Feedback controlled, ultra-high-precision drug delivery

反馈控制的超高精度药物输送

• 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
• 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

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.

我们已经展示了有史以来第一个闭环反馈控制血浆药物水平的例子