PDF(Pubmed)
Abstract：
Niclosamide, a potent anthelmintic agent, has emerged as a candidate against COVID-19 in recent studies. Its formulation has been investigated extensively to address challenges related to systemic exposure. In this study, niclosamide was formulated as a long-acting intramuscular injection to achieve systemic exposure in the lungs for combating the virus. To establish the dose-exposure relationship, a hamster model was selected, given its utility in previous COVID-19 infection studies. Pharmacokinetic (PK) analysis was performed using NONMEM and PsN. Hamsters were administered doses of 55, 96, 128, and 240 mg/kg with each group comprising five animals. Two types of PK models were developed, linear models incorporating partition coefficients and power-law distributed models, to characterize the relationship between drug concentrations in the plasma and lungs of the hamsters. Numerical and visual diagnostics, including basic goodness-of-fit and visual predictive checks, were employed to assess the models. The power-law-based PK model not only demonstrated superior numerical performance compared with the linear model but also exhibited better agreement in visual diagnostic evaluations. This phenomenon was attributed to the nonlinear relationship between drug concentrations in the plasma and lungs, reflecting kinetic heterogeneity. Dose optimization, based on predicting lung exposure, was conducted iteratively across different drug doses, with the minimum effective dose estimated to be ~1115 mg/kg. The development of a power-law-based PK model proved successful and effectively captured the nonlinearities observed in this study. This method is expected to be applicable for investigating the drug disposition of specific formulations in the lungs.
摘要：
氯硝柳胺,一种有效的驱虫药,在最近的研究中，已成为对抗COVID-19的候选药物。已对其配方进行了广泛的研究，以应对与全身暴露有关的挑战。在这项研究中,氯硝柳胺被配制为长效肌内注射剂，以实现肺部全身暴露，以对抗病毒。为了建立剂量-暴露关系，选择了仓鼠模型，鉴于其在以前的COVID-19感染研究中的实用性。使用NONMEM和PsN进行药代动力学(PK)分析。给仓鼠施用55、96、128和240mg/kg的剂量,每组包括五只动物。开发了两种类型的PK模型，包含分配系数和幂律分布模型的线性模型，表征仓鼠血浆和肺中药物浓度之间的关系。数值和视觉诊断，包括基本的拟合优度和视觉预测检查，被用来评估模型。与线性模型相比，基于幂律的PK模型不仅表现出优越的数值性能，而且在视觉诊断评估中也表现出更好的一致性。这种现象归因于血浆和肺中药物浓度之间的非线性关系，反映动力学异质性。剂量优化,基于预测肺部暴露，在不同的药物剂量中迭代进行，最小有效剂量估计为〜1115mg/kg。基于幂律的PK模型的开发被证明是成功的，并有效地捕获了本研究中观察到的非线性。预期该方法适用于研究特定制剂在肺中的药物处置。
