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Drug Safety Aug 2023Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous... (Review)
Review
INTRODUCTION
Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous reports. Electronic health records (EHRs) provide new opportunities to address limitations of traditional approaches and promote discovery-oriented pharmacovigilance.
METHODS
To evaluate the current state of EHR-based medication safety signal identification, we conducted a scoping literature review of studies aimed at identifying safety signals from routinely collected patient-level EHR data. We extracted information on study design, EHR data elements utilized, analytic methods employed, drugs and outcomes evaluated, and key statistical and data analysis choices.
RESULTS
We identified 81 eligible studies. Disproportionality methods were the predominant analytic approach, followed by data mining and regression. Variability in study design makes direct comparisons difficult. Studies varied widely in terms of data, confounding adjustment, and statistical considerations.
CONCLUSION
Despite broad interest in utilizing EHRs for safety signal identification, current efforts fail to leverage the full breadth and depth of available data or to rigorously control for confounding. The development of best practices and application of common data models would promote the expansion of EHR-based pharmacovigilance.
Topics: Humans; Adverse Drug Reaction Reporting Systems; Electronic Health Records; Pharmacovigilance; Data Mining
PubMed: 37340238
DOI: 10.1007/s40264-023-01325-0 -
BioMed Research International 2021To describe and synthesize aspects of knowledge, attitudes, and practice regarding pharmacovigilance and adverse drug reaction (ADR) reporting and to explore associated...
AIM
To describe and synthesize aspects of knowledge, attitudes, and practice regarding pharmacovigilance and adverse drug reaction (ADR) reporting and to explore associated barriers from a nurse perspective.
METHODS
A systematic review was conducted. Electronic databases including MEDLINE, Embase, Scopus, and Web of Knowledge from January 2010 to October 2020 were searched. Original observational studies that were written in English and which focused on nurses' knowledge, attitudes, practice, and perceived barriers regarding pharmacovigilance and ADR reporting in various healthcare settings were included.
RESULTS
Twenty-three studies published in English from 2010 to 2020 were retrieved during the search process. Overall, in the knowledge domain, the median percentages of nurses who were aware of the definitions of ADRs were 74.1%, while only 26.3% were aware of the adverse drug reaction reporting form. In the attitude domain, 84.6% of nurses believed ADR reporting to be important for patient/medicine safety and 37.1% had a fear of legal liability following ADR reporting. Although 67.1% of nurses encountered ADRs during their professional life, only 21.2% had a history of ADR reporting. In addition, lack of knowledge/training (median: 47.1%) was identified as the most common barrier in ADR reporting from a nursing viewpoint.
CONCLUSION
Despite positive nurse attitudes, knowledge and practice in relation to pharmacovigilance activities and ADR reporting did not occur regularly or often. Improving nurses' knowledge through in-service training and degree-level education and addressing the main barriers of ADR reporting may help to achieve an improved level of reporting.
Topics: Adverse Drug Reaction Reporting Systems; Attitude of Health Personnel; Health Knowledge, Attitudes, Practice; Humans; Nurses; Pharmacovigilance
PubMed: 33937402
DOI: 10.1155/2021/6630404 -
Current Medical Research and Opinion Dec 2015The impending expiry of the patent on a number of leading biologic drugs has led to a surge in the development of 'biosimilar' or 'follow-on' products. However, in... (Review)
Review
The impending expiry of the patent on a number of leading biologic drugs has led to a surge in the development of 'biosimilar' or 'follow-on' products. However, in contrast to generic small-molecule medicines, biosimilars are not identical to their reference products. The differences and complexities surrounding both the molecular structure and the manufacturing process for biologics and biosimilars have resulted in a lack of clarity regarding the terms used in different parts of the world to define various aspects of development and utilization such as regulatory approval, pharmacovigilance, interchangeability and treatment-naivety. This makes quantitative evaluation of biosimilars a great challenge to both the scientific community and regulatory agencies. This manuscript attempts to clarify the terms used and address an important knowledge gap which is currently resulting in an increasing rush to position biosimilars for certain indications and patients in the absence of agreed upon definitions.
Topics: Biosimilar Pharmaceuticals; Drugs, Generic; Humans; Pharmacovigilance
PubMed: 26397731
DOI: 10.1185/03007995.2015.1098601 -
CPT: Pharmacometrics & Systems... May 2022Promising drug development efforts may frequently fail due to unintended adverse reactions. Several methods have been developed to analyze such data, aiming to improve... (Review)
Review
Promising drug development efforts may frequently fail due to unintended adverse reactions. Several methods have been developed to analyze such data, aiming to improve pharmacovigilance and drug safety. In this work, we provide a brief review of key directions to quantitatively analyzing adverse events and explore the potential of augmenting these methods using additional molecular data descriptors. We argue that molecular expansion of adverse event data may provide a path to improving the insights gained through more traditional pharmacovigilance approaches. Examples include the ability to assess statistical relevance with respect to underlying biomolecular mechanisms, the ability to generate plausible causative hypotheses and/or confirmation where possible, the ability to computationally study potential clinical trial designs and/or results, as well as the further provision of advanced features incorporated in innovative methods, such as machine learning. In summary, molecular data expansion provides an elegant way to extend mechanistic modeling, systems pharmacology, and patient-centered approaches for the assessment of drug safety. We anticipate that such advances in real-world data informatics and outcome analytics will help to better inform public health, via the improved ability to prospectively understand and predict various types of drug-induced molecular perturbations and adverse events.
Topics: Adverse Drug Reaction Reporting Systems; Drug-Related Side Effects and Adverse Reactions; Humans; Machine Learning; Marketing; Pharmacovigilance
PubMed: 35143713
DOI: 10.1002/psp4.12765 -
European Journal of Clinical... Sep 2022Adverse Drug Reactions (ADR) add a significant clinical and economic burden to the healthcare system of a country. We present an overview of the different approaches of... (Review)
Review
OBJECTIVE
Adverse Drug Reactions (ADR) add a significant clinical and economic burden to the healthcare system of a country. We present an overview of the different approaches of ADR reporting systems worldwide and their evolution over time.
METHODS
A systematic review of the literature was made based on PubMed and the Cochrane database of systematic reviews. The articles searched for included original articles, WHO and FDA reports and institute of medicine reports. Reporting ADRs is the cornerstone of detecting uncommon ADRs once the drugs are on the market. In many countries, ADR reporting is regulated by national regulatory bodies and various methods are employed to report ADRs. Direct reporting by healthcare professionals has been adopted by many developed and developing countries. With emerging new technologies in the field of medicine, there is a great potential to develop better ADR reporting systems in the countries where they have poor reporting.
CONCLUSION
Development and acquisition of newer technologies to promote ADR monitoring and reporting is a necessity for an effective pharmacovigilance system in a country.
Topics: Adverse Drug Reaction Reporting Systems; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacovigilance; Software; Systematic Reviews as Topic
PubMed: 35788724
DOI: 10.1007/s00228-022-03358-3 -
Journal of the American Medical... Mar 2016This article summarizes past and current data mining activities at the United States Food and Drug Administration (FDA). (Review)
Review
OBJECTIVES
This article summarizes past and current data mining activities at the United States Food and Drug Administration (FDA).
TARGET AUDIENCE
We address data miners in all sectors, anyone interested in the safety of products regulated by the FDA (predominantly medical products, food, veterinary products and nutrition, and tobacco products), and those interested in FDA activities.
SCOPE
Topics include routine and developmental data mining activities, short descriptions of mined FDA data, advantages and challenges of data mining at the FDA, and future directions of data mining at the FDA.
Topics: Data Mining; Pharmacovigilance; Product Surveillance, Postmarketing; United States; United States Food and Drug Administration
PubMed: 26209436
DOI: 10.1093/jamia/ocv063 -
Therapie Sep 2017False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the...
False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the very early preclinical studies to the late post-marketing evaluations. The core concern associated with this false-positive is the lack of replicability of the results. Aside from fraud or misconducts, false-positive is often envisioned from the statistical angle, which considers them as a price to pay for type I error in statistical testing, and its inflation in the context of multiple testing. If envisioning this problematic in the context of pharmacoepidemiology and pharmacovigilance however, that both evaluate drugs in an observational settings, information brought by statistical testing and the significance of such should only be considered as additional to the estimates provided and their confidence interval, in a context where differences have to be a clinically meaningful upon everything, and the results appear robust to the biases likely to have affected the studies. In the following article, we consequently illustrate these biases and their consequences in generating false-positive results, through studies and associations between drug use and health outcomes that have been widely disputed.
Topics: Bias; Drug Evaluation, Preclinical; False Positive Reactions; Humans; Pharmacoepidemiology; Pharmacovigilance; Research Design
PubMed: 28579364
DOI: 10.1016/j.therap.2016.09.020 -
Drug Safety May 2022Artificial intelligence based on machine learning has made large advancements in many fields of science and medicine but its impact on pharmacovigilance is yet unclear. (Review)
Review
INTRODUCTION
Artificial intelligence based on machine learning has made large advancements in many fields of science and medicine but its impact on pharmacovigilance is yet unclear.
OBJECTIVE
The present study conducted a scoping review of the use of artificial intelligence based on machine learning to understand how it is used for pharmacovigilance tasks, characterize differences with other fields, and identify opportunities to improve pharmacovigilance through the use of machine learning.
DESIGN
The PubMed, Embase, Web of Science, and IEEE Xplore databases were searched to identify articles pertaining to the use of machine learning in pharmacovigilance published from the year 2000 to September 2021. After manual screening of 7744 abstracts, a total of 393 papers met the inclusion criteria for further analysis. Extraction of key data on study design, data sources, sample size, and machine learning methodology was performed. Studies with the characteristics of good machine learning practice were defined and manual review focused on identifying studies that fulfilled these criteria and results that showed promise.
RESULTS
The majority of studies (53%) were focused on detecting safety signals using traditional statistical methods. Of the studies that used more recent machine learning methods, 61% used off-the-shelf techniques with minor modifications. Temporal analysis revealed that newer methods such as deep learning have shown increased use in recent years. We found only 42 studies (10%) that reflect current best practices and trends in machine learning. In the subset of 154 papers that focused on data intake and ingestion, 30 (19%) were found to incorporate the same best practices.
CONCLUSION
Advances from artificial intelligence have yet to fully penetrate pharmacovigilance, although recent studies show signs that this may be changing.
Topics: Artificial Intelligence; Humans; Machine Learning; Pharmacovigilance
PubMed: 35579812
DOI: 10.1007/s40264-022-01176-1 -
Current Medical Research and Opinion Dec 2017This review outlines current issues of the pharmacovigilance (PV) system in the Russian Federation, namely the present state of regulatory aspects, regulatory... (Review)
Review
This review outlines current issues of the pharmacovigilance (PV) system in the Russian Federation, namely the present state of regulatory aspects, regulatory requirements in both Russia and the Eurasian Economic Union, and review of causes of under-reporting of adverse drug reactions. Specific attention will be focused on how the system is designed to monitor drug safety functions, reporting and accountability of pharmaceutical products, their manufacturers and medical staff, the role played by regional centers for drug-safety monitoring, and insufficient understanding of the part taken by patients in the system of PV. The prospects of the Russian PV system and its harmonization with global practice will also be discussed.
Topics: Adverse Drug Reaction Reporting Systems; Drug Monitoring; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacovigilance; Russia
PubMed: 28562116
DOI: 10.1080/03007995.2017.1336082 -
The British Journal of Dermatology Nov 2020
Topics: Adverse Drug Reaction Reporting Systems; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmacovigilance
PubMed: 33135791
DOI: 10.1111/bjd.19504