智能闭环给药系统

IF 37.6
Marco M. Paci, Tamoghna Saha, Omeed Djassemi, Steven Wu, Corrine Ying Xuan Chua, Joseph Wang, Alessandro Grattoni
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引用次数: 0

摘要

长期慢性疾病管理或治疗的药物管理面临着相当大的挑战,例如需要精确的剂量控制、及时给药和遵守药物方案。由于反应变化、药物浓度波动和缺乏实时监测反馈,传统的给药方法往往导致治疗效果欠佳。智能闭环系统(cls)可以通过将实时生物传感与自动给药相结合来解决这些限制,从而根据个人需求进行个性化治疗。本综述探讨了cls的现状,强调了可穿戴和植入式技术的最新进展,这些技术促进了生物标志物的持续监测,并提供了响应性的治疗干预。我们讨论了设备设计的含义和可穿戴和植入式系统之间的权衡。此外,我们强调了人工智能增强CLS控制算法的潜力,使系统能够学习和预测反应,以实现更有效和自适应的最佳治疗。最后,本综述描绘了下一代cls的发展道路,强调将合成生物学和工程细胞整合到可植入设备中。慢性疾病治疗药物的管理面临着精确剂量控制和及时给药等挑战。本综述探讨了智能闭环系统如何通过将实时生物传感与自动给药相结合来解决这些问题,重点介绍了可穿戴和植入式技术、人工智能增强控制算法以及个性化、适应性治疗合成生物学的集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Smart closed-loop drug delivery systems

Smart closed-loop drug delivery systems
The administration of therapeutics for long-term chronic disease management or treatment faces considerable challenges, such as the need for precise dosage control, timely delivery and adherence to medication regimens. Traditional drug delivery methods often result in suboptimal therapeutic outcomes owing to variable responses, fluctuating drug concentrations and lack of feedback from real-time monitoring. Smart closed-loop systems (CLSs) could address these limitations by integrating real-time biosensing with automated drug delivery, thereby personalizing treatments to individual needs. This Review explores the current landscape of CLSs, highlighting recent advancements in wearable and implantable technologies that facilitate continuous monitoring of biomarkers and offer responsive therapeutic interventions. We discuss the implications of device design and the trade-offs between wearable and implantable systems. In addition, we highlight the potential of artificial intelligence enhancement of CLS control algorithms by enabling systems to learn from and predict responses to achieve more effective and adaptive optimal therapies. Ultimately, this Review charts a path towards next-generation CLSs, emphasizing the integration of synthetic biology and engineered cells into implantable devices. The administration of therapeutics for chronic disease management faces challenges like precise dosage control and timely delivery. This Review explores how smart closed-loop systems can address these issues by integrating real-time biosensing with automated drug delivery, highlighting advancements in wearable and implantable technologies, artificial intelligence-enhanced control algorithms and the integration of synthetic biology for personalized, adaptive therapies.
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