Agata Blasiak, Anh T L Truong, Nigel Foo, Lester W J Tan, Kirthika S Kumar, Shi-Bei Tan, Chong Boon Teo, Benjamin K J Tan, Xavier Tadeo, Hon Lyn Tan, Cheng Ean Chee, Wei Peng Yong, Dean Ho, Raghav Sundar
{"title":"Personalized dose selection platform for patients with solid tumors in the PRECISE CURATE.AI feasibility trial.","authors":"Agata Blasiak, Anh T L Truong, Nigel Foo, Lester W J Tan, Kirthika S Kumar, Shi-Bei Tan, Chong Boon Teo, Benjamin K J Tan, Xavier Tadeo, Hon Lyn Tan, Cheng Ean Chee, Wei Peng Yong, Dean Ho, Raghav Sundar","doi":"10.1038/s41698-025-00835-7","DOIUrl":null,"url":null,"abstract":"<p><p>In oncology, the conventional reliance on the maximum tolerated dose (MTD) strategy for chemotherapy may not optimize treatment outcomes for individual patients. CURATE.AI is an AI-derived platform that utilizes a patient's own, small dataset to dynamically personalize only their own dose recommendations. The primary objective of this feasibility trial was to assess the logistical and scientific feasibility of providing dynamically personalized AI-derived chemotherapy dose recommendations for 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). CURATE.AI demonstrated adaptability to clinically relevant situations encountered by patients often treated with palliative intent of care. High rates of user adherence were demonstrated, which could be in part due to the high engagement of the physicians in selecting data and boundaries for CURATE.AI operations.</p>","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"49"},"PeriodicalIF":6.8000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Precision Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41698-025-00835-7","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
In oncology, the conventional reliance on the maximum tolerated dose (MTD) strategy for chemotherapy may not optimize treatment outcomes for individual patients. CURATE.AI is an AI-derived platform that utilizes a patient's own, small dataset to dynamically personalize only their own dose recommendations. The primary objective of this feasibility trial was to assess the logistical and scientific feasibility of providing dynamically personalized AI-derived chemotherapy dose recommendations for 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). CURATE.AI demonstrated adaptability to clinically relevant situations encountered by patients often treated with palliative intent of care. High rates of user adherence were demonstrated, which could be in part due to the high engagement of the physicians in selecting data and boundaries for CURATE.AI operations.
期刊介绍:
Online-only and open access, npj Precision Oncology is an international, peer-reviewed journal dedicated to showcasing cutting-edge scientific research in all facets of precision oncology, spanning from fundamental science to translational applications and clinical medicine.