Materiovigilance in Medical Devices: Current Practices, Challenges, and Future Perspectives

The World Health Organization (WHO) defines a medical device as any tool, apparatus, implant, reagent, software, or other item used for medical purposes, such as illness diagnosis, prevention, monitoring, or treatment, or for maintaining or supporting life. These days, pharmacovigilance also includes drug therapy-related problems (DTRPs) demonstrated by biologicals and blood products, medical devices, herbal remedies, and traditional, complementary, and alternative medicines (TCAMs). While pharmacovigilance (PV) and Materiovigilance (MV) have similar reporting objectives and methods, MV focuses on medical device adverse reactions and preventative techniques. Machine learning can be utilized for signal detection, safety surveillance, and the detection of ADRs or ADEs. Software as a medical device (SaMD) is defined by the International Medical Device Regulators Forum (IMDRF, https://www.imdrf.org/) as software designed for medical purposes that is not dependent on physical devices. For artificial intelligence (AI) applications, all available health data and medical images such as those from computed tomography, magnetic resonance, nuclear medicine, x-rays, and ultrasound exams may be the most intriguing. Pharmacovigilance focuses on all adverse drug reactions (ADRs), product quality flaws, medication errors, and ineffectiveness.