
AI Offers New Pathways to Strengthen Site Leadership in Underserved Regions
Examining how artificial intelligence can help identify true key opinion leaders in emerging markets to improve site influence, patient engagement, and trial success.
In a recent video interview Applied Clinical Trials, Gen Li, PhD, MBA, president, Phesi, highlighted results from the company’s new analysis on global inequity in breast cancer development.He discussed the geographic concentration of breast cancer trial leaders in the US and China, with a positive outlook on global diversity. Operational barriers in lower-income countries were attributed to traditional business models, with opportunities to implement a more patient-centric approach by leveraging artificial intelligence (AI) and machine learning. Li addressed the lack of local KOLs in underserved areas by emphasizing the importance of identifying local leaders. He also stressed the need to redistribute trial workloads and improve recruitment by using AI to identify and activate new sites.
The interview transcript was lightly edited for clarity.
ACT: How does the lack of local KOLs in underserved areas affect site activation, patient trust, and recruitment in breast cancer trials?
Li: We’re in the US, and there are people in India, right? So [in] the medical community, the way [it is] working in the US is not very different [when compared] with the medical community in India, for example.
You still have those leaders being established in a variety [of ways], and probably more so, in places like those less advanced countries—their activities [are] more involved with treating patients and [other direct care responsibilities].
So if we are looking at the issues from this perspective, then there is [a] better chance for us to identify the [true key opinion leaders (KOLs)] in those countries. The danger of not working with the right people is that you will make this whole thing much less influential in that community, and so [you will] have a more difficult time later on when you [try] to launch a particular drug in that country.
So those are the things [that] absolutely can be helped by the advancement of technology. Artificial intelligence giving us a very powerful way to identify the pattern of those leadership activities.
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