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脂质体抗生素在传染病模型中的多模态成像分布评估

Multimodal imaging distribution assessment of a liposomal antibiotic in an infectious disease model.

作者信息

Cheng Shih-Hsun, Groseclose M Reid, Mininger Cindy, Bergstrom Mats, Zhang Lily, Lenhard Stephen C, Skedzielewski Tinamarie, Kelley Zachary D, Comroe Debra, Hong Hyundae, Cui Haifeng, Hoover Jennifer L, Rittenhouse Steve, Castellino Stephen, Jucker Beat M, Alsaid Hasan

机构信息

Bioimaging, GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA 19426-2990, USA.

Bioimaging, GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA 19426-2990, USA.

出版信息

J Control Release. 2022 Dec;352:199-210. doi: 10.1016/j.jconrel.2022.08.061. Epub 2022 Oct 20.

Abstract

Liposomes are promising targeted drug delivery systems with the potential to improve the efficacy and safety profile of certain classes of drugs. Though attractive, there are unique analytical challenges associated with the development of liposomal drugs including human dose prediction given these are multi-component drug delivery systems. In this study, we developed a multimodal imaging approach to provide a comprehensive distribution assessment for an antibacterial drug, GSK2485680, delivered as a liposomal formulation (Lipo680) in a mouse thigh model of bacterial infection to support human dose prediction. Positron emission tomography (PET) imaging was used to track the in vivo biodistribution of Lipo680 over 48 h post-injection providing a clear assessment of the uptake in various tissues and, importantly, the selective accumulation at the site of infection. In addition, a pharmacokinetic model was created to evaluate the kinetics of Lipo680 in different tissues. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) was then used to quantify the distribution of GSK2485680 and to qualitatively assess the distribution of a liposomal lipid throughout sections of infected and non-infected hindlimb tissues at high spatial resolution. Through the combination of both PET and MALDI IMS, we observed excellent correlation between the Lipo680-radionuclide signal detected by PET with the GSK2485680 and lipid component signals detected by MALDI IMS. This multimodal translational method can reduce drug attrition by generating comprehensive biodistribution profiles of drug delivery systems to provide mechanistic insight and elucidate safety concerns. Liposomal formulations have potential to deliver therapeutics across a broad array of different indications, and this work serves as a template to aid in delivering future liposomal drugs to the clinic.

摘要

脂质体是很有前景的靶向给药系统,有潜力提高某些种类药物的疗效和安全性。尽管颇具吸引力,但脂质体药物的研发存在独特的分析挑战,鉴于其为多组分给药系统,包括人体剂量预测。在本研究中,我们开发了一种多模态成像方法,以对一种抗菌药物GSK2485680(以脂质体制剂Lipo680的形式给药)在细菌感染的小鼠大腿模型中的分布进行全面评估,以支持人体剂量预测。正电子发射断层扫描(PET)成像用于追踪注射后48小时内Lipo680的体内生物分布,从而清晰评估其在各种组织中的摄取情况,重要的是,评估其在感染部位的选择性蓄积。此外,建立了一个药代动力学模型来评估Lipo680在不同组织中的动力学。然后使用基质辅助激光解吸/电离(MALDI)成像质谱(IMS)在高空间分辨率下定量GSK2485680的分布,并定性评估脂质体脂质在感染和未感染的后肢组织切片中的分布。通过PET和MALDI IMS的结合,我们观察到PET检测到的Lipo680-放射性核素信号与MALDI IMS检测到的GSK2485680和脂质成分信号之间具有良好的相关性。这种多模态转化方法可以通过生成给药系统的全面生物分布概况来减少药物损耗,以提供机制性见解并阐明安全问题。脂质体制剂有潜力用于广泛的不同适应症的治疗,这项工作可作为一个模板,以帮助未来脂质体药物进入临床。

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