FDA will approve drugs using AI ( very, very quickly ) Stop Trusting the Experts

The Future of Drug Approval: AI’s Rapid Rise and the Risks of Overtrusting Technology

In recent discussions about the future of medical innovation, a provocative idea has emerged: leveraging artificial intelligence to expedite the drug approval process. Not merely assisting decision-makers, but actually replacing traditional vetting procedures—such as clinical trials and animal testing—with AI-driven approvals.

This concept gained attention when RFK Jr. appeared on Tucker Carlson’s show, asserting that the Food and Drug Administration (FDA) could start approving new medications “very, very quickly” through AI. He argued that the current system is too slow and inefficient, suggesting that bypassing extensive testing and relying solely on AI could be the solution. Significantly, he emphasized that this shift could happen soon, indicating a move toward a future where algorithms play a direct role in safeguarding public health.

Challenging Conventional Trust in Expert Authorities

Adding to the controversy, RFK Jr. made a striking statement: “We need to stop trusting the experts.” Framing expert advice as akin to religious doctrine or authoritarian control, he questioned the reliability of medical professionals and scientific authorities. This rhetoric implies that AI could replace human judgment, raising concerns about placing safety and efficacy entirely in the hands of complex neural networks—much of which remains opaque to users and regulators alike.

The Lack of Clear Strategy

However, his vision remains vague on the practical implementation. There’s little detail about how the AI would be trained, what data sources would be used, or the safeguards that would ensure its decisions are accurate and safe. Currently, AI systems are known to occasionally produce “hallucinated” data, misinterpret contexts, or be manipulated. Who bears responsibility if an AI-approved drug causes harm? Is it the developers, the regulatory bodies, or the AI itself? These questions underscore the complexity of substituting traditional processes with unproven technology.

AI in Medicine: Promising, But Not Without Caution

It’s essential to recognize that artificial intelligence holds exciting potential within the realm of biomedical research. For instance, tools like AlphaFold have revolutionized our understanding of protein structures, accelerating drug discovery. Companies such as Isomorphic Labs are exploring how AI can speed up the design of new molecules, suggesting an innovative future for medicine. However, discerning between supporting research and replacing comprehensive safety evaluations is critical.

Designing new compounds is vastly different from certifying their safety in humans. The drug approval process involves years of rigorous testing—clinical