AI Growing in Focus Amid HHS Restructure

The Department of Health and Human Services (HHS)’s recent reorganization in line with its “Make America Healthy Again” overall plan comes with new focuses on artificial intelligence development.

“The AI revolution has arrived, and we will be the cutting-edge agency using this technology to manage health care data more efficiently and securely, and to give Americans control over their own health,” HHS Secretary Robert Kennedy said during a Senate budget hearing on May 14.

The agency’s reorganization is significant. In addition to consolidating the agency’s 41 CIOs and disparate IT departments and creating 15 new divisions, it’s in the process of appointing new leadership. Earlier this month, the agency publicly listed a new CIO, Clark Minor. Yet it has not yet publicly confirmed a new chief AI officer.

Amid these movements, the agency has amplified renewed messages around AI and how it can help introduce efficiencies.

AI in Animal Testing

A key part of Make America Healthy Again that was also touted in the agency’s first 100 days is the initiative to minimize animal testing with the help of AI.

A partnership between NIH and FDA is exploring how to do this to not only reduce how much testing is done on animals, but also speed up evaluation processes and lower costs in research and consumer drug prices.

“By leveraging AI-based computational modeling, human organ model-based lab testing and real-world human data, we can get safer treatments to patients faster and more reliably, while also reducing R&D costs and drug prices,” said FDA Commissioner Martin Makary in a press release.

FDA plans to use pre-existing, real-world safety data from other countries, with comparable regulatory standards, where the drug has already been studied in humans. Makary said that the transition holds promise in accelerating cures.

“For patients, it means a more efficient pipeline for novel treatments. It also means an added margin of safety, since human-based test systems may better predict real-world outcomes,” he said.

NIH Director Dr. Jay Bhattacharya called this a critical leap forward in science and patient care.

“By integrating advances in data science and technology with our growing understanding of human biology, we can fundamentally reimagine the way research is conducted — from clinical development to real-world application,” said Bhattacharya.

AI in Drug Manufacturing

A new partnership between HHS, the Administration for Strategic Preparedness and Response (ASPR) and the Defense Advanced Research Projects Agency (DARPA) aims to accelerate drug manufacturing with emerging technologies like AI. The program, called Equip-A-Pharma, will couple industry partners and federal agencies to show how AI could enhance efficiency, lower production costs, reduce drug shortages and speed up approval times for drugs manufacturing.

“Traditional pharmaceutical manufacturing is often too rigid and slow to adapt to changing demands, especially during national emergencies. We’re launching projects aimed at completely changing the approach not just to bring pharmaceutical manufacturing back to the U.S. but to do it better,” said HHS Principal Deputy Assistant Secretary for Preparedness and Response John Knox in a press release.

FDA Rolls Out AI

With newly helmed Chief AI Officer Jeremy Walsh, FDA plans to release an “aggressive timeline” to scale use of internal generative AI tools across all FDA centers by June 30. The end state would see all centers operating on a single, secure generative AI system that integrates with internal data platforms.

“There have been years of talk about AI capabilities in frameworks, conferences and panels, but we cannot afford to keep talking,” said FDA Commissioner Marty Makary in a press release.

The tools will enable scientists and subject-matter experts to spend less time on repetitive tasks that slow down processes like drug reviews.

“This is a game-changer technology that has enabled me to perform scientific review tasks in minutes that used to take three days,” said Jin Liu, deputy director at FDA’s Office of Drug Evaluation Sciences.

Future iterations will focus on improving usability, expanding document integration and tailoring outputs to center-specific needs.