FDA has published 10 guiding principles for Good Machine Learning Practice (GMLP) in the development of medical devices with its regulatory counterparts in Canada and the U.K. The principles, which FDA created with its peers at Health Canada and the U.K. Medicines and Healthcare products Regulatory Agency, are intended to promote development of safe and effective medical devices that use artificial intelligence and machine learning. The document is one of the deliverables laid out in the FDA’s AI/ML software as a medical device (SaMD) action plan issued in January as it looks to establish a regulatory approach to the fast-developing field. FDA framed the principles as a starting point for international harmonization and is seeking feedback as part of its broader discussion of the regulatory framework for modifications to AI/ML-based SaMD.
This year may go down as the point that regulators started to try to get a handle on the use of AI and ML in medical devices. Over the past 10 months, FDA has issued an AI/ML action plan for regulating the technology in medical devices, the European Commission has released contentious plans for the entire AI field and the U.K. has proposed an overhaul of how it regulates AI as a medical device. Now, the U.S. and U.K. have begun working together on a global initiative. Working with their peers at Health Canada, officials at FDA and the U.K.’s MHRA have laid out the following guiding principles:
Collectively, the principles cover concerns about the possible biases of algorithms, their applicability to clinical practice and the potential for them to evolve as they are used in the real world. FDA and its collaborators have expanded on each of the principles, explaining, for example, that developers need to have “appropriate controls in place to manage risks of overfitting, unintended bias or degradation of the model” when their systems are “periodically or continually trained after deployment.”
The principles represent a starting point for further work, rather than the conclusion of the agencies’ thinking about AI and ML. FDA and its partners said the principles “are intended to lay the foundation for developing Good Machine Learning Practice” and identify areas where bodies such as the International Medical Device Regulators Forum could work to advance and harmonize the field.
Fuente: Medtechdive Fecha: 29 octubre, 2021
Effects on Costa Rican exports
Costa Rica already has an experienced IT sector and according to the study “Profile of the Costa Rican offer specialized in 4.0 technologies” carried out by PROCOMER, it is made up of about 450 companies (2019), of which approximately 12% develop technology-based services linked to industry. From this group, 35% of them sells to medical devices industry and 23% to pharmaceutical sector. In addition, the strong position that Costa Rica has in the manufacture of medical devices and the Foreign Direct Investment that the country receives from this type of industry, which is mostly dedicated to exports to the United States, allows the sector to adopt the new AI/ML best practice requirements that the FDA will implement in this industry.
It is also a sector that has experienced in managing large companies and capable of developing safe and effective medical devices that use AI and ML, which should be taken advantage of by international buyers. Costa Rican developers can adopt proven good practices in other fields and adjust them to the needs of medical devices and create new industry-specific approaches. If you are interested in learning more about Costa Rica’s export industry products offer, please let us know at [email protected]
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