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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 -
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 -
Pharmacovigilance through the development of text mining and natural language processing techniques.Journal of Biomedical Informatics Dec 2015
Topics: Data Mining; Natural Language Processing; Pharmacovigilance
PubMed: 26547007
DOI: 10.1016/j.jbi.2015.11.001 -
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 -
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 -
Sultan Qaboos University Medical Journal May 2021
Topics: Drug-Related Side Effects and Adverse Reactions; Humans; Oman; Pharmacovigilance
PubMed: 34221460
DOI: 10.18295/squmj.2021.21.02.001 -
Therapie 2022Protein kinase inhibitors experienced their advent in the 2000s. Their market introduction made it possible to constitute a class of targeted therapies administered... (Review)
Review
Protein kinase inhibitors experienced their advent in the 2000s. Their market introduction made it possible to constitute a class of targeted therapies administered orally. This name was chosen to mark a break with conventional chemotherapy drugs, but it is important to stress that these are multi-target drugs with complex affinity profiles. Adverse effects can be explained by direct interactions with their targets of interest, chosen for their indications (on-target) but also interactions with other targets (off-target). The adverse effect profiles of these drugs are therefore varied and it is possible to identify common profiles related to inhibitions of common targets. Identification of these targets has improved the global understanding of the pathophysiological mechanisms underlying the onset of adverse drug reactions as well as of the related diseases, and makes it possible to predict the adverse effect profile of new protein kinase inhibitors based on their affinities. In this review, we describe the main adverse drug reactions associated with protein kinase inhibitors, their frequency and their plausible mechanisms of action.
Topics: Adverse Drug Reaction Reporting Systems; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacovigilance; Protein Kinase Inhibitors
PubMed: 34895753
DOI: 10.1016/j.therap.2021.11.004 -
Journal of Clinical Pharmacy and... Nov 2022This study aimed to explore the safety profile of trastuzumab deruxtecan (T-DXd, formerly DS-8201a) using multi-source medical data. (Meta-Analysis)
Meta-Analysis
WHAT IS KNOWN AND OBJECTIVE
This study aimed to explore the safety profile of trastuzumab deruxtecan (T-DXd, formerly DS-8201a) using multi-source medical data.
METHODS
We explored trastuzumab deruxtecan related adverse events (AEs) in clinical trials available in ClinicalTrials.gov and electronic databases (MEDLINE, EMBASE and PubMed) up to July 16, 2022. Meta-analysis was performed by using incidence rate with 95%CIs. In the pharmacovigilance study of FDA Adverse Event Reporting System (FAERS), the reporting odds ratio (ROR) and the medicines and healthcare products regulatory agency (MHRA) methods were used to analyse the real-world AEs (up to June 28, 2022).
RESULTS AND DISCUSSION
A 8 clinical trials enrolled 1457 patients were included. The most common AEs of any grade were gastrointestinal disorders and blood and lymphatic system disorders. The most common AE of grade 3 or higher was neutropenia (21.4%, 95%CI: 14.7%-28.1%, I = 91%). The incidence of interstitial lung disease (ILD) and decreased left ventricular ejection fraction were 10.9% (95%CI: 7.2%-14.5%, I = 82%) and 1.2% (95%CI: 0.7%-2.2%, I = 98%), respectively. A total of 1244 AE reports were identified in the pharmacovigilance study. Gastrointestinal toxicity (ROR = 21.65), myelosuppression (ROR = 36.88), interstitial lung disease (ROR = 50.30), pneumonitis (ROR = 36.59), decreased ejection fraction (ROR = 16.08), and taste disorder (ROR = 14.06) mentioned in the instructions showed strong signals. Also, ascites (ROR = 14.90), lung opacity (ROR = 78.80), pulmonary fibrosis (ROR = 5.59), and increased KL-6 (ROR = 1761.97), which were not mentioned in the instructions, showed strong signals.
WHAT IS NEW AND CONCLUSION
Trastuzumab deruxtecan was well tolerated, and more attention should be paid on ILD as well as decreased ejection fraction.
Topics: Humans; Pharmacovigilance; Stroke Volume; Ventricular Function, Left; Trastuzumab; Lung Diseases, Interstitial
PubMed: 36200429
DOI: 10.1111/jcpt.13777