Dynamic, personalized dose selection platform, CURATE.AI, in patients with solid tumors: case series and pilot feasibility trial

Abstract

In oncology, the conventional reliance on maximum tolerated doses (MTD) strategy for chemotherapy may not optimize treatment outcomes for individual patients. Artificial intelligence (AI) holds promise to support treatment personalization strategies. In this study we present the experience of feasibility testing of CURATE.AI for individualized dose optimization of capecitabine in the treatment of 10 patients with advanced solid tumors at/for treatment with single-agent capecitabine, capecitabine in combination with oxaliplatin (XELOX), or capecitabine in combination with irinotecan (XELIRI) recruited under PRECISE CURATE.AI trial. CURATE.AI is an AI-derived platform that utilizes a patient’s own, small dataset to dynamically personalize only their own dose recommendations. This case series highlights the logistical and scientific feasibility of providing dynamically personalized AI-derived chemotherapy dose recommendations in the setting of a prospective clinical trial.