Personalized dose selection platform for patients with solid tumors in the PRECISE CURATE.AI feasibility trial

Area of Science:

• Oncology
• Artificial Intelligence in Medicine
• Personalized Medicine

Background:

• Conventional chemotherapy dosing (maximum tolerated dose) may not be optimal for individual cancer patients.
• There is a need for personalized treatment strategies in oncology.
• CURATE.AI offers a novel AI-derived platform for dynamic dose recommendations.

Purpose of the Study:

• To assess the feasibility of using an AI platform (CURATE.AI) for dynamically personalized chemotherapy dose recommendations.
• To evaluate the platform's adaptability in real-world clinical scenarios for advanced solid tumors.
• To determine user adherence and physician engagement with the AI system.

Main Methods:

• Feasibility trial involving patients with advanced solid tumors treated with capecitabine, XELOX, or XELIRI.
• Utilized CURATE.AI, an AI platform, to generate personalized dose recommendations based on individual patient data.
• Assessed logistical and scientific feasibility, user adherence, and physician engagement.

Main Results:

• CURATE.AI demonstrated adaptability to clinically relevant situations, including palliative care.
• High rates of user adherence were observed.
• Physician engagement in data selection and boundary setting was noted as a contributing factor.

Conclusions:

• Dynamically personalized, AI-derived chemotherapy dose recommendations using CURATE.AI are feasible for advanced solid tumors.
• The platform shows promise for optimizing treatment in oncology.
• High adherence suggests potential clinical utility and acceptance by physicians.