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通过实验设计和智能优化算法实现简便的放射性标记优化过程:在奥美拉唑放射性碘化中的应用。

Facile radiolabeling optimization process via design of experiments and an intelligent optimization algorithm: Application for omeprazole radioiodination.

作者信息

Farrag Nourihan S, Abdel-Halim Hala A, Abdel Moamen Ola A

机构信息

Labeled Compounds Department, Hot Labs. Center, Atomic Energy Authority, Cairo, Egypt.

Radioactive Waste Management Department, Hot Labs. Center, Atomic Energy Authority, Cairo, Egypt.

出版信息

J Labelled Comp Radiopharm. 2019 May 30;62(6):280-287. doi: 10.1002/jlcr.3734. Epub 2019 May 20.

DOI:10.1002/jlcr.3734
PMID:30970164
Abstract

The major uses of radiopharmaceuticals (RP) in clinical areas are diagnosis and/or therapy. The present study aimed to utilize the application of fractional factorial design analysis (FFDA) coupled with particle swarm optimization algorithm (PSO) to assess the optimization of RP production process. In this regard, omeprazole (OMP), which is gastric parietal cell proton pump inhibitor (PPI), was radiolabeled with iodine-125 ( I) isotope in order to be used as a radiotracer for stomach imaging. Different factors that affect radiolabeling process were studied. According to the proposed design, just 16 experimental runs of radiolabeling process were performed using the extremes of each factor. In addition, one run was executed at the mean point of each factor. Undesirable maximum radiolabeling yield (RY) of radioiodinated omeprazole ( I-OMP) was deduced from application of FFDA (88.4%). Furthermore, after applying PSO with changing limits of one factor, the maximum RY of I-OMP was found to be 93.78%. Moreover, the practically verification from optimum conditions, which obtained from PSO, was found to give an RY of 93.99%. Overall, the findings of this study confirmed the potential use of that hybrid design for optimization of radiolabeling processes.

摘要

放射性药物(RP)在临床领域的主要用途是诊断和/或治疗。本研究旨在利用分数析因设计分析(FFDA)与粒子群优化算法(PSO)相结合的方法来评估RP生产过程的优化。在这方面,奥美拉唑(OMP)作为胃壁细胞质子泵抑制剂(PPI),用碘-125(I)同位素进行放射性标记,以便用作胃部成像的放射性示踪剂。研究了影响放射性标记过程的不同因素。根据所提出的设计,仅使用每个因素的极值进行了16次放射性标记过程的实验运行。此外,在每个因素的均值点进行了一次运行。通过FFDA的应用推导出放射性碘化奥美拉唑(I-OMP)不理想的最大放射性标记产率(RY)为88.4%。此外,在对一个因素的变化极限应用PSO后,发现I-OMP的最大RY为93.78%。此外,从PSO获得的最佳条件进行的实际验证发现,RY为93.99%。总体而言,本研究结果证实了该混合设计在优化放射性标记过程中的潜在用途。

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