A new commentary in Nature Reviews Cancer explores how digital twin technologies –– virtual, continuously evolving models of individual patients –– can enable personalised cancer treatment, accelerate trial design, and deepen biological understanding over time. Co-authored by Dr Uzma Asghar, Concr’s Chief Scientific Officer and Consultant Medical Oncologist at Guy’s and St Thomas’ NHS Trust, it calls for a move beyond static biomarkers toward dynamic, learning systems that reflect the complexity of human biology and support truly individualized care.
At Concr, these principles are embedded in FarrSight®-Twin, our Bayesian AI-powered predictive engine that combines clinical, molecular, diagnostic and imaging information to provide patient-level predictions about their treatment response, benefit and prognosis.
These capabilities are underpinned by our proprietary Foundation Model of Cancer Biology, validated across multiple partnerships, nine retrospective trials, and the ongoing AI-VISION study.
“Digital twins represent an important shift toward data-driven, patient-specific treatments,” said Dr Uzma Asghar.
“In our commentary, we outline how these evolving models can move oncology beyond static biomarkers, allowing us to simulate how an individual might respond to a therapy before it’s given. That changes how we think about drug development, trial design, and ultimately clinical care.”
The piece underscores the clinical urgency and the importance of continued cross-disciplinary collaboration to drive adoption and validation of these models.
Get in touch if you’re interested to learn more and explore partnership opportunities.
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