Where AI Can Strengthen Clinical Research, and Where Patient Input is More Important

The narrative forming around AI in the pharma and biotech industries is less focused on if the technology should be used, it’s when it should be used. The powerful technology has the capability to be implemented in a variety of workflows, but that doesn’t always mean that it’s being used in a way that gets the best results.

Pharmaceutical Executive spoke with Stacy Hurt, chief patient officer at Parexel, about her views on AI-usage in clinical research. This is an area where she sees tremendous potential for the advanced tech, but she also sees a need to ensure that patients are being the given to provide input in the process as well.

When it’s not used properly, AI may create situations where patients are facing improperly designed research scenarios or struggling with poor communication. However, she also argues that when properly implemented, the AI can allow for a greater level of understanding of the patients’ viewpoints and allow not just for easier communication, but deeper communication as well.

Pharmaceutical Executive: Where can AI strengthen clinical research?
Stacy Hurt: I definitely think that AI can strengthen clinical research by making trials smarter, better, and faster — and the way that translates to patients is bringing treatments, cures, and improved quality of life to them more quickly. Every minute matters to patients, especially when you’re talking about advanced cancer or rare disease. Those minutes translate to moments, and every moment matters. So any way that AI can expedite that is important and meaningful to patients.

Patient input is important from the very beginning, and there’s no replacement for lived patient experience. I said the other day in one of my posts that until AI sits in a chemotherapy chair with chemotherapy running through its veins 55 times — experiencing nausea, fatigue, constipation, diarrhea — there’s no way it can substitute for what patients go through on a daily basis. So AI is complementary to patient experience. Patients know that AI is based on the prompts you give it; it trains on what prompts you give it. So it takes patients asking the right questions from their lived experience to train that AI and work in tandem with patients to improve clinical research for optimal results.