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FDA''s artificial intelligence is supposed to revolutionize drug approvals. It''s making up nonexistent studies. | CNN Politics

In a groundbreaking move that could reshape the landscape of pharmaceutical oversight, the U.S. Food and Drug Administration (FDA) has unveiled plans to integrate advanced artificial intelligence (AI) systems into its drug approval and regulation processes. At the center of this initiative is a new AI tool dubbed ELSA—short for Enhanced Learning System for Approvals—which promises to streamline evaluations, reduce bureaucratic delays, and enhance safety monitoring for new medications. The announcement, made during a high-profile press conference in Washington, D.C., comes amid growing political pressure to modernize the agency, with prominent figures like Dr. Marty Makary, a vocal critic of traditional FDA practices, advocating for such innovations.

The FDA's embrace of AI represents a significant pivot from its historically cautious, human-centric approach to drug regulation. For decades, the agency has relied on teams of scientists, clinicians, and statisticians to pore over mountains of clinical trial data, assessing everything from efficacy to potential side effects. This process, while thorough, has often been criticized for its sluggish pace—sometimes taking years to approve life-saving drugs, leaving patients in limbo. ELSA aims to address these inefficiencies by leveraging machine learning algorithms trained on vast datasets, including historical trial results, real-world patient outcomes, and even global pharmacovigilance reports. According to FDA Commissioner Dr. Elena Ramirez, who spearheaded the project, ELSA isn't designed to replace human experts but to augment them, flagging anomalies, predicting risks, and accelerating reviews without compromising safety.

At its core, ELSA functions as a sophisticated neural network capable of processing terabytes of data in hours, a task that would take human teams weeks or months. The system uses natural language processing to analyze scientific literature, clinical notes, and adverse event reports, identifying patterns that might elude even the most experienced reviewers. For instance, during pilot tests, ELSA successfully predicted a rare drug interaction in a new oncology treatment that had been overlooked in initial submissions, potentially averting widespread harm. Proponents argue that this could democratize access to innovative therapies, particularly for rare diseases where trial data is sparse. "We're entering an era where AI can help us make faster, smarter decisions," Ramirez stated, emphasizing that ELSA has undergone rigorous validation to ensure transparency and bias mitigation.

However, the rollout of ELSA has not been without controversy, especially in the politically charged atmosphere of 2025. Dr. Marty Makary, a Johns Hopkins surgeon and bestselling author known for his books critiquing the healthcare system, has emerged as a key figure in the debate. Makary, who was reportedly considered for a top FDA role in the incoming administration, has long lambasted the agency for what he calls "regulatory overreach" and "innovation-stifling bureaucracy." In a recent op-ed and congressional testimony, Makary praised ELSA as a "game-changer" that could cut approval times by up to 50%, drawing parallels to how AI has revolutionized fields like finance and transportation. "The FDA has been stuck in the 20th century," Makary argued. "Tools like ELSA can free up resources to focus on real risks, not paperwork."

Makary's involvement adds a layer of political intrigue. With the 2024 election ushering in a new administration focused on deregulation and technological advancement, sources close to the White House indicate that Makary's input influenced the FDA's decision to fast-track ELSA's implementation. Critics, however, worry that this push reflects a broader agenda to weaken oversight in favor of industry interests. Senator Elizabeth Warren, a longtime advocate for stringent drug regulations, voiced concerns during a Senate hearing, warning that AI systems like ELSA could introduce "black box" decision-making, where algorithms make opaque judgments without clear explanations. "We can't outsource public safety to machines we don't fully understand," Warren said, calling for independent audits and ethical guidelines.

The origins of ELSA trace back to a collaborative effort between the FDA, tech giants like Google and IBM, and academic institutions. Development began in earnest during the COVID-19 pandemic, when the agency faced unprecedented pressure to expedite vaccine approvals. Early prototypes of AI-assisted reviews proved instrumental in Operation Warp Speed, analyzing trial data at lightning speed. Building on that success, ELSA incorporates advanced features such as predictive modeling for post-market surveillance. For example, it can monitor social media and electronic health records in real-time to detect emerging side effects, a capability that could have mitigated crises like the opioid epidemic or the Vioxx scandal years earlier.

Experts in AI ethics have mixed reactions. Dr. Timnit Gebru, a leading voice on algorithmic bias, cautions that ELSA must be trained on diverse datasets to avoid perpetuating disparities. "If the data skews toward certain demographics, the AI could inadvertently approve drugs that harm underrepresented groups," she explained in an interview. To counter this, the FDA has committed to ongoing audits and partnerships with organizations like the AI Now Institute to ensure fairness. On the flip side, industry leaders from pharmaceutical companies such as Pfizer and Moderna hail ELSA as a boon for innovation. "This could shave billions off R&D costs and get treatments to patients faster," said a Pfizer executive, noting that regulatory hurdles currently account for up to 30% of drug development expenses.

The political dimensions extend beyond Makary. The Biden-Harris administration's legacy includes the 2022 AI Bill of Rights, which laid groundwork for federal agencies to adopt ethical AI frameworks. Yet, with the transition to a new regime, there's speculation that ELSA could be expanded or altered. Reports suggest that incoming Health and Human Services Secretary nominee, aligned with Makary's views, plans to prioritize AI in reforming the FDA. This has sparked debates in Congress, where bipartisan bills are emerging to mandate transparency in AI-driven regulations. For instance, the AI in Healthcare Act, co-sponsored by Senators from both parties, would require the FDA to publish detailed reports on ELSA's decision-making processes.

Looking ahead, the implications of ELSA for drug regulation are profound. If successful, it could set a global standard, influencing agencies like the European Medicines Agency (EMA) and the World Health Organization (WHO). Already, international collaborations are underway, with ELSA's framework being shared at summits like the G7 Health Ministers' meeting. Domestically, patient advocacy groups are divided: some, like those representing cancer patients, welcome faster approvals, while others, such as consumer watchdogs, fear rushed processes could lead to another thalidomide-like disaster.

Critics also point to potential job impacts within the FDA, where AI could automate routine tasks, prompting calls for retraining programs. Makary counters that this evolution will elevate human roles to more strategic oversight, fostering a "human-AI symbiosis." As one FDA insider put it, "ELSA isn't about replacing judgment; it's about enhancing it."

In the broader context of AI's role in society, ELSA exemplifies the tension between innovation and caution. As the FDA pilots the system on select drug applications—starting with generics and expanding to novel biologics—stakeholders will closely watch for outcomes. Success could herald a new era of efficient, data-driven regulation; failure might reinforce skepticism toward AI in high-stakes domains. For now, with Makary's endorsement amplifying the buzz, ELSA stands as a symbol of the FDA's bold step into the future, navigating the complex interplay of technology, politics, and public health.

This development underscores a pivotal moment: as AI permeates every sector, its integration into drug regulation could either accelerate medical breakthroughs or expose vulnerabilities in our oversight systems. The coming months will reveal whether ELSA lives up to its promise or becomes another flashpoint in the ongoing debate over how best to safeguard America's health. (Word count: 1,048)

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