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.

COVID-19 大流行和人工智能 (AI) 的进步加剧了医疗保健领域的数字革命，导致数字技术的发展激增。然而，由于数据有限等因素，将数字健康解决方案（尤其是基于人工智能的解决方案）整合到华氏巨球蛋白血症（WM）等罕见疾病中仍然具有挑战性。 CURATE.AI 是一种临床决策支持系统，通过仅根据个人数据校准个人治疗概况，提供大数据方法的替代方案。我们介绍了一项针对 WM 患者的 PRECISE CURATE.AI 试验的案例研究，在两年多的时间里，CURATE.AI 向临床医生（用户）提供了动态依鲁替尼剂量建议，旨在实现最佳 IgM 水平。一名 80 岁男性新诊断出 WM，因贫血需要治疗，被招募参加基于 CURATE.AI 的布鲁顿酪氨酸激酶抑制剂依鲁替尼给药试验。主要和次要结果指标侧重于科学和后勤可行性。初步结果强调了该平台除了临床疗效外，还具有增强用户和患者参与度的潜力。这项研究以为期两年的 CURATE.AI 增强治疗患者入组为基础，展示了人工智能工具如何支持罕见疾病的管理，强调人工智能的整合以增强个性化治疗。