Zhaohui Su, VP, Strategic Consulting at Veristat, shared on LinkedIn:
“A recent Clinical Oncology review highlights that the most evidence-supported applications of AI are operational and already being implemented in select cancer centers:
- Patient-trial matching
- Eligibility screening
- EHR data extraction
- Trial monitoring and workflow support
By contrast, more ambitious applications such as:
- Synthetic control arms
- Outcome simulations
- Digital twins
remain in development and face important methodological, validation, and regulatory challenges.
The takeaway: AI can help make oncology trials more efficient, scalable, and accessible, but success will depend on rigorous validation, transparency, human oversight, and following appropriate regulatory frameworks.”
Title: AI-based augmentation of oncology clinical trials
Authors: Andrea Villa, Ashley L. Eadie, David Synnott, Rebecca Romanò, Max Piffoux, Evelyn Yi Ting Wong, Naomi Scheinerman, Daniel S. W. Tan, Filippo Guglielmo Maria de Braud, Miriam Koopman, Jarushka Naidoo, Madhusmita Behera, Selen Bozkurt, Susan Halabi, Rodrigo Dienstmann, Loic Verlingue, Arsela Prelaj, Ravi B. Parikh․
Other articles about AI in Oncology on OncoDaily.