他克莫司
加药
个性化
医学
肝移植
移植
目标射程
内科学
计算机科学
人工智能
万维网
作者
Shi‐Bei Tan,Kirthika Senthil Kumar,Tiffany Rui Xuan Gan,Lester W. J. Tan,Anh T. L. Truong,Agata Blasiak,Marion M. Aw,Vidyadhar Padmakar Mali,Dean Ho
标识
DOI:10.1002/adtp.202300236
摘要
Abstract Tacrolimus is the cornerstone of immunosuppressive therapy after pediatric liver transplantation. However, reliance on the physician's experience for dose titration, coupled with tacrolimus's narrow therapeutic window and inter‐ and intrapatient variability, often results in frequent under or overdosing events with detrimental patient outcomes. Existing predictive dose personalization models are not readily feasible for clinical implementation, as they require multiple measurements each day while the standard frequency is once daily. CURATE.AI, a small‐data artificial intelligence‐derived platform, is developed as a clinical decision support system to dynamically personalize doses using the patient's own data obtained once a day. Retrospective dose personalization with CURATE.AI on 16 patients’ data demonstrates potential to enable more patients to reach therapeutic range within the first week. The findings support the testing of CURATE.AI in a prospective controlled trial as an aid for the physician's decision on tacrolimus dose personalization after pediatric liver transplantation.
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