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用于小鼠静脉注射药代动力学研究的溶剂型制剂:耐受性及推荐的溶剂剂量限度

Solvent-based formulations for intravenous mouse pharmacokinetic studies: tolerability and recommended solvent dose limits.

作者信息

Thackaberry Evan A, Wang Xiaojing, Schweiger Michelle, Messick Kirsten, Valle Nicole, Dean Brian, Sambrone Amy, Bowman Terri, Xie Minli

机构信息

Department of Safety Assessment .

出版信息

Xenobiotica. 2014 Mar;44(3):235-41. doi: 10.3109/00498254.2013.845706. Epub 2013 Oct 18.

DOI:10.3109/00498254.2013.845706
PMID:24138296
Abstract
  1. Modern high-throughput small molecule drug discovery requires rapid screening of the pharmacokinetic parameters of multiple candidate molecules in parallel. The mouse is often used for such screening, as are solvent-based intravenous formulations. Despite this, the intravenous toxicity of many commonly used solvents is unknown. The purpose of this investigation is to establish recommended no-observed-effect level (NOEL) and maximum tolerated dose (MTD) for several commonly used intravenous solvents in the CD-1 mouse. 2. The acute tolerability of polyethylene glycol 400, N-methylpyrrolidone, dimethyl sulfoxide, ethanol, dimethylacetamide and propylene glycol was established, along with combinations of polyethylene glycol 400 and/or ethanol and DMSO. Based on these data, an acute NOEL and recommended MTD is reported for each solvent or solvent combination. 3. These data can guide the use of these solvents to support single-dose intravenous pharmacokinetic studies in mice. By establishing a defined dose tolerability range for the most commonly used intravenous solvents, undue pain and distress in animals can be avoided while maximizing the generation of critical pharmacokinetic data for project teams.
摘要
  1. 现代高通量小分子药物研发需要并行快速筛选多个候选分子的药代动力学参数。小鼠常被用于此类筛选,基于溶剂的静脉制剂也是如此。尽管如此,许多常用溶剂的静脉毒性尚不清楚。本研究的目的是确定CD-1小鼠中几种常用静脉溶剂的推荐无观察到效应水平(NOEL)和最大耐受剂量(MTD)。2. 确定了聚乙二醇400、N-甲基吡咯烷酮、二甲基亚砜、乙醇、二甲基乙酰胺和丙二醇的急性耐受性,以及聚乙二醇400和/或乙醇与二甲基亚砜的组合。基于这些数据,报告了每种溶剂或溶剂组合的急性NOEL和推荐MTD。3. 这些数据可指导这些溶剂在支持小鼠单剂量静脉药代动力学研究中的使用。通过为最常用的静脉溶剂确定明确的剂量耐受范围,可以避免动物过度疼痛和痛苦,同时为项目团队最大限度地生成关键药代动力学数据。

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