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AI-designed mRNA vaccines for diseases that don't exist yet: the new business
AI is designing mRNA vaccines against diseases that don't exist yet. The pharmaceutical business reinvents itself: selling prevention of what might happen. Economic analysis.
AI-designed mRNA vaccines: pandemic insurance sold before the fire starts
The same technology that accelerated the ELbichito vaccines is now preparing for a qualitative leap: using artificial intelligence to design preventive immunizations against diseases that have not yet appeared. This is not science fiction; it is the horizon set by the latest developments in mRNA combined with generative AI models. The concept is as simple as it is unsettling: if AI can predict which pathogens might have pandemic potential, it can also design antigens for them and start injecting before they even exist.
The business is airtight. Pharmaceutical companies, which during the pandemic proved their ability to shape the government agenda, find here a natural extension of their recurring revenue model. No longer is a vaccine given against a real disease, but against what "might happen." The same logic as selling umbrellas in the middle of a drought: you collect the premium on an insurance policy against something that may never arrive, but which justifies the annual injection. And meanwhile, the underlying problem —unsustainable pensions, strained public healthcare— goes unsolved, but the needle keeps going in.
The economic calculations underlying this shift are devastating. An annual vaccination cycle for the entire population against a range of potential threats multiplies the industry's revenue by a factor that no official analysis has made public. With AI generating antigens for mutations it could itself design, the circle closes: the bicho is created, predicted, and vaccinated against. Whoever controls the AI controls the entire cycle.
Summary of a discussion on Burbuja.info - Foro de economía, actualidad y política., translated from Spanish and reviewed before publication.
Read the full discussion (11 replies).
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