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Clinical Medicine (London, England) Oct 2016Adverse drug reactions (ADRs) remain a challenge in modern healthcare, particularly given the increasing complexity of therapeutics, an ageing population and rising... (Review)
Review
Adverse drug reactions (ADRs) remain a challenge in modern healthcare, particularly given the increasing complexity of therapeutics, an ageing population and rising multimorbidity. This article summarises some of the key facts about ADRs and explores aspects relating to their prevention, diagnosis, reporting and management in current clinical practice.
Topics: Adverse Drug Reaction Reporting Systems; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacovigilance
PubMed: 27697815
DOI: 10.7861/clinmedicine.16-5-481 -
Trends in Pharmacological Sciences Sep 2019Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and must be closely... (Review)
Review
Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and must be closely monitored. Pharmacovigilance is the field of science that monitors, detects, and prevents adverse drug reactions (ADRs). Safety efforts begin during the development process, using in vivo and in vitro studies, continue through clinical trials, and extend to postmarketing surveillance of ADRs in real-world populations. Future toxicity and safety challenges, including increased polypharmacy and patient diversity, stress the limits of these traditional tools. Massive amounts of newly available data present an opportunity for using artificial intelligence (AI) and machine learning to improve drug safety science. Here, we explore recent advances as applied to preclinical drug safety and postmarketing surveillance with a specific focus on machine and deep learning (DL) approaches.
Topics: Adverse Drug Reaction Reporting Systems; Animals; Artificial Intelligence; Drug Evaluation, Preclinical; Drug-Related Side Effects and Adverse Reactions; Humans; Machine Learning; Pharmacovigilance; Product Surveillance, Postmarketing; Quantitative Structure-Activity Relationship; Toxicity Tests
PubMed: 31383376
DOI: 10.1016/j.tips.2019.07.005 -
BMC Psychiatry Jun 2020Antidepressants-induced movement disorders are rare and imperfectly known adverse drug reactions. The risk may differ between different antidepressants and... (Observational Study)
Observational Study
BACKGROUND
Antidepressants-induced movement disorders are rare and imperfectly known adverse drug reactions. The risk may differ between different antidepressants and antidepressants' classes. The objective of this study was to assess the putative association of each antidepressant and antidepressants' classes with movement disorders.
METHODS
Using VigiBase®, the WHO Pharmacovigilance database, disproportionality of movement disorders' reporting was assessed among adverse drug reactions related to any antidepressant, from January 1967 to February 2017, through a case/non-case design. The association between nine subtypes of movement disorders (akathisia, bruxism, dystonia, myoclonus, parkinsonism, restless legs syndrome, tardive dyskinesia, tics, tremor) and antidepressants was estimated through the calculation first of crude Reporting Odds Ratio (ROR), then adjusted ROR on four potential confounding factors: age, sex, drugs described as able to induce movement disorders, and drugs used to treat movement disorders.
RESULTS
Out of the 14,270,446 reports included in VigiBase®, 1,027,405 (7.2%) contained at least one antidepressant, among whom 29,253 (2.8%) reported movement disorders. The female/male sex ratio was 2.15 and the mean age 50.9 ± 18.0 years. We found a significant increased ROR for antidepressants in general for all subtypes of movement disorders, with the highest association with bruxism (ROR 10.37, 95% CI 9.62-11.17) and the lowest with tics (ROR 1.49, 95% CI 1.38-1.60). When comparing each of the classes of antidepressants with the others, a significant association was observed for all subtypes of movement disorders except restless legs syndrome with serotonin reuptake inhibitors (SRIs) only. Among antidepressants, mirtazapine, vortioxetine, amoxapine, phenelzine, tryptophan and fluvoxamine were associated with the highest level to movement disorders and citalopram, paroxetine, duloxetine and mirtazapine were the most frequently associated with movement disorders. An association was also found with eight other antidepressants.
CONCLUSIONS
A potential harmful association was found between movement disorders and use of the antidepressants mirtazapine, vortioxetine, amoxapine, phenelzine, tryptophan, fluvoxamine, citalopram, paroxetine, duloxetine, bupropion, clomipramine, escitalopram, fluoxetine, mianserin, sertraline, venlafaxine and vilazodone. Clinicians should beware of these adverse effects and monitor early warning signs carefully. However, this observational study must be interpreted as an exploratory analysis, and these results should be refined by future epidemiological studies.
Topics: Adult; Aged; Antidepressive Agents; Female; Humans; Male; Middle Aged; Movement Disorders; Pharmacovigilance; Selective Serotonin Reuptake Inhibitors; Sertraline
PubMed: 32546134
DOI: 10.1186/s12888-020-02711-z -
Drug Safety Aug 2023
Topics: Humans; Pharmacovigilance; Artificial Intelligence
PubMed: 37306853
DOI: 10.1007/s40264-023-01315-2 -
Frontiers in Public Health 2022Semaglutide was approved for treatment of type 2 diabetes mellitus (T2DM) and chronic weight management in obesity or overweight adults. However, real-world data...
BACKGROUND
Semaglutide was approved for treatment of type 2 diabetes mellitus (T2DM) and chronic weight management in obesity or overweight adults. However, real-world data regarding its long-term gastrointestinal safety and tolerability in large sample population are incomplete. We evaluated semaglutide-associated gastrointestinal safety signals by data mining of the FDA pharmacovigilance database.
METHODS
Reporting odds ratio (ROR) was employed to quantify the signals of semaglutide-related gastrointestinal adverse events (AEs) from 2018 to 2022. Serious and non-serious cases were compared by Mann-Whitney test or Chi-squared (χ) test, and signals were prioritized using a rating scale.
RESULTS
We identified 5,442 cases of semaglutide-associated gastrointestinal AEs, with 45 signals detected, ranging from a ROR of 1.01 (hypoaesthesia oral) to 42.03 (eructation), among which 17 AEs were identified as new and unexpected signals. Patient age ( < 0.001) and body weight ( = 0.006) rather than sex ( = 0.251) might be associated with an increased risk of gastrointestinal AEs severity. Notably, the association between semaglutide and gastrointestinal disorders remained when stratified by age, body weight, sex and reporter type. One strong, 22 moderate and 22 weak clinical priority signals were defined. The median time-to-onset (TTO) for strong clinical priority signal was 23 days, while for moderate and weak, they were 6 and 7 days, respectively. All of the disproportionality signals had early failure type features, suggesting that the risk of gastrointestinal AEs occurrence gradually decreased over time.
CONCLUSION
Our study provided a deeper and broader understanding of semaglutide's gastrointestinal safety profiles, which would help healthcare professionals to mitigate the risk of gastrointestinal AEs in clinical practice.
Topics: Adult; Humans; Pharmacovigilance; Adverse Drug Reaction Reporting Systems; Diabetes Mellitus, Type 2; Drug-Related Side Effects and Adverse Reactions; Body Weight
PubMed: 36339230
DOI: 10.3389/fpubh.2022.996179 -
Frontiers in Immunology 2023Risankizumab, a humanized IgG1 monoclonal antibody that selectively inhibits IL-23, is currently approved for the treatment of moderate-to-severe plaque psoriasis and...
BACKGROUND
Risankizumab, a humanized IgG1 monoclonal antibody that selectively inhibits IL-23, is currently approved for the treatment of moderate-to-severe plaque psoriasis and Crohn's disease. The real-world safety study of risankizumab in a large- sample population is currently lacking. The aim of this study was to evaluate risankizumab-associated adverse events (AEs) and characterize the clinical priority through the data mining of the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS).
METHODS
Disproportionality analyses were performed by calculating the reporting odds ratios (RORs), deemed significant when the lower limit of the 95% confidence interval was greater than 1, to quantify the signals of risankizumab-related AEs from the second quarter (Q2) of 2019 to 2022 Q3. Serious and non-serious cases were compared, and signals were prioritized using a rating scale.
RESULTS
Risankizumab was recorded in 10,235 reports, with 161 AEs associated with significant disproportionality. Of note, 37 PTs in at least 30 cases were classified as unexpected AEs, which were uncovered in the drug label, such as myocardial infarction, cataract, pancreatitis, diabetes mellitus, stress, and nephrolithiasis. 74.68%, 25.32%, and 0% PTs were graded as weak, moderate, and strong clinical priorities, respectively. A total of 48 risankizumab-related AEs such as pneumonia, cerebrovascular accident, cataract, loss of consciousness, cardiac disorder, hepatic cirrhosis, and thrombosis, were more likely to be reported as serious AEs. The median TTO of moderate and weak signals related to risankizumab was 115 (IQR 16.75-305) and 124 (IQR 29-301) days, respectively. All of the disproportionality signals had early failure type features, indicating that risankizumab-associated AEs gradually decreased over time.
CONCLUSION
Our study found potential new AE signals and provided valuable evidence for clinicians to mitigate the risk of risankizumab-associated AEs based on an extensive analysis of a large-scale postmarketing international safety database.
Topics: United States; Humans; Pharmacovigilance; Adverse Drug Reaction Reporting Systems; United States Food and Drug Administration; Drug-Related Side Effects and Adverse Reactions; Antibodies, Monoclonal; Antibodies, Monoclonal, Humanized
PubMed: 37256136
DOI: 10.3389/fimmu.2023.1169735 -
Drug Safety May 2022Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting... (Review)
Review
Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting in many adverse drug events being underreported or inaccurately reported. One challenge includes having access to large data sets from various sources including electronic health records and wearable medical devices. Artificial intelligence, including machine learning methods, such as natural language processing and deep learning, can detect and extract information about adverse drug events, thus automating the pharmacovigilance process and improving the surveillance of known and documented adverse drug events. In addition, with the increased demand for telehealth services, for managing both acute and chronic diseases, artificial intelligence methods can play a role in detecting and preventing adverse drug events. In this review, we discuss two use cases of how artificial intelligence methods may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.
Topics: Adverse Drug Reaction Reporting Systems; Artificial Intelligence; Drug-Related Side Effects and Adverse Reactions; Humans; Natural Language Processing; Pharmacovigilance; Telemedicine
PubMed: 35579810
DOI: 10.1007/s40264-022-01172-5 -
British Journal of Clinical Pharmacology Feb 2023Drug-related adverse reactions are among the main reasons for harm to patients under care worldwide and even their deaths. The pharmacovigilance system has been proven... (Review)
Review
Drug-related adverse reactions are among the main reasons for harm to patients under care worldwide and even their deaths. The pharmacovigilance system has been proven to be an effective method of avoiding or alleviating such adverse events. In 2019, after two decades of implementation of the drug-related adverse reaction reporting system, China formally implemented a pharmacovigilance system with the Pharmacovigilance Quality Management Standards and a series of supporting technical documents created to improve the safety of medication given to patients. China's pharmacovigilance system has faced many problems and challenges during its implementation. This spontaneous reporting system is the main source of data for China's medication vigilance activities, but it has not provided sufficiently powerful evidence for regulatory decision-making. In conformity with the health-centred drug regulatory concept, the Chinese government has accelerated the speed of examination and approval of urgently needed clinical drugs and orphan drugs along with the requirement to improve the safety supervision of these drugs after their listing. China's marketing authorization holders (MAHs) must strengthen their pharmacovigilance capabilities as the primary responsible departments for drug safety. Chinese medical schools generally lack professional courses on pharmacovigilance. The regulatory authorities have recognized such problems and have made efforts to improve the professional capacity of pharmacovigilance personnel and to strengthen cooperation with stakeholders through the implementation of an action plan of medication surveillance and the establishment of a patient-based adverse events reporting system and active surveillance systems, which will help China bridge the gap to bring its pharmacovigilance practice up to standards.
Topics: Humans; Pharmacovigilance; Adverse Drug Reaction Reporting Systems; Drug and Narcotic Control; China; Drug-Related Side Effects and Adverse Reactions
PubMed: 35165914
DOI: 10.1111/bcp.15277 -
Drug Safety May 2022With the rapid development of artificial intelligence (AI) technologies, and the large amount of pharmacovigilance-related data stored in an electronic manner,... (Review)
Review
With the rapid development of artificial intelligence (AI) technologies, and the large amount of pharmacovigilance-related data stored in an electronic manner, data-driven automatic methods need to be urgently applied to all aspects of pharmacovigilance to assist healthcare professionals. However, the quantity and quality of data directly affect the performance of AI, and there are particular challenges to implementing AI in limited-resource settings. Analyzing challenges and solutions for AI-based pharmacovigilance in resource-limited settings can improve pharmacovigilance frameworks and capabilities in these settings. In this review, we summarize the challenges into four categories: establishing a database for an AI-based pharmacovigilance system, lack of human resources, weak AI technology and insufficient government support. This study also discusses possible solutions and future perspectives on AI-based pharmacovigilance in resource-limited settings.
Topics: Artificial Intelligence; Databases, Factual; Health Personnel; Humans; Pharmacovigilance; Technology
PubMed: 35579814
DOI: 10.1007/s40264-022-01170-7 -
International Journal of Health Policy... Jul 2022Evaluating a pharmacovigilance system helps identify its deficiencies and could facilitate measures to remedy and improve the quantity and quality of adverse drug...
BACKGROUND
Evaluating a pharmacovigilance system helps identify its deficiencies and could facilitate measures to remedy and improve the quantity and quality of adverse drug reaction (ADR) reports and other opportunities for pharmacovigilance systems strengthening. This study aimed to evaluate the status of pharmacovigilance in Iran using the World Health Organization (WHO) pharmacovigilance indicators with the prospect of identifying the gaps and areas for improvement.
METHODS
This study was conducted in 2 parts. The first part included a secondary analysis of the national data obtained from the Iranian National Pharmacovigilance Center (PVC) using a structured data collection form based on WHO core pharmacovigilance indicators. In the second part, a 3-month prospective study was carried out to investigate 2 outcome indicators, ie, length of stay and costs of medicine-related hospitalization in all patients of 2 main referral hospitals in the southeast and north of Iran.
RESULTS
Iran has a PVC with national policy, trained staff, and a statutory budget. In 2017, the number of ADR reports was 15.0 per 100 000 population, and 262 signals were detected during the preceding 5 years. The average length of stay and costs of medicine-related hospitalization were 5 days and US$817.2 in Afzalipour hospital and 6.6 days and US$306.7 in Razi hospital, respectively. The status of pharmacovigilance in the Iranian public health programs (PHPs) is unknown, and most of the indicators could not be assessed.
CONCLUSION
A robust pharmacovigilance system is a pivotal part of the overall medicines regulatory system. The Iranian pharmacovigilance system has relatively the proper structural condition. Though the underreporting of ADRs, especially medicine-related deaths, is an important issue, and some indicators' status was unclear. The Iranian pharmacovigilance program requires a higher prioritization, particularly in the PHPs, a greater allocation of resources, and cross-sectoral cooperation to bolster and achieve the pharmacovigilance objectives.
Topics: Humans; Iran; Pharmacovigilance; Prospective Studies; Adverse Drug Reaction Reporting Systems; Drug-Related Side Effects and Adverse Reactions
PubMed: 33590736
DOI: 10.34172/ijhpm.2020.243