Miguel Bronchud, Veteran Cancer Clinician and Researcher and Co-Founder of Regenerative Medicine Solutions, shared on LinkedIn:
“AI-guided anticancer drug identification still requires appropriate clinical trials and comparative testing.
By all means, use AI as an allied tool, but clinical development and statistically robust research will still be required to confirm whether new AI-aided drug designs and combinations of existing drugs are truly clinically meaningful.
Drug development for unmet clinical needs or drug-resistant cancers is not a computer game. It is a science often shaped by unexpected discoveries and changing investment priorities.
In my 50 years in cancer research and clinical practice, I have lived through many unexpected changes, from tamoxifen and cisplatin to many others.
An international research team led by The Institute of Cancer Research, London and RCSI University of Medicine and Health Sciences now provides a roadmap for repurposing existing drugs and developing new treatments for patients with limited options.
In microsatellite-stable colorectal cancer, researchers analysed data from 2,000 patient tumour samples using AI to uncover previously unrecognised relationships between genetic, metabolic, protein and clinical features.
The team developed an AI approach called iPhenMap, creating a biological map of the tumour and revealing connections that may be missed when different data types are studied separately.
These findings may help identify vulnerabilities and treatment combinations that now need rigorous clinical validation.
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