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Critical Challenges in ML-Based SaMDs prompting FDA Action Plan
Author: Navid Toosi Saidy, Quality and Technology Translation Lead at Max Kelsen
At Max Kelsen, we’re developing a range of advanced machine learning-based Digital Health solutions for a range of pressing issues across the healthcare and life sciences industry. We envision this next generation of software tools will be vital to improving healthcare services, diagnostics and disease or injury management and assist healthcare workers to provide the best quality of care to patients.
Software used for diagnostics, prevention, treatment or monitoring of a disease fall into a category called ‘software as a medical device’ (SaMD) and are closely monitored and regulated by authorities such as the Food and Drug Administration (FDA) in the USA, as well as Australia’s Therapeutic Goods Administration (TGA).
While recent endeavours by the International Medical Device Regulators Forum (IMDRF) have provided better clarity around quality management and translation of SaMDs, regulation authorities are under mounting pressure to consider the implications of the fast-paced development of artificial intelligence (AI) and machine learning (ML)-based SaMDs.
Just a couple of weeks ago, the US FDA published an action plan for safe and patient-centric regulation of AI and ML-based…
