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Feedback controlled, ultra-high-precision drug delivery

反馈控制的超高精度药物输送

基本信息

批准号：
10321612
负责人：
Kevin W Plaxco
金额：
$ 48.96万
依托单位：
UNIVERSITY OF CALIFORNIA SANTA BARBARA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-01-14 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10321612
关键词：
Anesthesia procedures Animal Model Animal Welfare Animals Architecture Area Under Curve Biological Markers Brain Chemicals Clinic Clinical Clinical Research Communities Complex Development Dose Drug Delivery Systems Drug Kinetics Drug Monitoring Drug toxicity Ensure Exhibits Feedback Foundations Frequencies Goals Health Status Hour Human In Situ Infection Intravenous Maintenance Maps Measurement Measures Medical Research Metabolism Methods Molecular Mus Nature Outcome Pathology Patients Peripheral Pharmaceutical Preparations Pharmacological Treatment Physiology Plasma Program Development Rattus Reproducibility Research Research Personnel Running Safety Site Solid Neoplasm Technology Testing Therapeutic Therapeutic Intervention Time Tissues Translating Treatment Effectiveness Validation Work aptamer awake clinical practice cohort drug testing efficacy study improved in vivo innovation molecular marker personalized medicine pharmacologic precision drugs preclinical study programs research and development response risk minimization sensor simulation temporal measurement theories therapy outcome tool

项目摘要

We have demonstrated the first ever example of closed-loop feedback control over plasma drug levels informed by real-time in-vivo drug measurements. We achieved this using a sensing architecture that is independent of the chemical reactivity of the target molecule, rendering the approach, at least in theory, generalizable to any drug. Here we propose a research and development program aimed at translating this innovative breakthrough into a powerful new tool applicable to both pharmacological research and clinical practice. By improving (by orders of magnitude) the precision with which we can control in-vivo drug levels, the proposed technology would render pharmacokinetics an experimentally controllable parameter, allowing researchers to more precisely map the relationships between pharmacokinetics and clinical outcomes, to eliminate pharmacokinetic inconsistency as a confounding experimental variable, and to accurately simulate human pharmacokinetics in animal models. Ultimately, such a technology could be used in the clinic where, by optimize dosing moment-to-moment in response to a patient's changing metabolism, it would ensure that a therapy's benefits are maximized while its risks are minimized.

我们已经展示了第一个对血浆药物浓度进行闭环反馈控制的例子。通过实时体内药物测量获得信息。我们使用一种传感体系结构实现了这一点与目标分子的化学反应无关，使得该方法，至少在理论上，可推广到任何药物。在这里，我们提出一个研究和开发计划，旨在将这一点创新突破成为既适用于药理研究又适用于临床的强大新工具练习一下。通过提高(数量级)我们控制体内药物水平的精确度，拟议的技术将使药代动力学成为实验上可控的参数，从而研究人员更精确地映射药代动力学和临床结果之间的关系，以消除药代动力学不一致性作为混杂的实验变量，并准确模拟人在动物模型中的药代动力学。最终，这样的技术可以用于临床，在那里，根据患者不断变化的新陈代谢，随时优化给药，它将确保治疗的好处是最大化的，而风险是最小的。