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Regulatory oversight of companion apps

Regulatory Oversight of Companion Apps: Where Do They Stand? 

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Imagine sipping your morning coffee while an app effortlessly syncs with your glucose monitor. These are companion apps, digital tools that extend the functionality of medical devices. But with innovation comes responsibility. So, who ensures these apps are safe, effective, and secure?  Companion apps, particularly in healthcare, are rising fast. But the regulatory frameworks that […]

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All About Software as a Medical Device (SaMD)

Understanding Software as a Medical Device (SaMD)

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The International Medical Device Regulators Forum (IMDRF) defined Software as a Medical Device (SaMD) as “software intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device”. The FDA also aligns with this, noting SaMD runs on general-purpose computing platforms, such as smartphones or

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Medical Device Regulations in the United States

Medical Device Regulations in the United States

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Medical devices are indispensable tools that help improve the ability to diagnose and treat illnesses, both simple and complex in nature. As technological disruptors become increasingly available in the healthcare industry, medical device manufacturers are developing more advanced devices which necessitates a robust regulatory framework. Among the regulatory agencies, the United States Food and Drug

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A Guide to Using FDA’s eSTAR for Medical Device Submissions

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The United States Food and Drug Administration (USFDA) introduced the electronic Submission Template and Resource (eSTAR) program as part of its efforts to modernize and streamline medical device submission. This initiative aims to streamline the 510(k)-submission pathway, which is essential for manufacturers seeking to bring new medical devices. As of Oct 1, 2023, the use

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EU Classification of AI medical devices and IVDs

Navigating EU Classification Standards for AI in Medical Devices and Diagnostics

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The European Union (EU) has introduced stringent classification standards for Artificial Intelligence (AI) applications in medical devices and in vitro diagnostics (IVDs) to ensure patient safety, product efficacy, and compliance with regulatory frameworks. With AI technologies, these standards are crucial in defining the pathway for their integration into healthcare systems. This blog dives into the

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Total Product Life Cycle Advisory Program in Medical Devices

Enhancing Medical Device Innovation with the Total Product Life Cycle Advisory Program

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The medical device industry is driven by constant technological advancements and the need to meet growing patient demands. Ensuring that these innovations are safe, effective, and reach the market promptly is a critical aspect of public health. To address this need, the FDA has implemented the Total Product Life Cycle (TPLC) Advisory Program (TAP), a

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Regulatory Framework for Software and Artificial Intelligence as Medical Device

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The convergence of healthcare with technology has led to giant innovations, one of the most significant being the use of software and artificial intelligence (AI) as medical devices. Such developments have been called Software as a Medical Device (SaMD) by many and have wide applicability in transforming the diagnosis, treatment, and care of patients medically.

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Specifications for In Vitro Diagnostic Devices

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In vitro diagnostic medical devices (IVD devices) are an integral part of the healthcare system. They are typically used to analyze samples that are collected from the human body (i.e., saliva, blood, tissue, and urine) and help in diagnosing, screening, and monitoring various conditions. IVD devices are subjected to different regulations that specify different requirements

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The Use of EDDO to Ensure Drug Delivery Function

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When it comes to ensuring the safety and effectiveness of medical devices intended to deliver drugs, understanding Essential Drug Delivery Outputs (EDDO) is important. The advent of drug-device combination products has necessitated the development of robust guidelines to ensure safety, efficacy, and performance. One such crucial aspect of these combination products is the Essential Drug

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Machine Learning-Enabled Medical Devices

Ensuring Transparency for Machine Learning-Enabled Medical Devices

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Transparency in Machine Learning-Enabled Medical Devices (MLMDs) refers to the degree to which relevant information about a device—such as its intended use, the development process, performance, and logic—is clearly communicated to stakeholders.  Why is this important? To help the development of safe, effective, and high-quality AI/ML learning technologies. These may learn from real-world data and

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