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Clinical Therapeutics Dec 2018Pharmacovigilance (PV) is a relatively new discipline in the pharmaceutical industry. Having undergone rapid growth over the past 2 decades, PV now touches many other... (Review)
Review
PURPOSE
Pharmacovigilance (PV) is a relatively new discipline in the pharmaceutical industry. Having undergone rapid growth over the past 2 decades, PV now touches many other disciplines in the research and development enterprise. With its growth has come a heightened awareness and interest in the medical community about the roles that PV plays. This article provides insights into the background and inner workings of PV.
METHODS
This narrative review covers the core PV activities and other major areas of the pharmaceutical enterprise in which PV makes significant contributions.
FINDINGS
Drug safety monitoring activities were organized by the US Food and Drug Administration and academic medical centers in the early 1950s in response to growing concern over the occurrence of aplastic anemia and other blood dyscrasias associated with the use of chloramphenicol. This experience was codified in the 1962 Kefauver-Harris Amendments to the Federal Food, Drug and Cosmetic Act as adverse event evaluation and reporting requirements. The ensuing decades have seen the development of core PV functions for pharmaceutical companies: case management, signal management, and benefit-risk management. A broader scope of PV has developed to include the following major activities: support of patient safety during the conduct of clinical trials through assuring proper use of informed consent and institutional review boards (ethics committees); selection of the first safe dose for use in humans, based on pharmacologic data obtained in animal studies; development of the safety profile for proper use of a new molecular entity and appropriate communication of that information to the range of relevant stakeholders; attendance to surveillance activities through a set of signal management processes; monitoring the manufactured product itself through collaborative activities with manufacturing professionals; management of benefit-risk to assure appropriate use in medical care after marketing; and maintenance of inspection readiness as a corporate cultural process.
IMPLICATIONS
The extent and pace of change promise to accelerate with the integration of biomedical informatics, analytics, artificial intelligence, and machine learning. This progress has implications for the development of the next generation of PV professionals who will need to be trained in entirely new skill sets to lead continued improvements in the safe use of pharmaceuticals.
Topics: Animals; Drug Industry; Humans; Patient Safety; Pharmacovigilance
PubMed: 30126707
DOI: 10.1016/j.clinthera.2018.07.012 -
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 -
Pharmaceutical Medicine Oct 2022Artificial intelligence through machine learning uses algorithms and prior learnings to make predictions. Recently, there has been interest to include more artificial...
INTRODUCTION
Artificial intelligence through machine learning uses algorithms and prior learnings to make predictions. Recently, there has been interest to include more artificial intelligence in pharmacovigilance of products already in the market and pharmaceuticals in development.
OBJECTIVE
The aim of this study was to identify and describe the uses of artificial intelligence in pharmacovigilance through a systematic literature review.
METHODS
Embase and MEDLINE database searches were conducted for articles published from January 1, 2015 to July 9, 2021 using search terms such as 'pharmacovigilance,' 'patient safety,' 'artificial intelligence,' and 'machine learning' in the title or abstract. Scientific articles that contained information on the use of artificial intelligence in all modalities of patient safety or pharmacovigilance were reviewed and synthesized using a pre-specified data extraction template. Articles with incomplete information and letters to editor, notes, and commentaries were excluded.
RESULTS
Sixty-six articles were identified for evaluation. Most relevant articles on artificial intelligence focused on machine learning, and it was used in patient safety in the identification of adverse drug events (ADEs) and adverse drug reactions (ADRs) (57.6%), processing safety reports (21.2%), extraction of drug-drug interactions (7.6%), identification of populations at high risk for drug toxicity or guidance for personalized care (7.6%), prediction of side effects (3.0%), simulation of clinical trials (1.5%), and integration of prediction uncertainties into diagnostic classifiers to increase patient safety (1.5%). Artificial intelligence has been used to identify safety signals through automated processes and training with machine learning models; however, the findings may not be generalizable given that there were different types of data included in each source.
CONCLUSION
Artificial intelligence allows for the processing and analysis of large amounts of data and can be applied to various disease states. The automation and machine learning models can optimize pharmacovigilance processes and provide a more efficient way to analyze information relevant to safety, although more research is needed to identify if this optimization has an impact on the quality of safety analyses. It is expected that its use will increase in the near future, particularly with its role in the prediction of side effects and ADRs.
Topics: Artificial Intelligence; Drug-Related Side Effects and Adverse Reactions; Humans; Machine Learning; Pharmaceutical Preparations; Pharmacovigilance
PubMed: 35904529
DOI: 10.1007/s40290-022-00441-z -
Sante Publique (Vandoeuvre-les-Nancy,... 2023This article focuses on the hierarchical structure of users of a synthetic progestin, Homodeor and its effects on the construction of a pharmacovigilance plan by a...
This article focuses on the hierarchical structure of users of a synthetic progestin, Homodeor and its effects on the construction of a pharmacovigilance plan by a French health agency, at a time when an institutional desire is being expressed to work more closely with all patient associations. This case study is mainly on a qualitative survey led by interviewing agents, health professionals and user representatives, which aimed to explore the relationships and representations developed around this issue. Despite the diversity of progestin use, a hierarchy between the different user groups was gradually established. The pharmacovigilance measures were designed for a specific group of patients, presented as the ideal users of the drug. The case of Homodeor makes it possible to highlight the dynamics of competition between groups of patients, and more broadly, the challenges of taking minority groups into account in health policies in the light of their development context.
Topics: Humans; Progestins; Health Personnel; Surveys and Questionnaires; Health Facilities; Pharmacovigilance
PubMed: 37336747
DOI: 10.3917/spub.hs2.0049 -
Drug Safety Apr 2016The world changes continuously and pharmacovigilance as a new discipline also must change. There are new fields opening with novel challenges whilst we are still...
The world changes continuously and pharmacovigilance as a new discipline also must change. There are new fields opening with novel challenges whilst we are still perfecting ways to manage and improve the basic challenges such as inadequate data for decision making and under-reporting. Traditional medicines, vaccines, poisoning and medication error are all aspects of the safety of medicines that we have monitored for decades, though without perhaps paying enough attention to their special aspects. There are many new stakeholders taking serious interest in pharmacovigilance outside the regulatory sphere and they often focus on improving individual patient care, rather than the more traditional concentration on broad public health. The same stakeholders are also drawing attention to other iatrogenic outcomes that should be recognised, evaluated and their outcomes compared and contrasted with medication, such as harm from medical devices. The vigilance methods used for medication are very much applicable to all these new fields, though more and different expertise will be needed to evaluate outcomes.
Topics: Drug Monitoring; Humans; International Cooperation; Medication Errors; Pharmacovigilance; Poisoning; Treatment Outcome
PubMed: 26692393
DOI: 10.1007/s40264-015-0373-x -
Therapie 2022
Topics: Adverse Drug Reaction Reporting Systems; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacovigilance
PubMed: 35581019
DOI: 10.1016/j.therap.2022.03.001 -
Therapie 2023
Topics: Humans; Artificial Intelligence; Automation; Drug-Related Side Effects and Adverse Reactions; Pharmacovigilance
PubMed: 36577617
DOI: 10.1016/j.therap.2022.11.003 -
Expert Opinion on Drug Safety 2023Artificial intelligence (AI) based tools offer new opportunities for pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored to... (Review)
Review
INTRODUCTION
Artificial intelligence (AI) based tools offer new opportunities for pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored to preserve and strengthen medical and pharmacological expertise in drug safety.
AREAS COVERED
This work aims to describe PV tasks in which the contribution of AI and intelligent automation (IA) tools is required, in the context of a continuous increase of spontaneous reporting cases and regulatory tasks. A narrative review with expert selection of pertinent references was performed through Medline. Two areas were covered, management of spontaneous reporting cases and signal detection.
PERSPECTIVE
The use of AI and IA tools will assist a large spectrum of PV activities, both in public and private PV systems, in particular for tasks of low added value (e.g. initial quality check, verification of essential regulatory information, search for duplicates). Testing, validating, and integrating these tools in the PV routine are the actual challenges for modern PV systems, to guarantee high-quality standards in terms of case management and signal detection.
Topics: Humans; Artificial Intelligence; Pharmacovigilance; Drug-Related Side Effects and Adverse Reactions
PubMed: 37435796
DOI: 10.1080/14740338.2023.2227091 -
Revue Medicale Suisse Jan 2019The main pharmacovigilance updates in 2018 are reviewed. Quinolones : no longer recommended for mild or moderately severe infections. Denosumab in cancer patients:... (Review)
Review
The main pharmacovigilance updates in 2018 are reviewed. Quinolones : no longer recommended for mild or moderately severe infections. Denosumab in cancer patients: increased risk of new primary malignancies. Cyproterone : increased risk of meningioma at high dose. Saccharomyces boulardii : risk of fungemia in frail patients. Ulipristal : risk of hepatotoxicity. Daclizumab : early withdrawal from the market as risks clearly outweigh benefits. Interactions between boosted antiretrovirals and anti-P2Y12 : prasugrel appears as the best option. Neural tube defects in babies born to women treated with dolutegravir : a signal to investigate. Cobicistat-boosted antiretrovirals exposure is decreased during pregnancy. Fourth generation pills containing drospirenone : a greater propensity to prolong the QT interval than 2nd generation pills.
Topics: Drug-Related Side Effects and Adverse Reactions; Female; Humans; Pharmacovigilance; Pregnancy
PubMed: 30629378
DOI: No ID Found -
Therapie 2021
Topics: France; Humans; Nitrous Oxide; Pharmacovigilance; Substance-Related Disorders
PubMed: 32005483
DOI: 10.1016/j.therap.2020.01.001