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Applications of RWE for Regulatory Uses
Published in Kelly H. Zou, Lobna A. Salem, Amrit Ray, Real-World Evidence in a Patient-Centric Digital Era, 2023
Eleanor E. Panico, Corinne S. Pillai, Ewa Filipowska, Kelly H. Zou
The Sentinel System Initiative is an infrastructure launched in May 2008 by the Department of Health and Human Service (HHS) to support the Sentinel System and FDA-Catalyst. The Sentinel System was designed to complement existing FDA surveillance capabilities that track AE- reports to further inform medical product safety and allow the Agency to proactively assess the safety of marketed products (About the Food and Drug Administration (FDA) Sentinel Initiative). Currently, the Sentinel System contains data on more than 100 million individuals and exists within a network of 24 collaborating institutions and 16 data partners contributing data to the model (FDA’s Sentinel program). FDA uses multiple data sources to analyse drug and biologic utilization in the market to evaluate if any new safety issues or signals arise that require regulatory action or issuance of a query to the sponsor. The FDA-Catalyst is a platform within the Sentinel infrastructure designed to answer a wide range of questions by supplementing data from the Sentinel System with information from insurance plan members and providers. The Harvard Pilgrim Health Care Institute, as leader of the Sentinel System Coordinating Center, partners with data and academic partners to provide healthcare data and scientific, technical, and organizational expertise for purposes of addressing FDA questions. These partners are defined as Collaborating Institutions.
The US regulation of off-label uses of medicines
Published in Andrea Parziale, The Law of Off-label Uses of Medicines, 2023
In the wake of the Vioxx débacle, Congress moved to address these concerns with the FDA Amendments Act (FDAAA), signed into law by President George W. Bush in 2007. At the outset, the primary aim of the FDAAA was to strengthen the US pharmacovigilance system.29 To this end, the FDAAA first increased the budget of the FDA pharmacovigilance unit and adverse event reporting system, to reduce reliance on spontaneous (and industry) reporting. The FDAAA also allowed the FDA to assess product safety based on information from the immense reservoir of the US electronic clinical records. In this direction, the FDA launched the Sentinel Initiative in 2008, a public–private partnership under FDA’s oversight involving a consortium of patient and health advocacy associations, universities, insurance companies, and the industry. The initiative has the ambition to enable timely decision making based on “near real time” safety information. To this end, it routinely assembles anonymised data on prescriptions and clinical outcomes for millions of US patients.
Using Real-World Evidence to Transform Drug Development: Opportunities and Challenges
Published in Harry Yang, Binbing Yu, Real-World Evidence in Drug Development and Evaluation, 2021
Pharmacovigilance is also an important aspect of product life cycle management. Increasingly, greater attention has been given to data from secondary sources for the detection of a safety signal of rare events (Finkel et al. 2014; Alemayehu and Berger 2016). In May 2008, the FDA launched the Sentinel Initiative, which is a long-term program designed to build and implement RWD network for monitoring the safety of FDA-approved drugs and other medical products (FDA 2010). The systems include data from a wide range of sources including EHR and claims data. In certain instances, the use of RWD for pharmacovigilance was shown to be advantageous in revealing hidden safety signals compared with the traditional methods (Gooden et al. 2013).
How is safety of dermatology drugs assessed: trials, registries, and spontaneous reporting
Published in Expert Opinion on Drug Safety, 2020
Leila Asfour, Zenas Z.N. Yiu, Richard B. Warren
In the United States, the FDA Sentinel initiative has become a core principle of the agency’s evolving safety surveillance[81]. It was initially set up in 2008 as a pilot study aiming to review drug safety signals identified in insurance claims. The Sentinel system derives data from several organizations including academic medical centers, health-care systems, and health insurance companies. They have accessed electronic health-care data of nearly 100 million patients[82]. Their data have influenced the Center for Drug Evaluation and Research, minimizing the need for post-marketing studies on nine potential safety concerns regarding five products including ustekinumab and concern regarding serious infections[83].
The potential role of big data in the detection of adverse drug reactions
Published in Expert Review of Clinical Pharmacology, 2020
Janet Sultana, Gianluca Trifirò
Healthcare claims databases contain information on drug dispensing and hospitalization, as well as other billable health-care services such as diagnostic tests. EMRs contain information on drug prescription and diagnosis data that are recorded during a physician’s routine clinical activity. Both types of data have been widely used to investigate drug safety, whether through traditional epidemiologic study designs such as cohort studies and case-controls, or through artificial intelligence (AI) approaches including natural language processing (NLP), which are considered to be emerging or innovative in the field of pharmacovigilance. NLP has been used for signal detection, for example, to parse free-text in discharge summaries and clinical notes in order to identify associations between drugs mentioned and mentions of events that could potentially be ADRs [7]. There is an increasing use of several healthcare claims database and EMRs together in distributed database networks, which are closer to the original definition of big data, due to the significantly increased volume and variety of data [8]. These networks capture information on populations of an unprecedented size, allowing the rapid strengthening of potential signals, identified primarily in SRD, as done in the Sentinel Initiative and CNODES [9]. In addition, several projects funded by European Union research grants have seen the creation of database networks to address specific safety issues of public health concern [10]. While such networks are mostly used for signal validation, the value of database networks, such as EU-ADR [11] and more recently, the Sentinel Initiative [12], for signal detection, has also been explored. The main findings of these studies are that large distributed database networks may play an important role in complementing, but never replacing, spontaneous reporting systems for signal detection, particularly concerning adverse events with a high background incidence in general population, which are multifactorial and hence are unlikely to be flagged in spontaneous reports. Acute myocardial infarction is an example of such an event [13].