Introduction: Enactment of the Food and Drug Administration Amendments Act of 2007 (FDAAA) authorized the FDA to require manufacturers to submit Risk Evaluation and Mitigation Strategy (REMS) when it was deemed necessary to ensure that a drug's benefit outweigh its risk. REMS apply to new drug applications (NDAs), abbreviated new drug applications (ANDAs) and biologics license applications (BLAs). The objective of this review is to describe the impact of REMS requirements on the pharmaceutical industry.
Areas Covered: Articles were identified in MEDLINE searches through October 11, 2011, using the MeSH terms and keywords pharmaceutical industry, risk management, United States Food and Drug Administration, REMS, ETASU, and Medication Guide in various combinations.
Expert Opinion: The new powers ascribed to the FDA are notable, as they add enforceability to safety strategies that were not part of FDA's prior risk management tools, risk minimization action plans (RiskMAPs). Failure to comply with REMS can lead to financial penalties up to $10 million, and a drug could be deemed misbranded if the REMS is not followed. The new approach to risk management via FDAAA has elevated the rigor with which manufacturers must fulfill postmarketing safety commitments.
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http://dx.doi.org/10.1517/14740338.2012.650689 | DOI Listing |
Pilot Feasibility Stud
January 2025
Advocate Christ Medical Center, Advocate Health, Oak Lawn, IL, USA.
Background: Hypertension is the leading risk factor for cardiovascular disease (CVD). Despite advances in blood pressure management, significant racial and ethnic disparities persist, resulting in higher risks of stroke, heart disease, and mortality among non-White populations. Self-measured blood pressure (SMBP) monitoring, also known as home blood pressure monitoring, has shown promise in improving blood pressure control, especially when combined with feedback from healthcare providers.
View Article and Find Full Text PDFTrop Med Health
January 2025
Department of Community Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Background: Neurobrucellosis, a serious central nervous system infection caused by Brucella species, presents significant challenges due to its diverse clinical manifestations and the risk of long-term complications and poor outcomes. Identifying predictors of adverse outcomes is critical for improving patient management and overall prognosis.
Objectives: This study aimed to evaluate the long-term morbidity and mortality associated with neurobrucellosis and to identify key predictors of adverse outcomes.
BMC Med Inform Decis Mak
January 2025
Kenya Medical Research Institute- Center for Global Health Research (KEMRI-CGHR), P.O Box 1578-40100, Kisumu, Kenya.
Background: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machine learning (ML) to derive and validate a predictive model for LDD among children presenting with diarrhea to health facilities.
Methods: LDD was defined as a diarrhea episode lasting ≥ 7 days.
Genome-wide association studies (GWAS) have identified genetic variants robustly associated with asthma. A potential near-term clinical application is to calculate polygenic risk score (PRS) to improve disease risk prediction. The value of PRS, as part of numerous multi-source variables used to define asthma, remains unclear.
View Article and Find Full Text PDFBMC Med Ethics
January 2025
Faculty of Law, University of Montreal, Ch de la Tour, Montreal, QC, H3T 1J7, Canada.
Background: Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals' lack of training in how to use it, the paper summarizes how to approach the challenges of AI from an ethical and legal perspective. It concludes with suggestions for improvements to help healthcare professionals better navigate the AI wave.
Methods: We analyzed the literature that specifically discusses ethics and law related to the development and implementation of AI in healthcare as well as relevant normative documents that pertain to both ethical and legal issues.
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