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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：
10084266
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 2023-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10084266
关键词：
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 Pharmacology Physiology Plasma Program Development Rattus Reproducibility Research Research Personnel Running Safety Site Solid Neoplasm Technology Technology Transfer Testing Therapeutic Therapeutic Intervention Time Tissues Translating Treatment Effectiveness Tumor Tissue Validation Work aptamer awake base clinical practice cohort drug testing efficacy study improved in vivo innovation molecular marker personalized medicine 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.

我们展示了第一个对血浆药物水平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。我们使用传感架构实现了这一目标独立于目标分子的化学反应性，使得该方法至少在理论上，可以推广到任何药物。在这里，我们提出了一项研究和开发计划，旨在将这一成果转化为创新突破，成为适用于药理研究和临床的强大新工具实践。通过提高（数量级）我们控制体内药物水平的精度，所提出的技术将使药代动力学成为一个可通过实验控制的参数，从而允许研究人员更精确地绘制药代动力学和临床结果之间的关系，消除药代动力学不一致作为混杂实验变量，并准确模拟动物模型中的人体药代动力学。最终，这种技术可以用于临床，通过根据患者不断变化的新陈代谢不断优化剂量，这将确保治疗的益处最大化，同时风险最小化。