Drugs

Using AI in Drug Development

Five Hogan Lovells attorneys tackle whether and how life sciences companies can use artificial intelligence (AI) tools in their clinical development for medical products and regulatory workflows. In an online post, the attorneys look at two related questions:

whether AI can be used to help interpret or analyze clinical study data; and
whether AI tools can be used to assist with the preparation of submissions to FDA such as INDs, NDAs, and BLAs.

Based on FDA’s 1/2025 draft guidance on the use of AI to support regulatory decision making, the attorneys offer these key takeaways:

FDA’s approach to AI is pragmatic but disciplined, and the agency’s expectations are calibrated to the regulatory risk of the use case;
companies should invest time upfront in defining intended use and conducting appropriate risk assessments;
AI tools used to analyze clinical data could potentially attract significantly greater scrutiny than those used purely for drafting support;
thoughtful case-by-case governance, not blanket prohibition or unchecked adoption, is emerging as the most sustainable path forward; and
where sponsors outsource the development or deployment of AI tools to vendors, robust contracting and active sponsor oversight are essential to fulfilling the sponsor’s obligation to be ultimately responsible and to ensure that AI can be used to support regulatory decision making.

“As FDA continues to encourage sponsors to embrace AI through initiatives like the forthcoming real-time clinical trials (RTCT) pilot program,” the post concludes, “sponsors should ensure AI is deployed with the appropriate rigor, transparency, and human oversight that ensures compliance with the sponsor’s traditional regulatory obligations. The agency is currently conducting a request for information on the proposed RTCT pilot program to assess how AI-enabled technologies can improve efficiency, speed, and quality of decision-making in early-phase clinical trials. This RFI presents a unique opportunity for sponsors to shape the agency’s approach to the use of AI in clinical trials and regulatory decision-making more broadly. The RFI solicits industry feedback on important topics like system performance, trustworthiness, comparative evaluation, decision quality, data integrity, and patient safety.”

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