FDA’s AI tool Elsa signals new era for regulatory review, says QuantHealth CEO

When a famously cautious, methodical regulator like the FDA deploys generative AI as the agency recently did with “Elsa,” the industry sits up and takes notice. While there are signs that the tool itself has received something of a mixed response from staff, it also serves as a signpost:  AI has begun an official transition from a vendor buzzword to essential government infrastructure. For now, industry experts are asking questions about transparency, according to a recent article from Hogan Lovells:  Will pharma firms know if AI was used in their reviews? The post flagged the potential that sponsors would have “limited visibility into how much AI influenced the [regulatory] decision, raising concerns about opaque or unvalidated reasoning” as well as noting potential worries related to algorithms, model biases and transparency. 

To understand what the agency’s AI embrace shift means for the pharmaceutical industry and AI vendors already working in the space, Orr Inbar, CEO and co-founder of QuantHealth, shared over email his perspective on Elsa’s launch, its implications for the future of regulatory science and what it signals for companies already leveraging AI in drug development.

R&D World: Now that Elsa has launched with capabilities like summarizing clinical protocols and comparing labels, how well do these initial features align with your expectations of what the agency was doing after it unveiled its plans to deploy genAI agencywide by the end of June? 

Inbar: Elsa’s initial features are a strong match for the FDA’s stated goals. Tools like protocol summarization and label comparison target clear pain points: streamlining time-consuming, manual work in a way that preserves scientific rigor. These are smart, low-risk use cases that play into the strengths of current LLM and GenAI technology, while delivering immediate value for the agency. This early deployment reflects a practical quick-win that builds internal conviction on the value of AI while setting the stage for deeper integration.

R&D World: The FDA frames Elsa as an ‘initial step.’ Beyond these immediate operational gains, how do you see this initiative paving the way for more transformative shifts in regulatory science? 

Inbar: Elsa lays the groundwork for more impactful AI-driven transformation within the FDA. By starting with foundational capabilities, the agency is building infrastructure and trust that can support more complex use cases—like predictive toxicology, adaptive trial design, or real-time clinical data analysis. Longer term, this could lead to a faster, more responsive regulatory system that better keeps pace with scientific innovation, while also encouraging drug developers to integrate AI more fully into their own R&D and submission strategies.

R&D World: Finally, any sense on what the news might mean for vendors like QuantHealth that have long focused on AI? Will it help drive more interest in it given that interest was already high, or is it more of a sign of growing maturity and broader adoption?

Inbar: The FDA’s rollout of Elsa signals not just broader adoption, but also real institutional maturity in how AI is viewed in regulated settings. For companies like QuantHealth, it’s powerful validation—reinforcing that AI is moving from experimentation to essential infrastructure in drug development. We’re already seeing pharmaceutical companies actively implement AI across clinical trial design, drug discovery, and portfolio decisions. Seeing regulatory acceptance start to catch up is encouraging, as it builds confidence across the entire development ecosystem. This convergence between industry and regulators is critical for unlocking the full potential of AI in accelerating innovation and bringing better treatments to patients faster.