AI Is Moving Fast. Evidence Matters More.The conversation around AI in pharma has changed.
The question is no longer simply what AI could do. As its use expands across drug discovery, clinical trials, and safety, the more important questions are what has actually been proven, where the limitations remain, and how regulatory expectations are evolving alongside the technology.
That distinction matters.
An AI application showing promise in drug discovery is not the same as one being relied upon in a regulated clinical environment. And as applications move closer to decisions affecting development, evidence, compliance, and patient safety, understanding context of use, risk, and regulatory status becomes increasingly important.
Proof, Not Promise: How AI Is Actually Changing Pharma takes a deeper, evidence-based look at this changing landscape, including:
- Discovery: Where AI is producing tangible results and where expectations still exceed the evidence
- Clinical Trials: How AI and Big Data are changing the way trials can be designed, conducted, and evaluated
- Safety: Where AI is influencing the analysis and management of increasingly complex information
- Regulation: How FDA, EMA, and ICH frameworks are responding, including what is currently binding versus still evolving
- What Comes Next: The developments most likely to affect regulatory and compliance obligations over the next 12 to 18 months
Rather than treating AI as one technology with one level of maturity, this workshop provides a framework for asking a more useful question:
What is the evidence, and is it sufficient for this particular use?For professionals already familiar with the basics of AI, the session is designed to help connect the technology to the real operating, regulatory, and compliance environment of pharma today. |
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