After Slashing Thousands of Jobs, Trump's FDA Wants to Use AI to Rapidly Approve New Drugs
AI is slowly permeating all corners of the federal government, including the Food and Drug Administration, where, according to a newly released paper, its top brass now wants to use automation to more 'efficiently' approve new drugs.
An article recently published in the Journal of the American Medical Association (JAMA) by Dr. Vinay Prasad, the FDA's director of a subagency that deals with vaccines, lays out a vision for revamping the agency that will supposedly 'increase efficiency' at the agency that regulates what you eat and drink. According to that article, a big way to make the agency more efficient is to use AI to do tasks that humans previously worked on. Specifically, it suggests using automation to speed up the drug approval process.
'The advent of generative artificial intelligence (AI) holds several promises to modernize the FDA and radically increase efficiency in the review process,' the paper reads, while noting that the agency has already implemented a pilot program that involves first 'AI-assisted scientific review.' The article also speaks of a need to 'reevaluate legacy processes at the agency that slow down decisions and do not increase safety.'
The study also claims it is looking to find ways to use technology to avoid 'animal cruelty' at the agency. It has supposedly done this by developing 'a road map to reduce animal testing using AI-based computational modeling to predict toxicity-leveraging chip technology.'
All of this news comes not long after the FDA purged thousands of staffers from its ranks, including those responsible for reviewing food safety. Now, in what has become a typical pivot for organizations looking to integrate AI, roles previously held by humans seem like they're being automated.
The article also suggests the use of 'big data' to help better assess how drug products are developed and reviewed. 'In the past, randomized clinical trials were the sole method used to determine if a product was safe and effective,' the article reads. 'Advances in causal inference in nonrandomized data, including the use of target trials, which attempt to balance confounding and time zero, have [the] potential to yield actionable causal conclusions, in many cases at lower cost.'
AI has been spread throughout other parts of the government, as the administration's supposed 'efficiency' mandate looks for newfangled methods to 'streamline' bureaucratic processes. If AI could technically help speed up some bureaucratic processes, a quick look at the way automation rollout is being handled at other agencies doesn't necessarily inspire confidence in the initiative, particularly when it comes to an agency tasked with overseeing drugs that go into Americans' bodies.
When it comes to new drugs, there are always guinea pigs involved in the process; now AI's impact will have to be factored into the effectiveness of the latest tests.
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