Blasiak Agata, Tan Lester W J, Chong Li Ming, Tadeo Xavier, Truong Anh T L, Senthil Kumar Kirthika, Sapanel Yoann, Poon Michelle, Sundar Raghav, de Mel Sanjay, Ho Dean
The Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, 117456, Singapore.
The N.1 Institute for Health (N.1), National University of Singapore, Singapore, 117456, Singapore.
NPJ Digit Med. 2024 Aug 27;7(1):223. doi: 10.1038/s41746-024-01195-5.
The digital revolution in healthcare, amplified by the COVID-19 pandemic and artificial intelligence (AI) advances, has led to a surge in the development of digital technologies. However, integrating digital health solutions, especially AI-based ones, in rare diseases like Waldenström macroglobulinemia (WM) remains challenging due to limited data, among other factors. CURATE.AI, a clinical decision support system, offers an alternative to big data approaches by calibrating individual treatment profiles based on that individual's data alone. We present a case study from the PRECISE CURATE.AI trial with a WM patient, where, over two years, CURATE.AI provided dynamic Ibrutinib dose recommendations to clinicians (users) aimed at achieving optimal IgM levels. An 80-year-old male with newly diagnosed WM requiring treatment due to anemia was recruited to the trial for CURATE.AI-based dosing of the Bruton tyrosine kinase inhibitor Ibrutinib. The primary and secondary outcome measures were focused on scientific and logistical feasibility. Preliminary results underscore the platform's potential in enhancing user and patient engagement, in addition to clinical efficacy. Based on a two-year-long patient enrollment into the CURATE.AI-augmented treatment, this study showcases how AI-enabled tools can support the management of rare diseases, emphasizing the integration of AI to enhance personalized therapy.
由新冠疫情和人工智能(AI)进步所推动的医疗保健领域数字革命,已导致数字技术的迅猛发展。然而,由于数据有限等因素,在诸如华氏巨球蛋白血症(WM)等罕见疾病中整合数字健康解决方案,尤其是基于人工智能的解决方案,仍然具有挑战性。临床决策支持系统CURATE.AI通过仅基于个体数据校准个体治疗方案,为大数据方法提供了一种替代方案。我们展示了PRECISE CURATE.AI试验中一位WM患者的案例研究,在两年时间里,CURATE.AI向临床医生(用户)提供了动态伊布替尼剂量建议,旨在实现最佳IgM水平。一名80岁男性因贫血需要治疗,新诊断为WM,被招募到该试验中,接受基于CURATE.AI的布鲁顿酪氨酸激酶抑制剂伊布替尼给药。主要和次要结局指标集中在科学和后勤可行性方面。初步结果强调了该平台除临床疗效外,在增强用户和患者参与度方面的潜力。基于对参与CURATE.AI强化治疗长达两年的患者的研究,本研究展示了人工智能工具如何支持罕见疾病的管理,强调了人工智能在增强个性化治疗方面的整合。