was obtained from IBM Micromedex RED BOOK (2023) by matching the product name, dose strength and administration route. The product acquisition cost (“cost”) per trial was computed by summing the WAC for each drug and multiplying by the number of enrollments. Results: Overall, N=1020 trials were examined (phase I = 343, phase II = 611, phase III = 66). The mean (median) drug costs were $53.9 million (m) ($7.4m) overall, including $73.8m ($19.8m), $47.2m ($8.7m), and $44.7m ($5.8m) for trials solely sponsored, led by, or with secondary/tertiary participation by federal sponsors, respectively. Trial-level drug costs were $19.2m ($3.6m), $51.9m ($9.4m), and $244.9m ($38.8m) for phase I, II, and III trials, respectively. Drug costs were much greater for trials involving immune and/or targeted therapies ($60.1m [$11.4m]) than those with conventional chemotherapies ($30.8m [$1.5m]). In the subset of n=128 phase 2 or 3 comparative trials, drug costs were $97.7m ($21.8m) for experimental arms and $24.1m ($1.4m) for control arms. Conclusions: The costs for drugs in FS-CCTs were very high, especially for the experimental arms, highlighting the necessity for federally sponsored researchers to collaborate with industry partners to conduct trials. Drug costs for immune and/or targeted therapies were higher yet, suggesting that the cost burden to conduct trials for federal sponsors may continue to increase. These findings also suggest that systemwide costs for cancer drugs in clinical practice will continue to increase substantially. These results have implications for how FS-CCTs are designed and conducted, since the necessity of collaboration between federal and industry sponsors likely limits the independence of federal research. Future public policy efforts should focus on mechanisms for independent investigation of new pharmacologic agents.

Possible sex and racial disparities in myasthenia gravis care.

Given the importance of early diagnosis and treatment of myasthenia gravis (MG), it is critical to understand disparities in MG care. We aimed to determine if there are any differences in testing, treatment, and/or access to neurologists for patients of varying sex and race/ethnicity with MG. We used a nationally representative healthcare claims database of privately insured individuals (2001-2018) to identify incident cases of MG using a validated definition. Diagnostic testing, steroid-sparing agents, intravenous immunoglobulin (IVIG), plasma exchange (PLEX), and thymectomy were defined using drug names or CPT codes. Steroid use was defined using AHFS class codes. We also determined whether an individual had a visit to a neurologist and the time between primary care and neurologist visits. Logistic regression determined associations between sex and race/ethnicity and testing, treatments, and access to neurologists. Female patients were less likely to get a computed tomography (CT) chest (odds ratio (OR) 0.73, 95% confidence interval (CI): 0.64-0.83), receive steroids (OR: 0.85, 95% CI: 0.75-0.97), steroid-sparing agents (OR: 0.84, 95% CI: 0.72-0.97), and IVIG or PLEX (OR: 0.80, 95% CI: 0.67-0.95). Black patients were less likely to receive steroids (OR: 0.78, 95% CI: 0.63-0.96). No significant disparities were seen in access to neurologists. We found healthcare disparities in MG treatment with female and Black patients receiving less treatment than men and those of other races/ethnicities. Further research and detailed assessments accounting for individual patient factors are needed to confirm these apparent disparities.

Medication Extraction and Drug Interaction Chatbot: Generative Pretrained Transformer-Powered Chatbot for Drug-Drug Interaction

ObjectiveTo assist individuals, particularly cancer patients or those with complex comorbidities, in quickly identifying potentially contraindicated medications when taking multiple drugs simultaneously. Patients and MethodsIn this study, we introduce the Medication Extraction and Drug Interaction Chatbot (MEDIC), an artificial intelligence system that integrates optical character recognition and Chat generative pretrained transformer through the Langchain framework. Medication Extraction and Drug Interaction Chatbot starts by receiving 2 drug bag images from the patient. It uses optical character recognition and text similarity techniques to extract drug names from the images. The extracted drug names are then processed through Chat generative pretrained transformer and Langchain to provide the user with information about drug contraindications. The MEDIC responds to the user with clear and concise sentences to ensure the information is easily understandable. This research was conducted from July 2022 to April 2024. ResultsThis streamlined process enhances the accuracy of drug-drug interaction detection, providing a crucial tool for health care professionals and patients to improve medication safety. The proposed system was validated through rigorous evaluation using real-world data, reporting high accuracy in drug-drug interaction identification and highlighting its potential to benefit medication management practices considerably. ConclusionBy implementing MEDIC, contraindicated medications can be identified using only medication packaging, and users can be alerted to potential drug adverse effects, thereby contributing to advancements in patient care in clinical settings.

Experimental Study of the Promotional Implications of Proprietary Prescription Drug Names.

The meaning and characteristics embedded in proprietary drug names have the potential to affect name recall, perceptions of drug benefits and risks, and attitudes toward a drug. In this study, we examined: (1) whether names that reference the drug's medical indication affect consumers' and primary care physicians' (PCPs') perceptions of the drug and (2) whether names that overstate the drug's efficacy affect consumers' and PCPs' perceptions of the drug. We conducted an online experiment with 455 PCPs and 450 consumers to test the effects of fictitious proprietary prescription drug names. Participants were randomized to view one neutral drug name, one name that overstated the drug's efficacy, and five names that referenced the drug's medical indication. Names that referenced the drug's medical indication and names that overstated the drug's benefit both influenced perceptions of efficacy and risk compared to neutral names. For several outcomes, names evoking medical indications had similar effects to those designed to overstate the drug's efficacy. The patterns of effects were similar for PCPs and consumers. Findings suggest drug names alone can be sufficient to produce attitudes and risk and benefit perceptions about drugs, even in the absence of any information beyond the drug's medical indication.

Original drugs and generics: are there any differences from the clinician’s point of view?

The article defines the original drug (OD) and examines the history of the appearance of generic drugs (GD), as well as the evolution of views to prove their bioequivalence to OD. The question is considered to what extent pharmacokinetic equivalence can guarantee the clinical equivalence of OD and GD. The data on the rules of registration of GD in different countries are provided. A brief overview of various types of studies comparing the clinical efficacy and safety of OD and GD (meta-analyses, randomized controlled trials, observational studies, description of clinical cases) and their main results is given. The results of a number of observational studies on the replacement of OD with GD and its consequences are presented. The existing system of current quality control of GD is described, numerous cases of recall of GD due to detected violations during their production are given. It is mentioned about individual cases of clinical inefficiency of GD and their side effects identified by the practical physicians. It is concluded that a qualitatively produced GD with proven pharmacokinetic equivalence to OD is able to provide therapy of the same quality as OD. However, numerous cases of the appearance of GD on the pharmaceutical market, which does not correspond to the quality of OD, make us somewhat wary of therapy based on VP. Both the practitioner and the patient should know which of the drugs prescribed by the international nonproprietary name is OD and which is GD.

Errors associated with co-names of medicines: The nomenclature of combination medicinal products.

In comparison to the efforts required to bring a new drug or formulation to the clinic, bestowing a name on a medicine is relatively simple. However, if the name we choose causes confusion-by making its contents ambiguous or if it is too alike another drug-it can precipitate clinical errors. This prompted the World Health Organization to set up the International Nonproprietary Naming Committee in the 1970s to select unambiguous names for drugs. Unfortunately, multidrug products-which are becoming increasingly popular-do not fall under the remit of conventional International Non-proprietary Nomenclature. We have identified 26 combination formulations that have been historically named with the co-drug format in the United Kingdom. Most of them have also been prescribed in the United Kingdom in the past year, and although several of them are not prescribed very often, 11 were prescribed more than 2000 times. In this paper, we have explored the literature to identify prescribing errors with co-drug products and found several idiosyncrasies that have caused drug errors in the past. We advocate for a standard nomenclature (state the international nonproprietary name [INN] of each component followed by dose information in the x + y format) for these products on the box and in prescribing resources. We hope that this will enhance clarity and safety during prescribing and administration, particularly for high-volume drugs like paracetamol + codeine (co-codamol), amoxicillin + clavulanic acid (co-amoxiclav) and trimethoprim + sulfamethoxazole (co-trimoxazole).

Analyzing the Impact of Drug Name Similarity on Dispensing Errors: An Examination Using a Drug Name Similarity Index.

Dispensing errors pose a significant health risk, with drug name similarity being a potential contributory factor. To determine the impact of drug name similarity on dispensing errors within clinical settings, we analyzed 563 dispensing errors at an acute hospital in Japan from April 2015 to June 2018. Drug name similarity between two drugs was classified into Name-Similar and Name-Dissimilar groups using the m2-vwhtfrag index, the value of the drug name similarity. Drug efficacy similarity was categorized into Efficacy-Same, Efficacy-Close, and Efficacy-Far. The drug name similarity and drug efficacy similarity of all possible pair combinations were obtained and similarly classified. The proportion of the number of pairs with dispensing errors per the total number of drug pairs in the hospital's drug formulary in each category was calculated. The highest proportion of the number of pairs with dispensing errors was 36% for the Efficacy-Same and Name-Similar group, and the lowest proportion was 0.022% for the Efficacy-Far and Name-Dissimilar group. The proportion of the number of pairs with dispensing errors was significantly higher in the Name-Similar category than in the Name-Dissimilar category for all drug efficacy categories. Our results indicate that drug name similarity increases the risk of dispensing errors, and that m2-vwhtfrag is a useful indicator to assess dispensing errors in clinical practice. Such drug name and efficacy similarity evaluations can help identify factors causing dispensing errors, and predict the risk of dispensing errors for newly adopted drugs, considering the relationship with the whole drug formulary in the hospital dispensary.

Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis.

Data from the social media platform X (formerly Twitter) can provide insights into the types of language that are used when discussing drug use. In past research using latent Dirichlet allocation (LDA), we found that tweets containing "street names" of prescription drugs were difficult to classify due to the similarity to other colloquialisms and lack of clarity over how the terms were used. Conversely, "brand name" references were more amenable to machine-driven categorization. This study sought to use next-generation techniques (beyond LDA) from natural language processing to reprocess X data and automatically cluster groups of tweets into topics to differentiate between street- and brand-name data sets. We also aimed to analyze the differences in emotional valence between the 2 data sets to study the relationship between engagement on social media and sentiment. We used the Twitter application programming interface to collect tweets that contained the street and brand name of a prescription drug within the tweet. Using BERTopic in combination with Uniform Manifold Approximation and Projection and k-means, we generated topics for the street-name corpus (n=170,618) and brand-name corpus (n=245,145). Valence Aware Dictionary and Sentiment Reasoner (VADER) scores were used to classify whether tweets within the topics had positive, negative, or neutral sentiments. Two different logistic regression classifiers were used to predict the sentiment label within each corpus. The first model used a tweet's engagement metrics and topic ID to predict the label, while the second model used those features in addition to the top 5000 tweets with the largest term-frequency-inverse document frequency score. Using BERTopic, we identified 40 topics for the street-name data set and 5 topics for the brand-name data set, which we generalized into 8 and 5 topics of discussion, respectively. Four of the general themes of discussion in the brand-name corpus referenced drug use, while 2 themes of discussion in the street-name corpus referenced drug use. From the VADER scores, we found that both corpora were inclined toward positive sentiment. Adding the vectorized tweet text increased the accuracy of our models by around 40% compared with the models that did not incorporate the tweet text in both corpora. BERTopic was able to classify tweets well. As with LDA, the discussion using brand names was more similar between tweets than the discussion using street names. VADER scores could only be logically applied to the brand-name corpus because of the high prevalence of non-drug-related topics in the street-name data. Brand-name tweets either discussed drugs positively or negatively, with few posts having a neutral emotionality. From our machine learning models, engagement alone was not enough to predict the sentiment label; the added context from the tweets was needed to understand the emotionality of a tweet.

AN OVERVIEW OF THE COMMUNITY KNOWLEDGE LEVEL TOWARDS THE USE OF GENERIC DRUGS IN TUPA VILLAGE, NORTH BULANGO DISTRICT, BONE BOLANGO REGENCY, GORONTALO PROVINCE, IN 2022

Generic drugs are medications with generic names, as defined by the Indonesian Pharmacopoeia and International Non-proprietary Names (INN) from the WHO, and they do not use trade names or manufacturer logos. Examples of these include amoxicillin and metformin. The public often perceives generic drugs to be inferior to patented drugs because of their relatively lower prices. The purpose of this study is to describe the knowledge level of the community about the use of generic drugs in Desa Tupa, Kecamatan Bulango Utara, Kabupaten Bone Bolango in 2022. This study employs a descriptive method using a quantitative approach. Data were collected through questionnaires that were distributed to 30 randomly selected respondents. A univariate analysis was conducted by creating frequency distributions to determine the community's awareness level regarding generic drugs. The survey results indicated that most residents of Desa Tupa have limited information about the use of generic drugs. The study concluded that, in terms of knowledge level about generic drugs, 30% of respondents had heard of generic drugs, 22% knew that generic drugs were named according to INN (International Non-proprietary Names), 11% understood that generic drugs are those that have expired patents, 9% recognize that generic drugs do not use brand names, and 28% are aware that generic drugs are more affordable than branded drugs.

Influential factors of adherence to inhalation drug therapy in patients with stable chronic obstructive pulmonary disease.

This study aimed to investigate the influential factors of adherence to inhalation drug therapy (IDT) in patients with stable chronic obstructive pulmonary disease (COPD). A total of 243 patients with stable COPD who visited the chronic disease clinic of the respiratory department of our hospital between April 2022 and October 2022 were selected as participants using the convenience sampling method. Relevant information about all participants was collected by questionnaire for investigation, including basic information, clinical characteristics, inhaled drug names, situational awareness, dose and frequency. Univariate analysis revealed positive correlations between the following factors: (1) the total score of drug adherence and the total scores of the COPD knowledge questionnaire (COPD-Q), social support, subjective support, objective support and support utilisation, (2) the total score of dosage adherence and the total scores of COPD-Q, objective support and support utilisation and (3) the total score of technical standardisation and the total scores of social support, subjective support and objective support (p < 0.05). Multifactorial analysis showed that COPD health literacy, number of acute exacerbations in the past year and social support factors collectively accounted for 37.4% of the variable of patient adherence to IDT, as did COPD health literacy, modified Medical Research Council (mMRC) grading, duration of COPD, utilisation of support and marital status collectively account for 47.4% of the variable of patient dosage adherence. The goodness-of-fit of age, mMRC grading, social support, mode of residence, number of acute exacerbations in the past year and literacy to the patients' inhalation technical standardisation in the model was 47.4%. Dose adherence was predominantly influenced by COPD health literacy, mMRC grading, duration of COPD, utilisation of support and marital status. Inhalation technical standardisation was substantially limited by age, mMRC grading, social support, mode of residence, number of acute exacerbations in the past year and literacy.

Design, development, and evaluation of a multi-lingual web-based database for informing people regarding driving-impairing medicines

Objective Driving under the influence of drugs (DUID) is a growing traffic safety problem in many countries. It is estimated that 5 to 10% of medicinal drugs may impair driving due to their side effects. Despite the high number of medicinal drugs prescribed in Iran, there is a lack of a database that could provide specialized information regarding medicinal drugs and driving. Therefore, the present study aimed to design, develop, and evaluate a database for informing the general public, drivers, and healthcare providers regarding driving-impairing medicines. Methods The Drugs-and-traffic-safety (DATS) database, which has been developed by Road Traffic Injury Research Center (RTIRC), was designed using Java, HTML, JavaScript and MySql database. After completing the testing process, pharmaceutical data (i.e., generic and brand names, route of administration, anatomical classification, etc.), the level of influence of medicinal drugs on driving, and driving-related recommendations based on the level of influence for consumers were entered into the database. A cross-sectional study, and a qualitative study as semi-structured interviews and expert panels were conducted in different target groups to evaluate the DATS. Finally, the evaluation results were used to improve the database. The quantitative and qualitative data were analyzed using SPSS 25.0 and MAXQDA-10, respectively. Results The DATS was the only web-based database that could be accessed online via different browsers. The database included information about 1,255 medicinal drugs, and their influence on driving was shown with four colors, i.e., green (insignificant or no effect), yellow (mild effect), orange (moderate effect), and red (severe effect). The database was designed in multiple languages, which could enable users to search for medicinal drug names in both Persian and English. Based on the quantitative results, the mean score of the DATS was 75.10 ± 16.01 (out of 100) from the public viewpoint, indicating that the users were relatively satisfied with the database. Some themes and subthemes were extracted from the qualitative section of the study which revealed the users found DATS a practical, useful, and user-friendly tool. Conclusion Considering the positive feedback of users about DATS in the quantitative and qualitative evaluations, implementing DATS in Iran could provide useful advice in terms of the influence of medicinal drugs on driving to the public and traffic users. Therefore, it can raise public awareness of the risk of driving under the influence of medicinal drugs.

CRITICAL ANALYSIS OF CLAIMS IN DRUG PROMOTIONAL LITERATURE AVAILABLE TO MEDICAL PRACTITIONERS

Context: Objective: To ascertain whether the pharmaceutical companies are following the World Health Organisation (WHO) criteria for Ethical Medicinal Drug Promotion 2015 and Organisation of Pharmaceutical Producers of India (OPPI) Code of Pharmaceutical Marketing Practices, 2019 and to what extent. Also, to evaluate the therapeutic claims made by them in their drug promotional literature (DPL) and to classify them. Methods: DPL brochures were collected from different pharmaceutical companies from various medical practitioners and assessed for ethical promotion based on guidelines. Therapeutic claims made by them were classified as authentic, exaggerated, controversial, false, misinterpreted, and ambiguous. Results: A total of 100 DPLs were collected and critically analyzed for authenticity of the content. It was observed that the majority of the DPLs did not comply with the criteria mentioned in the WHO Criteria of Ethical Promotion 2015 and the OPPI Code of Pharmaceutical Practices 2019. International non-proprietary names and the brand name were mentioned by 100% of DPLs. The amount of active ingredients and approved therapeutic indications were mentioned by (99%) and (96%) respectively. The dosage form or regimen was mentioned by 87% of DPLs. Criteria like side effects, precautions/contraindications, and major interactions were mentioned in 28%, 29%, and 14% respectively. Based on the therapeutic claims 23% of the DPLs were found to be authentic and the remaining 77% were extravagant. Conclusions: This study enabled us to find out to what extent the pharmaceutical industries follow the standard criteria for DPL and evaluate the claims made by them. The majority of the DPLs did not follow ethical guidelines and were inadequate in terms of their adequacy, quality, and reliability.

PRESCRIPTION PROFILE OF ANTIHYPERTENSIVE DRUGS IN PREECLAMPSIA PATIENTS AT KIRANA HOSPITAL

Preeclampsia is a complication of pregnancy with symptoms of hypertension ≥ 140/90 mmHg and proteinuria ≥ 0.3 grams/24 hours or 30 mg/dl (+1 dipstick) arising after more than 20 weeks of gestation in previously normotensive pregnant women. Maternal deaths in Indonesia in 2021 related to hypertension in pregnancy reached 1077 cases (Source: Directorate General of Public Health, Ministry of Health, 2021). Pharmacological therapy intervention, antihypertensive treatment is also needed in addition to maintaining a healthy lifestyle. The purpose of the study was to determine the description of pharmacological therapy including the pharmacological class of drugs, drug names, drug doses, rules of use, and types of antihypertensive drug therapy (single / combination) in patients with preeclampsia. This type of descriptive observational research is retrospective with total sampling obtained from medical records and patient prescriptions. The results of this study were the incidence of preeclampsia aged 35 years and over by 21 patients (36%) and the most common diagnosis was mild preeclampsia by 38 samples (66%). The use of nifedipine which is included in the CCB (Calcium Channel Blocker) group was 42 respondents (72%). Meanwhile, the use of methyldopa which is included in the central sympatholytic group was 17 respondents (28%). In the single therapy type study, 59 prescriptions (100%) used nifedipine or methyldopa. Pregnant women are encouraged to routinely conduct antenatal care checks at the hospital every month.