Data from the various manufacturers’ digital twins would regularly (e.g. daily) ‘feed’ a government-controlled ‘๐ฉ๐ก๐๐ซ๐ฆ๐ ๐ข๐ง๐๐ฎ๐ฌ๐ญ๐ซ๐ฒ ๐ฆ๐๐ง๐ฎ๐๐๐๐ญ๐ฎ๐ซ๐ข๐ง๐ ๐๐ง๐ ๐ฌ๐ฎ๐ฉ๐ฉ๐ฅ๐ฒ ๐๐ก๐๐ข๐ง ๐๐ข๐ ๐ข๐ญ๐๐ฅ ๐ญ๐ฐ๐ข๐ง.’
This will require enabling legislation e.g. to overcome manufacturer claims of proprietary information, trade secrets, etc. that they historically have used to not provide information. A wide variety of “carrots” and "sticks" will need to be used to gain industry cooperation, for example the government underwriting the costs of development, deployment, and implementation, with the benefits of having such a system accruing to the manufacturers.
Once the FDA’s QMMP is deployed to manufacturers its data can then also be folded into the digital twin. With the resulting complete transparency and end-to-end visibility across the entire industry now available to the government (manufacturing information, quality information, supply chain information, etc.), the use of AI, ML, and other such tools should support the ability to forecast and anticipate problems, issues, disruptions, etc. so that the appropriate efforts at prevention, mitigation, etc. can be carried out successfully.
6-part article of which the above is a sub-part
6-part article of which the above is a sub-part
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