The FDA also launched the Emerging Drug Safety Technology Program (EDSTP).2 Launched in 2024 by the FDA’s Center for Drug Evaluation and Research, this voluntary program offers another forward-looking mechanism for dialogue. It allows sponsors to discuss their AI strategies with the FDA in a non-binding format. The program signals an openness to innovation while maintaining regulatory standards.
By fostering collaboration, it helps bridge the gap between cutting-edge technology and navigating ever-evolving compliance expectations.
Technology’s role in evolving today’s workforce
AI has evolved from a simple upgrade into a catalyst for workforce transformation and upskilling. Traditional PV operations have centered around manual and resource-heavy processes. By leveraging modern, technology-based approaches such as automation, PV professionals can be unshackled from traditional, repetitive, and resource-heavy tasks, allowing them to focus on more critical tasks and gain new skills in AI-based technologies.3
Twenty-first-century PV teams are increasingly composed of specialists with deep domain knowledge and technical fluency. These individuals interpret AI-generated outputs, guide decision-making, and ensure that safety conclusions are clinically sound and compliant with regulatory requirements.
This change calls for targeted workforce development. PV professionals must be trained not only in pharmacology but also in the ethical and operational implications of AI. They need to understand how to validate algorithms, interpret statistical outputs, and collaborate with data scientists and IT teams. As the level of casework continues to increase and automation assistance becomes commonplace, these high-value skills will be essential.
Practical considerations for making AI work for users
Effective AI integration is built on the alignment of people, process, and technology. Organizations must build robust frameworks to assess AI performance quantitatively and by quality, as well as its compliance adherence. This includes thorough documentation on model design, assumptions, version control, and outputs.
At the core of this accelerated technological boom is continuous human oversight and expertise, especially when it comes to signal evaluation and adverse event assessment.
Another factor in ensuring that AI is being used to its fullest potential is identifying the right use cases.
Not every PV activity is suitable for automation. Literature review, for instance, presents a strong use case, as AI can rapidly triage documents and extract relevant clinical content from unstructured data. Similarly, contact center calls and social media activity can be analyzed for potential adverse events using natural language processing and sentiment analysis.
A common theme in each use case is that implementation must be backed by a clear change management strategy. This includes preparing teams for updated or new workflows, communicating compliance requirements, and embedding checks and balances that prioritize patient safety above efficiency gains.
Preparing for what’s next
The FDA’s draft guidance and EDSTP indicate an important inflection point, not to be seen as speed bumps to slow progress but as invitations to engage in thoughtful innovation. Sponsors who take advantage of these programs can better anticipate regulatory expectations and gain confidence in their AI systems.
Ultimately, the future of PV will not be defined by the technology-driven tools but by the users and strategies behind them. AI can help PV teams push the boundaries of what is possible, but only if it is applied with clarity, integrity, and a sustained focus on patient outcomes.
Archana Hegde is Senior Director, PV Systems and Innovations, at IQVIA
References
1. FDA, Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products (January 2025). https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-artificial-intelligence-support-regulatory-decision-making-drug-and-biological
2. CDER Emerging Drug Safety Technology Program (EDSTP). FDA. May 7, 2025. https://www.fda.gov/drugs/science-and-research-drugs/cder-emerging-drug-safety-technology-program-edstp
3. Kell, J. How Pharmaceutical Companies Are Training Their Workers on AI. Business Insider. March 10, 2025. https://www.businessinsider.com/pharmaceutical-companies-embrace-ai-in-drug-discovery-efforts-2025-3?utm_source=chatgpt.com