Artificial Intelligence Driven insights for Regulatory Intelligence in Medical Devices: Evaluating EMA, FDA and CDSCO Frameworks
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Keywords
Regulatory framework, Patient Monitoring, Diagnostics, Neural Networks, Machine Learning
Abstract
The current review elaborates Artificial Intelligence (AI) in medical devices is changing the landscape of diagnostics allowing for more accurate and efficacious treatments leading to better patient care. An overview of AI technologies and their application in medical devices elaborates on AI technologies, such as neural networks and advanced data analytics being applied in diagnostic imaging and patient-monitoring preventative analytic models. Machine learning, a subset of AI, enables devices to learn from data and improve their performance over time, enhancing diagnostic accuracy and personalized treatment plans. An elaborated critical review is presented for the regulatory strategies implemented by relevant global leaders, such as the European Union (EU), the United States (US Food and Drug Administration, FDA), and India (Central Drugs Standard Control Organization of India, CDSCO). This is indicative of the EU regulatory approach as observed through reflection paper by the European Medicines Agency (EMA) on a methodology to assess AI technologies used in conjunction with medicinal products, and the Software as a Medical Device (SaMD) guideline by the FDA in the United States. The discussion is on adaptive regulatory strategies, an overview of some pre-certification programs, and detailed advice to manufacturers about compliance with the processes. Also, India aligning with the International Medical Device Regulators Forum (IMDRF) guidelines shows its appetite to help build an extensive regulatory framework for AI-powered medical devices. The current review concludes by highlighting the need for continued coordination between regulators, manufacturers, and healthcare players so that AI advances are safe and adherent to the regulations that improve overall patient care.
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