Innovative AI 'Digital Twin' Platform Personalizes Cancer Treatment Dosing in Clinical Research

Researchers at the National University of Singapore's Yong Loo Lin School of Medicine have developed a groundbreaking AI-powered platform that tailors chemotherapy doses to individual cancer patients. This innovative 'digital twin' technology creates a virtual replica of each patient's biological profile by analyzing biomarkers like CEA and CA125, along with treatment data, to optimize drug dosing in real time.

In a recent feasibility study conducted at the National University Cancer Institute in Singapore, the team led by Professor Dean Ho successfully utilized the CURATE.AI platform to make precise dose adjustments for 10 patients diagnosed with advanced solid tumors. Over the course of nearly two years, clinicians accepted 97.2% of the platform's dose recommendations, some of which were approximately 20% lower than standard doses, potentially reducing side effects and treatment costs.

This approach marks a significant shift in personalized oncology, moving away from uniform treatment protocols toward dynamic, data-driven adjustments based on each patient's evolving condition. The system integrates clinical data such as drug type, dosage, and biomarker levels to generate customized treatment plans, allowing for more precise and effective care.

Professor Ho emphasizes that current data collection methods are largely static snapshots, which do not reflect how patients change over time. "By harnessing AI to continuously adapt dosing based on live biomarker data, we are opening new horizons in personalized medicine," he states.

The clinical trial's success demonstrates the potential for AI to transform cancer treatment, not only enhancing efficacy but also reducing unnecessary medication and associated costs. The study, published in npj Precision Oncology, paves the way for larger trials to validate this personalized approach and its benefits.

Beyond oncology, this technology shows promise in other medical fields like immunotherapy, hypertension, and longevity medicine. Co-author Nigel Foo highlights that effective treatment relies on not just data quantity but quality and timing, with digital twins guiding individualized patient care based on how their biomarker profiles evolve.

As AI-driven precision medicine advances, such innovations are poised to revolutionize clinical practices, making treatments safer, more effective, and tailored specifically to each patient's unique biological journey.