JULY 20229when first put into use. As the product has been built through learning data, the manufacturer shall demonstrate that the quality of the data and data acquisition mechanism is adequate. In addition to the specification of the product and the design process, the manufacturer shall file specifications of the expected changes of the algorithm depending on the experience and data acquired, and the plan to control and validate it.Post-production metrics transparently shared with the authority and the users shall demonstrate that the plan for change control is adequate to maintain safety and effectiveness of the adaptative device.Updated specifications and plans shall be filed when the experience and learning of the device affects the intended use or users, which typically increase over time.Intrinsic to the nature of an adaptative device is its connectivity to multiple devices and sensors that constantly provide input. Besides the need for a robust mechanism to validate the data, there is an extreme need for cyber vulnerability control. Cyber security requirements will strictly apply to these devices.Is this model compatible with EU regulation? MDR requires "devices that incorporate electronic programmable systems, including software, or software that are devices in themselves, shall be designed to ensure repeatability, reliability and performance with their intended use ...". Demonstration of compliance is made in the EU through the application of harmonized standards. The specific standard for the software life cycle is ISO/IEC 62304, which does not specifically exclude AI, but it needs interpretations.To make sure that we can interpret the word "repeatability" not as repeatably provide the same results with repetition of use, but rather repeatably appropriate results for the inputs provided, I would consider a mapping example that a manufacturer could use as reference:· Adopt ISO/IEC 62304 ­Many of the AI companies are small and composed of engineers with a mentality and experience which is far from regulation and interpretations. Have they the skills and can they afford to define the process expected?According to the Centres for Disease Control and Prevention (CDC) statistics, an estimated 50 million people in the U.S. suffer from chronic pain each year, in addition to around 19 million suffering from high impact chronic pain.QUI CKB Y TES· Add Data Life Cycle & Control· Customize with control of dynamic changes· Use in conjunction with Security Standards· Use in conjunction with ISO 82304 to cover the whole life cycle· Define clear criteria to distinguish maintenance (learning within the same intended use) from new cycle (readiness for new intended use/users)The model described, or similar ones, as a potential new way of ensuring adequate regulation, might, in my opinion, allow answering YES to the initial question "Can your medical device learn whilst working," meaning that a manufacturer would be allowed to put into market, devices that learn and adapt to the data and situations, providing outputs not validated according to the traditional regulatory approach and definition, but leaving open questions:· Many of the AI companies are small and composed of engineers with a mentality and experience which is far from regulation and interpretations. Have they the skills and can they afford to define the process expected?· Software is generally international. Can small companies be compliant with different requirements from different regulators? Would IMDRF be a solution for them?· How will Clinical Evaluation be performed and repeated? What value will it provide?· Who will define and control the Intended Use, the actual use and what are the legal and ethical responsibilities?
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