Computational Nuclear Oncology Toward Precision Radiopharmaceutical Therapies: Ethical, Regulatory, and Socioeconomic Dimensions of Theranostic Digital Twins

Lidia Strigari, Jazmin Schwarz, Tyler Bradshaw, Julia Brosch-Lenz, Geoffrey Currie, Georges El-Fakhri, Abhinav K. Jha, Signe Mežinska, Neeta Pandit-Taskar, Emilie Roncali, Kuangyu Shi, Carlos Uribe, Tahir Yusufaly, Habib Zaidi, Arman Rahmim, Babak Saboury
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Abstract

Computational nuclear oncology for precision radiopharmaceutical therapy (RPT) is a new frontier for theranostic treatment personalization. A key strategy relies on the possibility to incorporate clinical, biomarker, image-based, and dosimetric information in theranostic digital twins (TDTs) of patients to move beyond a one-size-fits-all approach. The TDT framework enables treatment optimization by real-time monitoring of the real-world system, simulation of different treatment scenarios, and prediction of resulting treatment outcomes, as well as facilitating collaboration and knowledge sharing among health care professionals adopting a harmonized TDT. To this aim, the major social, ethical, and regulatory challenges related to TDT implementation and adoption have been analyzed. Methods: The artificial intelligence–dosimetry working group of the Society of Nuclear Medicine and Molecular Imaging is actively proposing, motivating, and developing the field of computational nuclear oncology, a unified set of scientific principles and mathematic models that describe the hierarchy of etiologic mechanisms involved in RPT dose response. The major social, ethical, and regulatory challenges to realize TDTs have been highlighted from the literature and discussed within the working group, and possible solutions have been identified. Results: This technology demands the implementation of advanced computational tools, harmonized and standardized collection of large real-time data, and modeling protocols to enable interoperability across institutions. However, current legislations limit data sharing despite TDTs’ benefiting from such data. Although anonymizing data is often sufficient, ethical concerns may prevent sharing without patient consent. Approaches such as seeking ethical approval, adopting federated learning, and following guidelines can address this issue. Accurate and updated data input is crucial for reliable TDT output. Lack of reimbursement for data processing in treatment planning and verification poses an economic barrier. Ownership of TDTs, especially in interconnected systems, requires clear contracts to allocate liability. Complex contracts may hinder TDT implementation. Robust security measures are necessary to protect against data breaches. Cross-border data sharing complicates risk management without a global framework. Conclusion: A mechanism-based TDT framework can guide the community toward personalized dosimetry-driven RPT by facilitating the information exchange necessary to identify robust prognostic or predictive dosimetry and biomarkers. Although the future is bright, we caution that care must be taken to ensure that TDT technology is implemented in a socially responsible manner.

向精确放射药物治疗的计算核肿瘤学:治疗数字双胞胎的伦理、监管和社会经济维度
精确放射药物治疗的计算核肿瘤学(RPT)是治疗个性化的新前沿。一项关键策略依赖于将临床、生物标志物、基于图像和剂量学信息纳入患者治疗数字双胞胎(tdt)的可能性,以超越一刀切的方法。TDT框架通过实时监测现实世界系统、模拟不同治疗方案和预测最终治疗结果,以及促进采用统一TDT的卫生保健专业人员之间的协作和知识共享,实现了治疗优化。为此,分析了与TDT实施和采用相关的主要社会、伦理和监管挑战。方法:核医学和分子成像学会的人工智能剂量学工作组正在积极提出、推动和发展计算核肿瘤学领域,这是一套统一的科学原理和数学模型,描述了RPT剂量反应中涉及的病因机制层次。实现tdt的主要社会、伦理和监管挑战已经从文献中得到强调,并在工作组中进行了讨论,并且已经确定了可能的解决方案。结果:该技术需要实现先进的计算工具,协调和标准化的大型实时数据收集,以及建模协议,以实现跨机构的互操作性。然而,目前的立法限制了数据共享,尽管tdts;受益于这些数据。虽然匿名数据通常是足够的,但伦理方面的考虑可能会阻止未经患者同意的共享。寻求道德认可、采用联合学习和遵循指导方针等方法可以解决这个问题。准确和更新的数据输入对于可靠的TDT输出至关重要。在治疗计划和验证中缺乏对数据处理的报销构成了一个经济障碍。tdt的所有权,特别是在相互关联的系统中,需要明确的合同来分配责任。复杂的合同可能会阻碍TDT的实施。需要强有力的安全措施来防止数据泄露。跨境数据共享使没有全球框架的风险管理复杂化。结论:基于机制的TDT框架可以通过促进必要的信息交换来识别可靠的预后或预测性剂量学和生物标志物,从而指导社区实现个性化剂量学驱动的RPT。虽然未来是光明的,但我们警告说,必须注意确保以对社会负责的方式实施TDT技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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