Wikipedia Drug Safety Advisory Committee: Distilling a Drug Adverse Effect Reference Set Using Wisdom of the Crowd

Large datasets of relational medical data, such as the adverse effects of drugs or vaccines, typically attain their large size, by relying on automatic, or semi-automatic, methods for generation. This often comes with a compromise on the precision of generated data, which can be at least partially alleviated by having experts curate the data. Since having experts review a large dataset can be costly and time consuming, here we suggest using Wikipedia for this task - that is, augment the automatic generation step by an automatic curation step based on the expert knowledge accumulated in Wikipedia. We use the method to curate two large adverse drug effects datasets, and show that the obtained datasets have a much higher precision relative to their originating ones.

Prevalence and Significance of Antibiotic-Associated Adverse Reactions

The World Health Organization (WHO) defines Pharmacovigilance as the science and activities relating to the detection, assessment, understanding and prevention of adverse drug effects. The aim is to promote the safety and effective use of medicines through an early detection and evaluation of drug safety risks. The pharmacovigilance system is essentially based in spontaneous reports of Adverse Drug Reactions (ADR). ADR can be associated with severe outcomes and significant mortality, besides, most of them are deemed to be preventable events. Globally, antibiotics are among the most widely prescribed medications and their extensive use is linked to antibiotic-associated ADR. This chapter aims to summarize available epidemiological data concerning antibiotic use related ADR and analyze the reports received by the EudraVigilance system regarding the exclusive usage of antibiotics.

Perceived barriers to psychiatric help-seeking in South Korea by age groups: Text mining analyses of social media big data (Preprint)

BACKGROUND In South Korea, the psychiatric treatment gap is huge. Sociocultural context, such as stigma attached to mental illness, limit opportunities for professional help-seeking. OBJECTIVE This study uses TM of the internet to investigate barriers by age groups to receiving psychiatric treatment. METHODS A corpus of data was collected from web communities, social network services, and personal blogs on the internet from 1 January 2016 to 31 July 2019. Words frequently linked with psychiatry were collected by natural language processing. Words that may be associated with barriers to receiving psychiatric help were identified and categorized. Because the data from web communities could be classified approximately according to age, the analyses were arranged by age groups. RESULTS A total of 97,730,360 articles were identified for the period in question, among which 6,097,369 texts contained keywords relevant to psychiatry. Among words that were associated with ‘psychiatry,’ approximately 3,000 were selected based on their frequency of occurrence. Words associated with barriers to receiving psychiatric help were categorized into the following four groups: structural discrimination, public prejudice, low accessibility, and adverse drug effects. Structural discrimination was the greatest barrier (34%), followed by public prejudice (27.8%), adverse drug effects (18.6%), and cost/low accessibility (16.1%). Structural discrimination was the greatest barrier in the groups consisting of teenagers (51%), job seekers (64%), and young mothers (43%). However, in the seniors group, the greatest barrier was public prejudice (49%). CONCLUSIONS Structural discrimination is the greatest barrier to receiving psychiatric help in Korea. Difference in the barriers, however, exists among age groups. As well as addressing structural issues for all, more tailored approaches may be required by generations to lower the gap.

CYP2D6 phenotype and ABCB1 haplotypes are associated with antipsychotic safety in adolescents experiencing acute psychotic episodes

Objectives To identify possible associations of CYP2D6, CYP3A4/5, and ABCB1 gene polymorphisms with the efficacy and safety of antipsychotics in adolescents with acute psychotic episodes. Methods We examined the associations of pharmacogenetic factors with the efficacy and safety of antipsychotics in 101 adolescents with acute psychotic episodes. The diagnosis on admission was “Brief psychotic disorder” (F23.0–23.9 by ICD-10). All patients were administered antipsychotics for 14 days. Treatment efficacy and safety were assessed using the PANSS, CGAS, CGI-S(I), UKU SERS, BARS, and SAS scales. Pharmacokinetic genotyping was performed for the CYP2D6*4, *10, ABCB1 1236C>T, 2677G>T, and 3435C>T genes. Results CYP2D6 intermediate metabolisers had “Micturition disturbances” more often than extensive metabolisers (24.2 vs. 7.4%; p=0.026). “Wild” homozygote ABCB1 3435C>T CC was associated with more prominent akathisia. Haplotype analysis of three ABCB1 polymorphisms revealed that the “wild” alleles “C-G-C” (ABCB1 1236-2677-3435) were associated with higher risk of “Reduced salivation” (OR=2.95; 95% CI=1.35–6.45; p=0.0078). Conclusions CYP2D6 intermediate metabolism was associated with the risk of urinary difficulties under treatment with antipsychotics. We found that “wild” homozygotes ABCB1 1236C>T, 2677G>T, and 3435C>T were predictors of adverse drug effects caused by treatment with antipsychotics.

Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria

The human gut microbiome, composed of trillions of microorganisms, plays an essential role in human health. Many factors shape gut microbiome composition over the life span, including changes to diet, lifestyle, and medication use. Though not routinely tested during drug development, drugs can exert profound effects on the gut microbiome, potentially altering its functions and promoting disease. This study develops a machine learning (ML) model to predict whether drugs will impair the growth of 40 gut bacterial strains. Trained on over 18,600 drug–bacteria interactions, 13 distinct ML models are built and compared, including tree-based, ensemble, and artificial neural network techniques. Following hyperparameter tuning and multi-metric evaluation, a lead ML model is selected: a tuned extra trees algorithm with performances of AUROC: 0.857 (±0.014), recall: 0.587 (±0.063), precision: 0.800 (±0.053), and f1: 0.666 (±0.042). This model can be used by the pharmaceutical industry during drug development and could even be adapted for use in clinical settings.

Pharmacovigilance in Older Adults

Polypharmacy and physiological changes inherent to the aging process can cause significant modifications in the pharmacokinetic and dynamic regimens of drugs, making the elderly more susceptible to adverse drug effects. Adverse drug reactions (ADR) in older adults have a significant impact on hospital admissions, increasing hospital stay and healthcare costs. Most common ADR in this population are dose-related and predictable. However, they can be difficult to diagnose as they often have nonspecific symptoms. This could be minimized by decreasing the use and prescription of potentially inappropriate medication and being aware of possible drug interactions. Besides, being older patients underrepresented in clinical trials and due to their physiological modifications, serious or atypical ADR are more common in this age range. To minimize harm in older adults, effective pharmacovigilance must be encouraged.

Pharmacognostic, Phytochemical and Therapeutic Overview of three Allied Herbs used in Dentistry

The dental herbs are very much essential for the treatment of many dental problems. They can be used as such or in the form of dental formulations. These dental formulations of the herbs have enormous economical importance too. Apart from the pharmaco-therapeutic role the pharmacognostic and it’s chemical composition is also essential. These parameters help to modify the formulations and to overcome the adverse drug effects associated with these. The present review work tries to highlight the Pharmacognostic and Phytochemical aspects of three dental herbs.

Adverse Drug Effects and Non-Adherence to Antiretroviral Therapy in Nigeria: A Review

Objectives: This review aims to assess the link between adverse drug effects and non-adherence to antiretroviral therapy (ART) among people living with HIV/AIDS (PLWHA) in Nigeria. Methodology: Databases were searched namely PubMed, Web of science core collection, Science direct, Global Health (CABI) and MEDLINE. Fifteen (15) primary articles (studies carried out in Nigeria) met the inclusion criteria and were selected for the review. The primary articles selected for the review were analyzed and critiqued. Results: The articles selected for review showed that adverse drug effects is a barrier to adherence to ART. Conclusion: The review conclude that adverse drug effect is a barrier to adherence to ART among PLWHA in Nigeria and recommends patient education on side effects of ART, the need for regular exercises, eating healthy meals and the need for physicians to simplify the regimen with regards to the amount of medication to take and the timing.