Adverse drug reactions

Exploring common mechanisms of adverse drug reactions and disease phenotypes through network-based analysis

The need for a deeper understanding of adverse drug reaction (ADR) mechanisms is vital for improving drug safety and repurposing. This study introduces Drug Adverse Reaction Mechanism Explainer (DREAMER), a network-based framework that uses a comprehensive knowledge graph to uncover molecular mechanisms underlying ADRs and disease phenotypes. By examining shared phenotypes of drugs and diseases and their effects on protein-protein interaction networks, DREAMER identifies proteins linked to ADR mechanisms. Applied to 649 ADRs, DREAMER identified molecular mechanisms for 67 ADRs, including ventricular arrhythmia and metabolic acidosis, and emphasized pathways like GABAergic signaling and coagulation proteins in personality disorders and intracranial hemorrhage. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes, emphasizing the importance of network-based analyses with integrative data for enhancing drug safety and accelerating the discovery of novel therapeutic strategies.

DDInter 2.0: an enhanced drug interaction resource with expanded data coverage, new interaction types, and improved user interface

Drug interactions pose significant challenges in clinical practice, potentially leading to adverse drug reactions, reduced efficacy, and even life-threatening consequences. As polypharmacy becomes increasingly common, the risk of harmful drug interactions rises, underscoring the need for comprehensive and user-friendly drug interaction resources to ensure patient safety. To address these concerns and support healthcare professionals in optimizing drug therapy, we present DDInter 2.0, a significantly expanded and enhanced update to our drug interaction database. This new version incorporates additional interaction types, including drug-food interactions (DFIs), drug-disease interactions (DDSIs), and therapeutic duplications, providing a more complete resource for clinical decision-making. The updated database covers 2310 drugs, with 302 516 drug-drug interaction (DDI) records accompanied by 8398 distinct, high-quality mechanism descriptions and management recommendations. DDInter 2.0 also includes 857 DFIs, 8359 DDSIs and 6033 therapeutic duplication records, each supplemented with detailed information and guidance. Furthermore, the enhanced user interface and advanced filtering options in this second release facilitate easy access to and analysis of the comprehensive drug interaction data. By providing healthcare professionals and researchers with a more complete and user-friendly resource, DDInter 2.0 aims to support clinical decision-making and ultimately improve patient outcomes. DDInter 2.0 is freely accessible at https://ddinter2.scbdd.com.

HSTrans: Homogeneous substructures transformer for predicting frequencies of drug-side effects

Identifying the frequencies of drug-side effects is crucial for assessing drug risk-benefit. However, accurately determining these frequencies remains challenging due to the limitations of time and scale in clinical randomized controlled trials. As a result, several computational methods have been proposed to address these issues. Nonetheless, two primary problems still persist. Firstly, most of these methods face challenges in generating accurate predictions for novel drugs, as they heavily depend on the interaction graph between drugs and side effects (SEs) within their modeling framework. Secondly, some previous methods often simply concatenate the features of drugs and SEs, which fails to effectively capture their underlying association. In this work, we present HSTrans, a novel approach that treats drugs and SEs as sets of substructures, leveraging a transformer encoder for unified substructure embedding and incorporating an interaction module for association capture. Specifically, HSTrans extracts drug substructures through a specialized algorithm and identifies effective substructures for each SE by employing an indicator that measures the importance of each substructure and SE. Additionally, HSTrans applies convolutional neural network (CNN) in the interaction module to capture complex relationships between drugs and SEs. Experimental results on datasets from Galeano et al.'s study demonstrate that the proposed method outperforms other state-of-the-art approaches. The demo codes for HSTrans are available at https://github.com/Dtdtxuky/HSTrans/tree/master.

A scoping review of the clinical utility of adverse drug reaction causality analysis tools for use in the hospital setting

INTRODUCTION

Identification and monitoring of adverse drug reactions (ADRs) and interventions to reduce ADRs are essential for patient safety in hospitals. Causality analysis (CA) is an approach that helps to determine a causal link between medication and patient harm (i.e. an ADR). While numerous CA tools exist, there is no gold standard.

AREAS COVERED

Five online databases were searched to identify studies that evaluated the potential clinical utility of CA tools for ADRs. CA tools were mapped against the Bradford Hill (BH) criteria and included if they adhered to the first seven criteria proposed by BH. Upon the database search, 550 studies were identified, with 41 studies being selected that looked at tools mapped to BH. Thirty-four different CA tools were identified in the included studies.

EXPERT OPINION

Naranjo and WHO-UMC were the most reported CA tools for studies examining inter-rater and intra-rater reliability. Naranjo commonly received a 'fair' agreement level while WHO-UMC received a 'substantial' agreement level between raters. Along with kappa statistics, time using the CA tool was also analyzed, with WHO-UMC being the most time-efficient. There does not appear to be one CA tool that can be applied universally to pharmacovigilance efforts in hospital in-patient settings.

A review of serious adverse events linked with GLP-1 agonists in type 2 diabetes mellitus and obesity treatment

Glucagon-like peptide-1 (GLP-1) agonists play a crucial role in treating type 2 diabetes mellitus and obesity by providing glycemic control and aiding weight management. Despite their widespread use, concerns about serious adverse events have prompted extensive research. This review aims to describe the current understanding of serious adverse events associated with GLP-1 agonists. A comprehensive search of PubMed, Google Scholar and Embase databases was performed starting from 2010. Studies reporting evidence of an association between GLP-1 agonists and serious adverse events from 22 articles (5 case reports, 5 randomized controlled trials (RCTs), 9 real-world data cohort analyses, 2 meta-analyses and 1 systematic review and meta-analysis) were included and categorized by the type of adverse event. While some studies reported risks, including anaphylaxis, cardiovascular, gastrointestinal, psychiatric and thyroid-related events, others found no significant associations. The evidence remains mixed, necessitating further research to fully understand the safety profile of GLP-1 agonists and inform clinical practice.

DREAMER: Exploring Common Mechanisms of Adverse Drug Reactions and Disease Phenotypes through Network-Based Analysis

Adverse drug reactions (ADRs) are a major concern in clinical healthcare, significantly affecting patient safety and drug development. This study introduces DREAMER, a novel network-based method for exploring the mechanisms underlying ADRs and disease phenotypes at a molecular level by leveraging a comprehensive knowledge graph obtained from various datasets. By considering drugs and diseases that cause similar phenotypes, and investigating their commonalities regarding their impact on specific modules of the protein-protein interaction network, DREAMER can robustly identify protein sets associated with the biological mechanisms underlying ADRs and unravel the causal relationships that contribute to the observed clinical outcomes. Applying DREAMER to 649 ADRs, we identified proteins associated with the mechanism of action for 67 ADRs across multiple organ systems. In particular, DREAMER highlights the importance of GABAergic signaling and proteins of the coagulation pathways for personality disorders and intracranial hemorrhage, respectively. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes.

Identifying strategies to improve adverse drug reporting through key informant interviews among community pharmacists in a developing country

Reporting adverse drug reactions (ADRs) is fundamental in improving medication safety. Community pharmacists (CPs) being the first point of contact for individuals seeking healthcare in a community, play a significant role in ADR reporting. However, this has been poorly implemented in many countries including Nigeria. This paper aims to explore stakeholders' perspectives on current reporting practices and suggest ways to enhance ADR reporting among CPs in Nigeria. This qualitative study employed a purposive sampling approach to identify key informants. Key informant interviews (KIIs) were conducted with 25 carefully selected pharmacists, using a semi-structured interview guide between July 2023 and August 2023. The interview transcripts were analyzed using a thematic content approach. While a low ADR reporting trend was observed among all participating pharmacists, it was notably higher among those with less than five years of experience. The main barriers to ADR reporting, as identified by the interviewed community pharmacists were lack of awareness and knowledge, absence of motivation, and insufficient feedback from National Agency for Food Drug Administration and Control (NAFDAC). Training and awareness campaigns were the most frequently suggested methods for improving ADR reporting. Other proposed strategies included providing motivation, regular feedback, establishing mandatory reporting, and simplifying the reporting process. The study has highlighted the suboptimal ADR reporting practices among CPs in Anambra state. It underscores the significance of training, sensitization, advocacy, and other related interventions as pivotal means to enhance ADR reporting in this group. Furthermore, there is a pressing need for intervention-based studies to delve into and implement these approaches effectively.

Genetic Variants in the ABCB1 and ABCG2 Gene Drug Transporters Involved in Gefitinib-Associated Adverse Reaction: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis aimed to verify the association between the genetic variants of adenosine triphosphate (ATP)-binding cassette subfamily B member 1 (ABCB1) and ATP-binding cassette subfamily G member 2 (ABCG2) genes and the presence and severity of gefitinib-associated adverse reactions. We systematically searched PubMed, Virtual Health Library/Bireme, Scopus, Embase, and Web of Science databases for relevant studies published up to February 2024. In total, five studies were included in the review. Additionally, eight genetic variants related to ABCB1 (rs1045642, rs1128503, rs2032582, and rs1025836) and ABCG2 (rs2231142, rs2231137, rs2622604, and 15622C>T) genes were analyzed. Meta-analysis showed a significant association between the ABCB1 gene rs1045642 TT genotype and presence of diarrhea (OR = 5.41, 95% CI: 1.38-21.14, I2 = 0%), the ABCB1 gene rs1128503 TT genotype and CT + TT group and the presence of skin rash (OR = 4.37, 95% CI: 1.51-12.61, I2 = 0% and OR = 6.99, 95%CI: 1.61-30.30, I2= 0%, respectively), and the ABCG2 gene rs2231142 CC genotype and presence of diarrhea (OR = 3.87, 95% CI: 1.53-9.84, I2 = 39%). No ABCB1 or ABCG2 genes were positively associated with the severity of adverse reactions associated with gefitinib. In conclusion, this study showed that ABCB1 and ABCG2 variants are likely to exhibit clinical implications in predicting the presence of adverse reactions to gefitinib.

Structure-activity relationships andz interindividual variability of drug responses: pharmacogenomics with antimicrobial drugs as a paradigm

Adverse drug reactions represent a major health burden because they cause notable patient morbidity and mortality. From this viewpoint, several strategies have been developed to prevent or reduce adverse drug reactions. One such strategy is the use of pharmacogenomics. Interindividual variability in drug response and adverse effects is mainly attributable to genetic variation in enzymes such as sulfotransferases and cytochrome P450s. The current narrative review discusses the relationship between the structure and activity of drugs. Specifically, the activity of drugs can be increased and/or their adverse effects can be reduced by altering specific positions in their structures.

[Pharmacovigilance of vaccines against COVID-19 in community pharmacies. Results after the second dose and comparison between both]

Aim

Detection and tracing of suspicious adverse reactions (ARs) in community pharmacies after the second of COVID-19 vaccine dose. Comparison between doses.

Methods

Design: prospective observational study.

Subjects

Vaccinated against COVID-19, of legal age, who consent to participate.

Variables

Number and percentage of participants with ARs. Number, type and frequency of ARs. Impact on their daily life. Relations between variables.Approved by the Galician Ethical Committee of Research with medicines.

Results

693 participants with the 2nd dose, 63.6% women. Age 56.8 years. 312 (45.0%) vaccinated, 49.4% women and 37.3% men (p<0.0001), reported at least one AR: 43.9% with Comirnaty®, 37.7% with Vaxzevria®, 63.0% with Spikevax®.There were 972 ARs, 75.2% in women and 24.8% in men (p<0.0001). Mean 1.4/vaccinated (maximum 11). The most prevalent AR: pain at injection site 197 (28.4%), tiredness/fatigue 141 (20.3%), myalgia 112 (16.2%), headache 95 (13.7%), fever 84 (12.1%).51 participants with ARs needed professional help: 10 from the doctor, 6 in the emergency room, 3 in hospitals (1 referral), 33 in the pharmacy. 70 (15.1%) were prevented from their daily activity. 201 Ars from vaccinated persons were reported.Number of people vaccinated with ARs and the number of ARs were less with the 2nd dose (p<0.05).Inverse relationship (p<0.05) between "age" and "number of vaccinated with ARs", "need for professional care" and "prevented daily activity".

Conclusions

The number of vaccinated participants with ARs and their number was also high with the second dose, although lower than with the first. Women and younger people are predictive of increased risk of AR after vaccination against COVID-19.

Review of Natural Language Processing in Pharmacology

Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understand it to a certain degree, and use it in various applications. This area has rapidly developed in the past few years and now employs modern variants of deep neural networks to extract relevant patterns from large text corpora. The main objective of this work is to survey the recent use of NLP in the field of pharmacology. As our work shows, NLP is a highly relevant information extraction and processing approach for pharmacology. It has been used extensively, from intelligent searches through thousands of medical documents to finding traces of adversarial drug interactions in social media. We split our coverage into five categories to survey modern NLP: methodology, commonly addressed tasks, relevant textual data, knowledge bases, and useful programming libraries. We split each of the five categories into appropriate subcategories, describe their main properties and ideas, and summarize them in a tabular form. The resulting survey presents a comprehensive overview of the area, useful to practitioners and interested observers. SIGNIFICANCE STATEMENT: The main objective of this work is to survey the recent use of NLP in the field of pharmacology in order to provide a comprehensive overview of the current state in the area after the rapid developments that occurred in the past few years. The resulting survey will be useful to practitioners and interested observers in the domain.

[Pharmacovigilance of vaccines against COVID-19 in community pharmacies. Results with the first dose]

Aim

Detection, reporting and monitoring of suspected Adverse Drug Reactions (ADR) in users of community pharmacies and their impact on health and daily life.

Methods

Design: prospective observational. Subjects: people vaccinated against COVID-19, of legal age, who signed informed consent. Variables: number and percentage of participants who had at least one ADR. Number, type and frequency of possible reactivity. Impact on your daily life. The study was approved by CEIm-G (Exp. 2021-007).

Results

10 pharmacies from Pontevedra and 2 from Ourense collaborated. 781 cases, 488 (62.5%) women. Age 56.8 (SD=17.9) years. 389 (49.8%) in risk group.495 (63.4%) vaccinated, 321 women (65.8%) and 174 (59.4%) men, reported at least one ADR: 236 (53.0%) Comirnaty®, 157 (82.6%) Vaxzevria®, 69 (66.3%) Spikevax® and 33 (80.5) Janssen®.1,367 ADR were recorded. The most prevalent: pain at the injection point 375 (48.0%), tiredness/fatigue 170 (21.8%), chills 118 (15.1%), headache 117 (15.0%), muscle pain 112 (14.3%) and fever 98 (12.5%).Of the 495 respondents with ADR, 77 (15.6%) needed professional help: from the family doctor 30 (39.0%), 9 (11.7%) in the emergency department, 1 (1.3%) in the hospital and 37 (48.1%) in the pharmacy. 118 (15.1%) were unable to carry out their daily activity.ADR were reported from 264 (53.3%) vaccinated.

Conclusions

The number of vaccinated people who reported having suffered RA was high. Pain at the injection site the most prevalent. Half were treated at the pharmacy. Although they were generally mild, they markedly affected his daily life.

Large-scale prediction of adverse drug reactions-related proteins with network embedding

MOTIVATION

Adverse drug reactions (ADRs) are a major issue in drug development and clinical pharmacology. As most ADRs are caused by unintended activity at off-targets of drugs, the identification of drug targets responsible for ADRs becomes a key process for resolving ADRs. Recently, with the increase in the number of ADR-related data sources, several computational methodologies have been proposed to analyze ADR-protein relations. However, the identification of ADR-related proteins on a large scale with high reliability remains an important challenge.

RESULTS

In this article, we suggest a computational approach, Large-scale ADR-related Proteins Identification with Network Embedding (LAPINE). LAPINE combines a novel concept called single-target compound with a network embedding technique to enable large-scale prediction of ADR-related proteins for any proteins in the protein-protein interaction network. Analysis of benchmark datasets confirms the need to expand the scope of potential ADR-related proteins to be analyzed, as well as LAPINE's capability for high recovery of known ADR-related proteins. Moreover, LAPINE provides more reliable predictions for ADR-related proteins (Value-added positive predictive value = 0.12), compared to a previously proposed method (P < 0.001). Furthermore, two case studies show that most predictive proteins related to ADRs in LAPINE are supported by literature evidence. Overall, LAPINE can provide reliable insights into the relationship between ADRs and proteomes to understand the mechanism of ADRs leading to their prevention.

AVAILABILITY AND IMPLEMENTATION

The source code is available at GitHub (https://github.com/rupinas/LAPINE) and Figshare (https://figshare.com/articles/software/LAPINE/21750245) to facilitate its use.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pathology of drug hypersensitivity reactions and mechanisms of immune tolerance

Immune-mediated type IV adverse drug reactions are idiosyncratic in nature, generally not related to the primary or secondary pharmacology of the drug. Due to their complex nature and rarity, these iatrogenic reactions are seldom predicted or encountered during preclinical/early clinical development stages, and often precipitate upon exposure to wider populations (i.e. phase III onwards). They confer a burden on the healthcare sector in both a clinical and financial sense presenting a severe impediment to the drug discovery and development process. Research over the past 50 years has improved our understanding of these reactions markedly as both in vitro and in vivo studies have placed the role of the immune system, in particular; drug-responsive T cells, firmly in the spotlight as the mediators of these reactions. Indeed, the role of different populations of T cells in adverse events and the interaction of drug molecules with HLA proteins expressed on the surface of antigen-presenting cells is of considerable interest. Herein, this review examines the pathways of immune-mediated adverse events including the various T cell subtypes implicated and the mechanisms of T cell activation. Additionally, we address the enigma of immunological tolerance and explore the role tolerance plays in determination of susceptibility to such adverse events even in individuals carrying immunogenic liabilities.

Motivation and Knowledge of Portuguese Community Pharmacists Towards the Reporting of Suspected Adverse Reactions to Medicines: A Cross-Sectional Survey

The close contact between patients and community pharmacists, along with the extensive geographical distribution of pharmacies in Portugal, offer exceptional conditions to detect and report adverse drug reactions (ADR). This study aimed to evaluate the motivation and knowledge of spontaneous reporting of ADR by community pharmacists of Porto, Portugal. Secondly, we aimed to generate real-world evidence on the main factors determining ADR report and at raising potential alternatives to the current reporting procedure in community pharmacy. We performed a descriptive, cross-sectional, observational, anonymous web survey-based study. Between April and July 2021, a web survey was implemented, targeting community pharmacists in the Porto district, Portugal. We validated 217 surveys from pharmacists. Regular notifiers seem to be more familiarised than non-regular notifiers with the Portuguese Pharmacovigilance System (PPS), with the Portal RAM for reporting suspected ADR, and with the update of the concept of ADR. Moreover, regular notifiers seem to be more proactive with their care in questioning patients about ADR and have more self-knowledge to identify suspected ADR. Conversely, non-regular notifiers, seem to be more reluctant to be judged by their ADR reporting activities. Respondents suggested to simplify and optimise the reporting process (31% of the suggestions), or to integrate a reporting platform into the pharmacy's software (27%). This study identified opportunities to promote the ADR reporting process by community pharmacists, namely receiving feedback from the PPS on the reported case and its regulatory implications, implementing training programs in pharmacovigilance, and creating solutions to simplify the reporting process.

An Assessment of Mentions of Adverse Drug Events on Social Media With Natural Language Processing: Model Development and Analysis

BACKGROUND

Adverse reactions to drugs attract significant concern in both clinical practice and public health monitoring. Multiple measures have been put into place to increase postmarketing surveillance of the adverse effects of drugs and to improve drug safety. These measures include implementing spontaneous reporting systems and developing automated natural language processing systems based on data from electronic health records and social media to collect evidence of adverse drug events that can be further investigated as possible adverse reactions.

OBJECTIVE

While using social media for collecting evidence of adverse drug events has potential, it is not clear whether social media are a reliable source for this information. Our work aims to (1) develop natural language processing approaches to identify adverse drug events on social media and (2) assess the reliability of social media data to identify adverse drug events.

METHODS

We propose a collocated long short-term memory network model with attentive pooling and aggregated, contextual representation generated by a pretrained model. We applied this model on large-scale Twitter data to identify adverse drug event-related tweets. We conducted a qualitative content analysis of these tweets to validate the reliability of social media data as a means to collect such information.

RESULTS

The model outperformed a variant without contextual representation during both the validation and evaluation phases. Through the content analysis of adverse drug event tweets, we observed that adverse drug event-related discussions had 7 themes. Mental health-related, sleep-related, and pain-related adverse drug event discussions were most frequent. We also contrast known adverse drug reactions to those mentioned in tweets.

CONCLUSIONS

We observed a distinct improvement in the model when it used contextual information. However, our results reveal weak generalizability of the current systems to unseen data. Additional research is needed to fully utilize social media data and improve the robustness and reliability of natural language processing systems. The content analysis, on the other hand, showed that Twitter covered a sufficiently wide range of adverse drug events, as well as known adverse reactions, for the drugs mentioned in tweets. Our work demonstrates that social media can be a reliable data source for collecting adverse drug event mentions.

Drug dosing in children with obesity: a narrative updated review

Childhood obesity and its associated comorbidities are highly prevalent diseases that may add to any other possible health problem commonly affecting the pediatric age. Uncertainties may arise concerning drug dosing when children with obesity need pharmacologic therapies. In general, in pediatric practice, there is a tendency to adapt drug doses to a child's total body weight. However, this method does not consider the pharmacological impact that a specific drug can have under a two-fold point of view, that is, across various age and size groups as well. Moreover, there is a need for a therapeutic approach, as much as possible tailored considering relevant interacting aspects, such as modification in metabolomic profile, drug pharmacokinetics and pharmacodynamics. Taking into account the peculiar differences between children with overweight/obesity and those who are normal weight, the drug dosage in the case of obesity, cannot be empirically determined solely by the per kg criterion. In this narrative review, we examine the pros and cons of several drug dosing methods used when dealing with children who are affected also by obesity, focusing on specific aspects of some of the drugs most frequently prescribed in real-world practice by general pediatricians and pediatric subspecialists.

Development and Implementation of an e-Trigger Tool for Adverse Drug Events in a Swiss University Hospital

PURPOSE

The purpose of the study was to develop and implement an institution-specific trigger tool based on the Institute for Healthcare Improvement medication module trigger tool (IHI MMTT) in order to detect and monitor ADEs.

METHODS

We performed an investigator-driven, single-center study using retrospective and prospective patient data to develop ("development phase") and implement ("implementation phase") an efficient, institution-specific trigger tool based on the IHI MMTT. Complete medical data from 1008 patients hospitalized in 2018 were used in the development phase. ADEs were identified by chart review. The performance of two versions of the tool was assessed by comparing their sensitivities and specificities. Tool A employed only digitally extracted triggers ("e-trigger-tool") while Tool B employed an additional manually extracted trigger. The superior tool - taking efficiency into account - was applied prospectively to 19-22 randomly chosen charts per month for 26 months during the implementation phase.

RESULTS

In the development phase, 189 (19%) patients had ≥1 ADE (total 277 ADEs). The time needed to identify these ADEs was 15 minutes/chart. A total of 203 patients had ≥1 trigger (total 273 triggers - Tool B). The sensitivities and specificities of Tools A and B were 0.41 and 0.86, and 0.43 and 0.86, respectively. Tool A was more time-efficient than Tool B (4 vs 9 minutes/chart) and was therefore used in the implementation phase. During the 26-month implementation phase, 22 patients experienced trigger-identified ADEs and 529 did not. The median number of ADEs per 1000 patient days was 6 (range 0-13). Patients with at least one ADE had a mean hospital stay of 22.3 ± 19.7 days, compared to 8.0 ± 7.6 days for those without an ADE (p = 2.7×10-14).

CONCLUSION

We developed and implemented an e-trigger tool that was specific and moderately sensitive, gave consistent results and required minimal resources.

Spontaneous Reporting of Adverse Drug Reactions in a Pediatric Population in a Tertiary Hospital

The pediatric population is a vulnerable group for adverse drug reactions (ADRs), and data on spontaneous reporting of ADRs in the hospital setting are scarce. We conducted a retrospective analysis of ADRs in pediatric patients spontaneously reported by health care professionals to a Pharmacovigilance Program in a tertiary hospital between 2010 and 2020, and we compared characteristics of ADRs between pediatric age subgroups. From 1787 spontaneously reported ADRs in an 11-year period, 103 (5.85%) were pediatric ADRs. The median age of patients with ADRs was 8.4 years (range 1 day-17 years) and 57.3% were male. The most frequent ADRs reported were nervous system disorders (13.6%) and the most frequently involved drugs were antineoplastics and immunodulators (32.4%). A 59.2% of the ADRs were serious and 55.3% were classified as being type B reactions. Medication errors were involved in 7.8% of the ADRs and 11.9% of the suspected drugs were used off-label. Spontaneous reports of ADRs in newborns, infants, and toddlers were more serious and less often described in the product data sheet than in children and adolescents (p < 0.001 and p = 0.004 respectively). Medication errors were more frequent in patients under two years of age. These results should be interpreted with caution due to under-reporting and biases in spontaneous reporting of ADRs.

PharmVIP: A Web-Based Tool for Pharmacogenomic Variant Analysis and Interpretation

The increasing availability of next generation sequencing (NGS) for personal genomics could promote pharmacogenomics (PGx) discovery and application. However, current tools for analysis and interpretation of pharmacogenomic variants from NGS data are inadequate, as none offer comprehensive analytic functions in a simple, web-based platform. In addition, no tools exist to analyze human leukocyte antigen (HLA) genes for determining potential risks of immune-mediated adverse drug reaction (IM-ADR). We describe PharmVIP, a web-based PGx tool, for one-stop comprehensive analysis and interpretation of genome-wide variants obtained from NGS platforms. PharmVIP comprises three main interpretation modules covering analyses of pharmacogenes involved in pharmacokinetics, pharmacodynamics and IM-ADR. The Guideline module provides Clinical Pharmacogenetics Implementation Consortium (CPIC) drug guideline recommendations based on the translation of genotypic data in genes having guidelines. The HLA module reports HLA genotypes, potential adverse drug reactions, and the relevant drug guidelines. The Pharmacogenes module is employed for prioritizing variants according to variant effect on gene function. Detailed, customizable reports are provided as exportable files and as an interactive web version. PharmVIP is a new integrated NGS workflow for the PGx community to facilitate discovery and clinical application.

The severity of adverse drug reactions and their influencing factors based on the ADR monitoring center of Henan Province

Adverse drug reactions (ADRs) may be a serious public health problem and have received widespread attention in recent years. This study has analyzed the factors leading to the occurrence of serious ADRs (SADRs), determined the factors affecting the prognosis of patients with severe adverse reactions at different levels of medical institutions, and finally made corresponding recommendations for the monitoring, prevention, and treatment of SADRs. We used descriptive analysis and chi-square test to analyze the year, age, gender, proportion of SADRs, and the results of the ADRs in the report. Use the logistic regression to analyze the factors affecting the prognosis of SADRs in different levels of medical institutions. A total of 387 642 people’s 394 037 ADRs were collected from the Henan Provincial Adverse Drug Reaction Monitoring Center from 2016 to 2020. Among them 35 742 cases of serious ADRs (9.1%), 96.1% were eventually relieved or cured, but 39 cases of SADRs caused death. The main causes of death included hemorrhages, organ failure, and allergies. Age, number of medication and illnesses, level of medical institution, history of adverse reactions, and type and method of medication were all factors that affected the severity of ADR. The prognosis of SADRs is worse than normal ADRs. The ADRs in autumn and winter and new adverse reactions are unique risk factors found in this study. The elderly and patients with multiple diseases or taking multiple drugs should pay attention to their adverse reactions. They should be closely observed within a week after taking the medicine. The supervision of patients with a history of allergies and new adverse reactions should be strengthened by primary medical institutions, and in nonprimary medical institutions should paid attention with past medical histories, and use imported drugs and biological agents with caution to ensure the safety and health of patients.

Toward better drug discovery with knowledge graph

Drug discovery is the process of new drug identification. This process is driven by the increasing data from existing chemical libraries and data banks. The knowledge graph is introduced to the domain of drug discovery for imposing an explicit structure to integrate heterogeneous biomedical data. The graph can provide structured relations among multiple entities and unstructured semantic relations associated with entities. In this review, we summarize knowledge graph-based works that implement drug repurposing and adverse drug reaction prediction for drug discovery. As knowledge representation learning is a common way to explore knowledge graphs for prediction problems, we introduce several representative embedding models to provide a comprehensive understanding of knowledge representation learning.

Assessment of Knowledge, Attitude, and Practice in Adverse Drug Reaction Reporting of Healthcare Professionals in Vietnam: A Cross-Sectional Study

Background: Under-reporting is a major issue of ADR spontaneous reporting system. This study assesses the knowledge, attitude, and practice of healthcare professionals in Children’s Hospital in Vietnam and suggests solutions to enhance ADR reporting rate based on findings. Methods: A cross-sectional study was conducted and 397 self-administered structured questionnaires were distributed to all potential HCPs working in surveyed hospital within 2 weeks from June 03 to June 20, 2020. Results: Overall response rate was 97% with 384 responses. A majority answered correctly ADRs’ knowledge apart from form supplier (1.6%) and possible causes (2.6%). The need to focus on patient care (33.3%) and the trivia of reaction (31.5%) reduced HCPs’ attention. About 61.7% reported once in their career, 49.7% had training. Having trained group had numbers of practice significantly higher than their counterparts. Major reason for not reporting was lack of information and instruction. Preferred solutions were regularly training, updating, and collaboration of HCPs in reporting ADR. Conclusion: Healthcare professionals had adequate knowledge, positive attitude, and moderate practice. Training significantly raised the number of practices in reporting ADR. Preferred solutions were regular training, updating, and collaboration of healthcare professionals in ADR reporting.

Drug-Related Deaths in a Tertiary Hospital: Characteristics of Spontaneously Reported Cases and Comparison to Cases Detected from a Retrospective Study

Drug-related deaths (DRDs) are a common cause of hospital death. Pharmacovigilance, either as spontaneous reporting or active surveillance, plays a key role in the detection and reporting of suspected adverse drug reactions (ADRs). We conducted a retrospective analysis of all DRDs spontaneously reported to a pharmacovigilance program of a tertiary hospital, by health care professionals. We compared these results to those of a previous retrospective study conducted in the same hospital from the hospital's mortality registry. From 1460 spontaneous reported ADRs in a 10-year period, 73 (5%) were DRDs. The median age of DRD was 75 years (range 1 month-94) and 60.3% were men. The most frequent DRDs were hemorrhages (41.1%), followed by infections (17.8%). The most frequently involved drugs were anticoagulants and/or antithrombotic (30%), and antineoplastics (26.3%). When comparing both studies, spontaneous reporting detected more type B reactions (p < 0.001) and hospital-acquired DRD (p < 0.001); the number of concomitant drugs was higher (p = 0.0035); and the kind of ADR were different. The combination of several methods is mandatory to detect, assess, understand, and design strategies to prevent ADRs in a hospital setting, to ensure patient safety.

A novel graph attention model for predicting frequencies of drug-side effects from multi-view data

Identifying the frequencies of the drug-side effects is a very important issue in pharmacological studies and drug risk-benefit. However, designing clinical trials to determine the frequencies is usually time consuming and expensive, and most existing methods can only predict the drug-side effect existence or associations, not their frequencies. Inspired by the recent progress of graph neural networks in the recommended system, we develop a novel prediction model for drug-side effect frequencies, using a graph attention network to integrate three different types of features, including the similarity information, known drug-side effect frequency information and word embeddings. In comparison, the few available studies focusing on frequency prediction use only the known drug-side effect frequency scores. One novel approach used in this work first decomposes the feature types in drug-side effect graph to extract different view representation vectors based on three different type features, and then recombines these latent view vectors automatically to obtain unified embeddings for prediction. The proposed method demonstrates high effectiveness in 10-fold cross-validation. The computational results show that the proposed method achieves the best performance in the benchmark dataset, outperforming the state-of-the-art matrix decomposition model. In addition, some ablation experiments and visual analyses are also supplied to illustrate the usefulness of our method for the prediction of the drug-side effect frequencies. The codes of MGPred are available at https://github.com/zhc940702/MGPred and https://zenodo.org/record/4449613.

Barriers to adverse drug reaction reporting in Malaysia: a narrative review based on theoretical domains framework

Objectives

This review aims to determine the common barriers to adverse drug reaction (ADR) reporting in Malaysia based on theoretical domains framework (TDF).

Methods

Three online databases, PubMed (Medline), Scopus and Web of Science, were searched from 2000 to 2020 to identify related quantitative and qualitative studies.

Key findings

Eleven articles were reviewed – nine quantitative and two qualitative studies. Three domains from TDF were identified as the most common: (1) knowledge, (2) skills and (3) environmental context and resources. Lack of awareness of an ADR reporting system, lack of clinical and ADR knowledge and lack of time were identified as the main barriers. Additionally, assumption of healthcare professionals (HCPs) of ADR to be too insignificant or too well known and unavailability of the ADR form were also reported as barriers for reporting an ADR.

Conclusions

The findings from this narrative review could be useful for the policymakers in planning strategies at the national level to improve the reporting rate of ADR in Malaysia. It is necessary to promote and publicize pharmacovigilance activities and to enhance communication and engagement between the Malaysian ADR Advisory Committee and the HCPs and consumers. There is also a need to increase training and continuous education related to ADR and pharmacovigilance system and making ADR reporting compulsory for all HCPs.

Single-step direct drug provocation testing is safe for delabelling selected non-low-risk penicillin allergy labels

BACKGROUND

Penicillin allergy labels are prevalent, and removal of incorrect labels improves patient outcomes and health economics. Labels may be classified as "low-risk" or "non-low-risk," of which the symptoms of the latter chiefly suggest immunoglobulin E-mediated etiology. Traditionally, "non-low-risk" allergy labels are evaluated by penicillin skin testing followed by graded multistep penicillin drug provocation testing (DPT).

OBJECTIVE

To evaluate the safety of assessing "non-low-risk" labels with single-step direct DPT.

METHODS

We consecutively enrolled inpatients and outpatients of a teaching hospital in Sydney, Australia, with penicillin allergy labels requiring penicillin for first-line treatment. Patients were classified as "low-risk" or "non-low-risk" based on the allergy labels. All patients proceeded directly to amoxicillin DPT, unless there was a history of anaphylaxis within 10 years of assessment to a beta-lactam (except for cefazolin) or Gell and Coombs type 2, type 3, or severe type 4 reaction. This was followed by a course of amoxicillin.

RESULTS

A total of 149 patients (41 inpatients, 108 outpatients) were enrolled. No patient was excluded from the study. No patient experienced life-threatening reactions to the protocol. There were 85 patients who reported "non-low-risk" allergy labels. One patient developed generalized pruritus and rash that resolved with standard-dose antihistamines, 2 developed delayed benign maculopapular exanthem, and 3 experienced diarrhea during the course of amoxicillin.

CONCLUSION

In our cohort, direct single-step DPT was safe, with only 6 patients with "non-low-risk" allergy experiencing benign reactions. We hope that further studies can be performed into single-step direct DPT to evaluate "non-low-risk" penicillin allergy labels.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: LNR/16/HAWKE/452.

Adverse reactions to radiopharmaceuticals: liver radiopharmaceuticals

Radiopharmaceuticals are radioactive compounds used in nuclear medicine, consisting of a radioactive moiety and a pharmaceutical part. Radiopharmaceuticals are used for diagnosis (predominantly) and therapy (to a lesser extent). Adverse drug reactions are undesirable, unexpected, often harmful drug responses that occur when the drug is administered in therapeutic doses. Adverse reactions are more minor and rare because radiopharmaceuticals contain small amounts of pharmaceuticals and are administered to the patient in small doses. The main cause of the rare adverse reactions to radiopharmaceuticals is not the radiation itself, but the pharmaceutical part. Examples of adverse reactions frequently encountered in radiopharmaceuticals include nausea, dyspnea, bronchospasm, decreased blood pressure, itching, flushing, hives, chills, cough, bradycardia, muscle cramps, dizziness, fever, infection, shock, and other allergic reactions. 99mTc-iminodiacetic acid derivatives, 99mTc-sulfur colloid, 99mTc-albumin colloid, and 67Ga-gallium citrate compounds are frequently used as liver imaging agents. Adverse reactions seen in liver radiopharmaceuticals are generally nausea, vomiting, erythema, flushing, widespread rash, itching, urticaria, respiratory events, and fever. There are rare reported cases of death. Due to the widespread use of radiopharmaceuticals today, it has become important in adverse reactions. Reporting of adverse events is important, since alerting healthcare professionals to these problems, assessing the magnitude of the problems, improving diagnostic accuracy, determination of treatment methods of adverse reactions will help minimize negative effects. For this reason, it is of great importance to identify and appropriately report the adverse effects seen. It is very important for countries to have the necessary pharmacovigilance systems to report and evaluate these effects.

Prediction of adverse drug reactions using drug convolutional neural networks

Prediction of Adverse Drug Reactions (ADRs) has been an important aspect of Pharmacovigilance because of its impact in the pharma industry. The standard process of introduction of a new drug into a market involves a lot of clinical trials and tests. This is a tedious and time consuming process and also involves a lot of monetary resources. The faster approval of a drug helps the patients who are in need of the drug. The in silico prediction of Adverse Drug Reactions can help speed up the aforementioned process. The challenges involved are lack of negative data present and predicting ADR from just the chemical structure. Although many models are already available to predict ADR, most of the models use biological activities identifiers, chemical and physical properties in addition to chemical structures of the drugs. But for most of the new drugs to be tested, only chemical structures will be available. The performance of the existing models predicting ADR only using chemical structures is not efficient. Therefore, an efficient prediction of ADRs from just the chemical structure has been proposed in this paper. The proposed method involves a separate model for each ADR, making it a binary classification problem. This paper presents a novel CNN model called Drug Convolutional Neural Network (DCNN) to predict ADRs using chemical structures of the drugs. The performance is measured using the metrics such as Accuracy, Recall, Precision, Specificity, F1 score, AUROC and MCC. The results obtained by the proposed DCNN model outperform the competing models on the SIDER4.1 database in terms of all the metrics. A case study has been performed on a COVID-19 recommended drugs, where the proposed model predicted the ADRs that are well aligned with the observations made by medical professionals using conventional methods.

Public awareness in Wales of the UK Yellow Card scheme for reporting suspected adverse drug reactions

We used the HealthWise Wales (HWW) platform to explore public knowledge about the UK Yellow Card scheme (YCS), the spontaneous reporting scheme for suspected adverse drug reactions (ADRs) and whether a short information video could improve awareness. Members of the public in Wales (n = 1606) completed a questionnaire about the YCS, watched the information video and then completed a follow-up questionnaire. Almost half (46.5%) of respondents said they had previously experienced an ADR (>90% of the ADRs involving prescribed medicines). Before the video, 18% of respondents knew how to report an ADR via the YCS and of these, 34% were from allied-health professions. Immediately after watching it, 71% participants reported knowing how to report and 82% reported being confident to report. If this awareness were maintained, such an approach could contribute to improved reporting of suspected ADRs by the public.

Cardiovascular Events in an Inner-City HIV Clinic and Relationship to Abacavir Versus Tenofovir Disoproxil Fumarate-Containing Antiretroviral Regimens

Following cardiovascular events (CVE) among people living with HIV (PLWH) is essential. Abacavir (ABC)'s impact on CVE challenges clinicians. We characterized CVE at our HIV clinic associated with ABC versus tenofovir disoproxil fumarate (TDF). This was a retrospective study of PLWH who started combination antiretroviral therapy with no prior CVE. Patients were evaluated as antiretroviral naive or antiretroviral experienced. Regimens included the following: always-ABC, always-TDF, first-ABC-switched-to-TDF, and first-TDF-switched-to-ABC regimens. Frequencies, rates, and Poisson regression were used to analyze CVE (cardiovascular/cerebrovascular) and were stratified with an a priori cutoff of before or after January 1, 2009. 1,440/2,852 patients were antiretroviral naive; 658 on always-ABC regimens, 1,186 on always-TDF regimens, 737 first-ABC-switched-to-TDF regimens, and 271 first-TDF-switched-to-ABC regimens. Seventy seven CVE occurred overall [16 naive vs. 61 experienced (p < .0001)]. Sixty events were cardiovascular and 17 cerebrovascular (p < .0001). Sixty-nine CVE occurred before 2009 and eight after (p < .0001). There were 5.65 CVE-per-1,000-years [95% confidence interval (CI) 3.23-9.87] in the always-ABC, 1.95 CVE-per-1,000-years (95% CI 1.08-3.51) in the always-TDF, 2.01 CVE-per-1,000-years (95% CI 1.14-3.56) in the ABC-switched-to-TDF, and 1.82 CVE-per-1,000-years (95% CI 0.77-4.30) in TDF-switched-to-ABC (p <.01). Multivariable Poisson regression incidence rate ratios (IRRs) revealed that being on ABC-only (IRR 2.89; 95% CI 2.13-3.94), age (IRR 1.06 per year; 95% CI 1.04-1.07), and smoking (IRR for current 2.81; 95% CI 1.97-3.99; IRR for former 2.49; 95% CI 1.72-3.61) increased risk of CVE. Thus, in our clinic, CVE rates were increased in those on ABC and adds to the body of literature suggesting concern.

Pediatric drug eruptions

Drug eruptions in children are common but in general less studied than their adult counterparts. Aside from having significant impact on the child's health and quality of life, these reactions can limit what medications the patient can receive in the future. Familiarity with pediatric drug eruptions is important for accurate diagnosis and to prevent future recurrence or ineffective therapy. Our current understanding of how drug reactions differ mechanistically between children and adults is poor. There are multiple factors that could be contributing to the differing incidence, presentation, and treatment modalities offered to pediatric versus adult patients. For many of these cutaneous drug reactions, the treatment regime is not standardized, being based primarily on case reports. Although not comprehensive, this review highlights common pediatric drug eruption patterns and discuss diagnostic mimickers. Five cutaneous adverse drug reactions in the pediatric population are presented: morbilliform (exanthematous) eruptions, urticarial eruptions, serum sickness-like reactions, fixed drug eruptions, and DRESS syndrome. Clinical features, diagnostic workup, and management are discussed with an emphasis on the pediatric population.

Mechanistic Studies of Cytochrome P450 3A4 Time-Dependent Inhibition Using Two Cysteine-Targeting Electrophiles

Experiments designed to identify the mechanism of cytochrome P450 inactivation are critical to drug discovery. Small molecules irreversibly inhibit P450 enzymatic activity via two primary mechanisms: apoprotein adduct formation or heme modification. Understanding the interplay between chemical structures of reactive electrophiles and the impact on CYP3A4 structure and function can ultimately provide insights into drug design to minimize P450 inactivation. In a previous study, raloxifene and N-(1-pyrene) iodoacetamide (PIA) alkylated CYP3A4 in vitro; however, only raloxifene influenced enzyme activity. Here, two alkylating agents with cysteine selectivity, PIA and pyrene maleimide (PM), were used to investigate this apparent compound-dependent disconnect between CYP3A4 protein alkylation and activity loss. The compound's effect on 1) enzymatic activity, 2) carbon monoxide (CO) binding capacity, 3) intact heme content, and 4) protein conformation were measured. Results showed that PM had a large time-dependent loss of enzyme activity, whereas PIA did not. The differential effect on enzymatic activity between PM and PIA was mirrored in the CO binding data. Despite disruption of CO binding, neither compound affected the heme concentrations, inferring there was no destruction or alkylation of the heme. Lastly, differential scanning fluorescence showed PM-treated CYP3A4 caused a shift in the onset temperature required to induce protein aggregation, which was not observed for CYP3A4 treated with PIA. In conclusion, alkylation of CYP3A4 apoprotein can have a variable impact on catalytic activity, CO binding, and protein conformation that may be compound-dependent. These results highlight the need for careful interpretation of experimental results aimed at characterizing the nature of P450 enzyme inactivation. SIGNIFICANCE STATEMENT: Understanding the mechanism of CYP3A4 time-dependent inhibition is critical to drug discovery. In this study, we use two cysteine-targeting electrophiles to probe how subtle variation in inhibitor structure may impact the mechanism of CYP3A4 time-dependent inhibition and confound interpretation of traditional diagnostic experiments. Ultimately, this simplified system was used to reveal insights into CYP3A4 biochemical behavior. The insights may have implications that aid in understanding the susceptibility of CYP enzymes to the effects of electrophilic intermediates generated via bioactivation.

Adverse drug reactions

An adverse drug reaction (ADR) is defined as a response to a medicinal product which is noxious and unintended. ADRs are an important cause of morbidity and mortality and increase health costs. The pharmacovigilance systems allow the identification and prevention of the risks associated with use of a drug, especially of recently marketed drugs; they detect signals from data of the global ADR register and also support decisions taken by regulatory agencies in different countries. Only a few drugs are withdrawn from the market, mainly due to hepatotoxicity. Spontaneous notification of ADR is the cheapest, simplest and most used method to recognize new safety drug problems, under-reporting being its main limitation. The future of pharmacovigilance and ADRs will include a higher involvement of patients, doctors, health authorities and pharmaceutical companies, and the use of new technologies.

N-acetyltransferase 2 enzyme genotype-phenotype discordances in both HIV-negative and HIV-positive Nigerians

BACKGROUND

The N-acetyltransferase 2 (NAT2) enzyme has been understudied in Nigerians including genotype-phenotype association studies.

OBJECTIVE

The aim of this study was NAT2 haplotype identification and genotype-phenotype investigations in HIV-positive and HIV-negative Nigerians.

PATIENTS AND METHODS

Phenotypes included self-reported sulphonamide hypersensitivity survey, experimental and computational NAT2 phenotyping. The NAT2 gene was amplified by PCR. Gene sequencing used ABI 3730 and Haploview 4.2 for haplotype reconstruction. Genotype-phenotype analyses used the χ P-value and odds ratio with a 95% confidence interval.

RESULTS

Self-reported sulphonamide hypersensitivity showed a prevalence of 3.1 and 12.4% in HIV-positive and HIV-negative Nigerians, respectively. NAT2 genetic variants 191G>A, 282C>T, 341T>C, 481C>T, 590G>A, 803A>G and 857G>A were not significantly different between both groups (odds ratio=0.87; 95% confidence interval: 0.54-1.38, P=0.55). Nine haplotypes: NAT2*4, NAT2*12A, NAT2*13A, NAT2*5B, NAT2*6A, NAT2*7B, NAT2*5C, NAT2*14B and NAT2*14A had frequencies more than 1%, whereas NAT2*12B had 1.1% in the HIV-positive and 0.4% in the HIV-negative group. Overall, slow acetylator haplotypes made up 68%. The NAT2*12 signature single-nucleotide polymorphism was in high linkage disequilibrium with signature single-nucleotide polymorphism for NAT2*13 (D'=0.97, r=0.61) and NAT2*5 (D'=0.98, r=0.64). Genotype-phenotype association analysis showed haplotypes NAT2*13A, NAT2*5C, NAT2*7B and NAT2*14A to be associated strongly with the slow metabolic phenotype (P=0.002, 0.029, 0.032 and 0.050, respectively). Computational phenotypes were similar, with 30.9, 66 and 3.1% for slow, intermediate and rapid acetylators, respectively, among HIV-positive Nigerians and 31.2, 66.3 and 2.5% among the HIV-negative group. Overall, slow phenotypes made up 31%.

CONCLUSION

NAT2 haplotype frequencies are similar in Nigerians, irrespective of HIV status, but genotype-phenotype discordances exist.

Adverse Drug Reaction (ADR) as a Cause of Hospitalization at a Government Hospital in Saudi Arabia: A Prospective Observational Study

Background:

ADRs represent a substantial burden on health care resources worldwide and are considered as one of the leading causes of morbidity and mortality which significantly affects hospitalization rates. However, ADR related hospital admissions are not well explored in Saudi Arabia.

Objective:

The current study aims to evaluate ADR-related admissions at King Saud Hospital, Unaizah, Qassim, Saudi Arabia.

Methods:

A prospective, observational study was conducted at King Saud Hospital Unaizah. Over a period of 6 months, patients above 12 years of age who visited the Emergency Department (ED) with an ADR were included in this study. The investigators collected patient data by reviewing the patient's medical records and the ED records for admission. The Naranjo algorithm was used to assess the causality of the suspected ADR, and Hartwig’s Severity Assessment Scale was used to assess the severity of the ADR.

Results:

Out of 4739 admissions to the wards, 38 (0.801%) were related to an ADR. The majority of patients were male (52.6%), with a mean age of ± 49.08 years. The total length of hospital stay was 565 days with a mean of ± 14.87 days. The causality assessment shows that 35 (92.1%) cases were probable ADRs, whereas 3 (7.9%) cases were possible ADRs. Moreover, the severity assessment showed that 6 (15.1%) cases were mild, and 27 (71.1%) and 5 (13.2%) cases were moderate and severe, respectively. In regard to the outcome of patients, most patients recovered after the ADR, and 2 ADRs resulted in the death of the patient.

Conclusion:

Our study shows that ADRs as a cause of hospitalization in Qassim population is considerably low. However, ADRs may contribute to morbidity and mortality and result in a considerable financial burden.

Adverse drug reactions in dentistry

An adverse drug reaction (ADR) is an undesirable effect of a drug. ADRs are possible with any medication that is prescribed or administered in the dental office. While most pharmacological agents in use today have favourable drug profiles and are relatively safe, the prudent clinician must be aware of the potential ADRs that can occur and be prepared to manage any complications. Here we review the most commonly used agents in dentistry, namely local anaesthetics, sedatives, analgesics and antibiotics, and their ADRs and management.

Adverse pharmacokinetic interactions between illicit substances and clinical drugs

Adverse pharmacokinetic interactions between illicit substances and clinical drugs are of a significant health concern. Illicit substances are taken by healthy individuals as well as by patients with medical conditions such as mental illnesses, acquired immunodeficiency syndrome, diabetes mellitus and cancer. Many individuals that use illicit substances simultaneously take clinical drugs meant for targeted treatment. This concomitant usage can lead to life-threatening pharmacokinetic interactions between illicit substances and clinical drugs. Optimal levels and activity of drug-metabolizing enzymes and drug-transporters are crucial for metabolism and disposition of illicit substances as well as clinical drugs. However, both illicit substances and clinical drugs can induce changes in the expression and/or activity of drug-metabolizing enzymes and drug-transporters. Consequently, with concomitant usage, illicit substances can adversely influence the therapeutic outcome of coadministered clinical drugs. Likewise, clinical drugs can adversely affect the response of coadministered illicit substances. While the interactions between illicit substances and clinical drugs pose a tremendous health and financial burden, they lack a similar level of attention as drug-drug, food-drug, supplement-drug, herb-drug, disease-drug, or other substance-drug interactions such as alcohol-drug and tobacco-drug interactions. This review highlights the clinical pharmacokinetic interactions between clinical drugs and commonly used illicit substances such as cannabis, cocaine and 3, 4-Methylenedioxymethamphetamine (MDMA). Rigorous efforts are warranted to further understand the underlying mechanisms responsible for these clinical pharmacokinetic interactions. It is also critical to extend the awareness of the life-threatening adverse interactions to both health care professionals and patients.

Probable Enalapril Hepatotoxicity in a 13-Year-Old Male Western Lowland Gorilla: Pharmacologic Risks and Vigilance

A 13-year-old male Western lowland gorilla presented acutely with a precipitous decline in health status from liver disease. Through diagnostic assessment, including serum chemistries and advanced imaging, it was diagnosed with probable hepatotoxicity resulting from its prescribed medication, enalapril. As one of several angiotensin converting enzyme inhibitors (ACE-I) available to zoo veterinarians, enalapril had been administered for treatment of mild ventricular hypertrophy diagnosed during routine examination 2.5 years prior to the presentation. The gorilla made a complete recovery with discontinuation of this medication, and provision of hepatoprotectants. Hepatotoxicity has been documented in humans receiving this product as an adverse drug reaction and is considered both rare and unpredictable in occurrence. In this event, an association was suspected with indulgent consumption of mulberry browse (Morus sp.) offered as nutritional enrichment immediately prior to clinical presentation and had potential impact on hepatic cytochrome P450 metabolism of the enalapril. Although ACE-I are important medications in this taxon due to its predisposition to cardiac disease, this event underscores the need for vigilance on the part of veterinarians and managers whenever pharmaceuticals are administered. Most drugs are modeled in a limited number of species but utilized in a wide variety, and unintended results are possible.

Polypharmacy: a healthcare conundrum with a pharmacogenetic solution

The use of multiple medications is growing at an alarming rate with some reports documenting an average of 12-22 prescriptions being used by individuals ≥50 years of age. The indirect consequences of polypharmacy include exacerbation of drug-drug interactions, adverse drug reactions, increased likelihood of prescribing cascades, chronic dependence, and hospitalizations - all of which have significant health and economic burden. While many practical solutions for reducing polypharmacy have been proposed, they have been met with limited efficacy. This highlights the need for a new systematic approach for fine-tuning dispensing of medications. Pharmacogenetic testing provides an empirical and scientifically rigorous approach for guiding appropriate selection of medicines, with the potential to reduce unnecessary polypharmacy while improving clinical outcomes. The goal of this review article is to provide healthcare providers with an understanding of polypharmacy, its adverse effects on the healthcare system and highlight how pharmacogenetic information can be used to avoid polypharmacy in patients.

Malarone® induced pancreatitis and alopecia in a dog: a case report

BACKGROUND

Malarone® is a drug used for the treatment of malaria in humans. This drug is also particularly effective in the treatment of canine Babesia gibsoni infections. Malarone® is rarely used in dogs, and its adverse effects have not been widely reported. Its mechanism of action is related to the inhibition of cytochrome b and electron transport in the cell. This is the first known report of the development of acute pancreatitis and alopecia in a dog following the administration of Malarone®.

CASE PRESENTATION

A 3-year-old, intact, female Maltese was referred to our clinic with intermittent vomiting and sudden, generalized alopecia. Two months previously, the dog had been prescribed Malarone® for the treatment of a suspected B. gibsoni infection. The dog was evaluated using hematology, radiography, ultrasonography, a PCR for Babesia detection, and a canine pancreatic lipase immunoreactivity (cPLI) assay. The result of the PCR test was negative, whereas the cPLI assay yielded a positive result. Dermatologic examination revealed bacterial infection with hair cycle arrest.

CONCLUSIONS

Based on these findings, drug-induced acute pancreatitis and alopecia with superficial pyoderma were diagnosed. Malarone® may induce severe adverse reactions in dogs. Therefore, careful monitoring for adverse effects is required when using Malarone® in dogs.

Safety of direct drug provocation testing in adults with penicillin allergy and association with health and economic benefits

BACKGROUND

Nonprescription of penicillin-containing antibiotics in patients diagnosed with penicillin allergy is associated with morbidity and mortality. Adverse reactions to penicillins comprise type A and B reactions.

OBJECTIVE

To assess the feasibility of penicillin allergy evaluation without penicillin skin testing (PST) for adult patients with type B reactions and the health and economic benefits of this process.

METHODS

Inpatients at an Australian tertiary hospital between April 1, 2017, and April 30, 2018, with a diagnosis of type B penicillin allergy, requiring a penicillin-containing antibiotic for treatment, were included. All patients underwent clinical history review, PST, and drug provocation testing (DPT).

RESULTS

Seventy-one patients were enrolled. Sixty-three reported a history of type B or unknown adverse reactions. No patients had a history of anaphylaxis requiring intubation or epinephrine within the last 10 years or a history suggesting Gell and Coombs type 2, 3, or 4 (severe) hypersensitivity reaction. Seven did not complete DPT because the treating team used a β-lactam antibiotic other than amoxicillin. Fifty-four of 56 remaining patients (96%) completed 3-day DPT to amoxicillin with no adverse reaction. Two experienced mild cutaneous reactions. Penicillin allergy evaluation was significantly associated with reduced length of stay, reduced hospital expenditure on bed and second-line antibiotics, and reduced readmission rates.

CONCLUSION

Penicillin allergy evaluation with DPT without PST may be feasible for all adult patients with a reported history of type B reactions to penicillins who do not have a history of anaphylaxis within the last 10 years or a type 2, 3, or 4 (severe) hypersensitivity reaction.

Discovering Links Between Side Effects and Drugs Using a Diffusion Based Method

Identifying the unintended effects of drugs (side effects) is a very important issue in pharmacological studies. The laboratory verification of associations between drugs and side effects requires costly, time-intensive research. Thus, an approach to predicting drug side effects based on known side effects, using a computational model, is highly desirable. To provide such a model, we used openly available data resources to model drugs and side effects as a bipartite graph. The drug-drug network is constructed using the word2vec model where the edges between drugs represent the semantic similarity between them. We integrated the bipartite graph and the semantic similarity graph using a matrix factorization method and a diffusion based model. Our results show the effectiveness of this integration by computing weighted (i.e., ranked) predictions of initially unknown links between side effects and drugs.

Factors that facilitate reporting of adverse drug reactions by pharmacists in Saudi Arabia

Objectives: Adverse drug reactions (ADRs) are a pervasive global problem, and its management is integral to patient safety and healthcare quality. Pharmacists play a pivotal role in monitoring and reporting ADRs, which has a direct impact on patient care. The aim of this study was to identify potential factors that facilitate pharmacists in community and hospital settings to report ADRs. Methods: A cross-sectional, online survey using a validated questionnaire was administered to pharmacists working in community and hospital pharmacies in Saudi Arabia. Results: 1,717 community and 153 hospital pharmacists participated in this study. Only 10.2% and 26.8% of community and hospital pharmacists, respectively, admitted ever reporting an ADR. The most reported factors that may facilitate ADRs reporting have included ongoing improvements in therapeutic knowledge about ADRs, attending educational programs with continuous medical education credits, the seriousness of the experienced ADRs and accessibility to patients' medical profile. The impact of peers by seeing colleagues reporting ADRs and ADRs due to herbal or traditional medicine were the least important factors reported by pharmacists. Conclusion: The study identified factors that can effectively address the under-reporting of ADRs by pharmacists. A multi-stakeholder, multi-pronged approach of ADR reporting is needed to develop greater awareness of this issue among pharmacists.

Development of a mortality score to assess risk of adverse drug reactions among hospitalized patients with moderate to severe chronic kidney disease

BACKGROUND

Chronic kidney disease (CKD) is a significant health burden that increases the risk of adverse events. Currently, there is no validated models to predict risk of mortality among CKD patients experienced adverse drug reactions (ADRs) during hospitalization. This study aimed to develop a mortality risk prediction model among hospitalized CKD patients whom experienced ADRs.

METHODS

Patients data with CKD stages 3-5 admitted at various wards were included in the model development. The data collected included demographic characteristics, comorbid conditions, laboratory tests and types of medicines taken. Sequential series of logistic regression models using mortality as the dependent variable were developed. Bootstrapping method was used to evaluate the model's internal validation. Variables odd ratio (OR) of the best model were used to calculate the predictive capacity of the risk scores using the area under the curve (AUC).

RESULTS

The best prediction model included comorbidities heart disease, dyslipidaemia and electrolyte imbalance; psychotic agents; creatinine kinase; number of total medication use; and conservative management (Hosmer and Lemeshow test =0.643). Model performance was relatively modest (R square = 0.399) and AUC which determines the risk score's ability to predict mortality associated with ADRs was 0.789 (95% CI, 0.700-0.878). Creatinine kinase, followed by psychotic agents and electrolyte disorder, was most strongly associated with mortality after ADRs during hospitalization. This model correctly predicts 71.4% of all mortality pertaining to ADRs (sensitivity) and with specificity of 77.3%.

CONCLUSION

Mortality prediction model among hospitalized stages 3 to 5 CKD patients experienced ADR was developed in this study. This prediction model adds new knowledge to the healthcare system despite its modest performance coupled with its high sensitivity and specificity. This tool is clinically useful and effective in identifying potential CKD patients at high risk of ADR-related mortality during hospitalization using routinely performed clinical data.

Knowledge, awareness, perception and reporting of experienced adverse drug reactions among outpatients in Nigeria

Background Higher incidence of adverse drug reactions (ADRs) remain a major cause of morbidity and mortality. Most targeted ADR reporting activities are mainly professional-centered with less attention to patients' knowledge, perception and selfreporting of experienced ADRs. Objectives To comprehensively evaluate patients' knowledge, awareness, perception and reporting of experienced ADRs. Setting Three public healthcare facilities in Ibadan, southwestern Nigeria. Method A questionnaire-guided cross-sectional interview of 1190 consented ambulatory adult patients consecutively recruited from various clinics of the selected hospitals between February and June 2018. The 32-item pretested questionnaire comprised open- and closed-ended questions, as well as open-ended questions with relevant prompts. Data were summarised using descriptive statistics, while Chi square was used to investigate association between relevant categorical variables at p < 0.05. Main outcome measure Knowledge, awareness, perception and reporting of experienced ADRs among patients. Results Response rate was 99.1%. Mean age was 40.6 ± 14.9 years. Forty-nine (4.1%) patients were aware of pharmacovigilance. A total of 964 (81.0%) correctly understood what can be regarded as serious adverse drug reactions (ADRs), 444 (37.3%) had previously experienced ADRs, while 77 (6.5%) experienced reactions with current medication(s). Of this, 64 (83.1%) made a report largely to physician (52; 81.3%). Summarily, reported reactions were more with antimalarials (214; 49.1%), with itching (168; 78.5%) constituting the most frequently occurring reaction. Use of text message (276; 27.2%) and filling of ADR report form (248; 24.4%) were topmost on the list of suggested methods for ADR reporting. There was a significant association between patient's age and awareness of pharmacovigilance (p = 0.015), while educational qualification (p = 0.001) significantly influenced tendency to make a report of experienced ADRs. Conclusion Approximately four percent of patients were aware of pharmacovigilance, while more than three-quarters correctly understood the concept of serious adverse drug reactions. A little above one-quarter had previously experienced one form of reaction or the other, with majority reporting such reactions to physician. Continuous education of stakeholders in pharmacovigilance activities is advocated, while patient's active involvement in spontaneous reporting of ADRs should be carefully considered.

Approaches to managing older people using opiates and their risk of dependence

There is little doubt that opiates have transformed healthcare, particularly in relation to pain management. However, many patients prescribed this type of drug develop problems such as dependency. Although we do not know how many older people have developed such problems due to opiate use we know that some will. It is important for nurses to understand the context in which opiates are used, as well as the specific needs of older people and how to respond to them.