利用液滴微流控技术优化放射性化学反应。
Optimization of Radiochemical Reactions using Droplet Arrays.
机构信息
Physics and Biology in Medicine Interdepartmental Graduate Program, University of California Los Angeles (UCLA); Crump Institute of Molecular Imaging, UCLA.
Crump Institute of Molecular Imaging, UCLA; Department of Molecular & Medical Pharmacology, David Geffen School of Medicine.
出版信息
J Vis Exp. 2021 Feb 12(168). doi: 10.3791/62056.
Current automated radiosynthesizers are designed to produce large clinical batches of radiopharmaceuticals. They are not well suited for reaction optimization or novel radiopharmaceutical development since each data point involves significant reagent consumption, and contamination of the apparatus requires time for radioactive decay before the next use. To address these limitations, a platform for performing arrays of miniature droplet-based reactions in parallel, each confined within a surface-tension trap on a patterned polytetrafluoroethylene-coated silicon "chip", was developed. These chips enable rapid and convenient studies of reaction parameters including reagent concentrations, reaction solvent, reaction temperature and time. This platform permits the completion of hundreds of reactions in a few days with minimal reagent consumption, instead of taking months using a conventional radiosynthesizer.
当前的自动化放射性合成器旨在生产大量的临床用放射性药物。它们并不适合用于反应优化或新型放射性药物开发，因为每个数据点都需要大量试剂消耗，而且仪器污染需要放射性衰变一段时间才能进行下一次使用。为了解决这些限制，开发了一种在平行的微型液滴反应阵列中进行操作的平台，每个反应都被限制在聚四氟乙烯（PTFE）涂层硅“芯片”上的表面张力阱内。这些芯片能够快速方便地研究反应参数，包括试剂浓度、反应溶剂、反应温度和时间。与传统的放射性合成器相比，该平台可在数天内完成数百次反应，只需消耗少量试剂，而不是花费数月时间。
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