渗透性基准:比较硅,体外和体内测量的指南

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Christian Jorgensen*, Raleigh M. Linville, Ian Galea, Edward Lambden, Martin Vögele, Charles Chen, Evan P. Troendle, Fiorella Ruggiu, Martin B. Ulmschneider, Birgit Schiøtt and Christian D. Lorenz, 
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引用次数: 0

摘要

通透性是衡量细胞通过生物屏障运输分子的程度。通透性的单位是每单位时间的距离(通常是厘米/秒),需要精确的测量来定义体内平衡中的药物输送,并模拟疾病期间发生的功能障碍。这一观点提供了一套以社区为主导的指导方针,通过多学科方法和不同的生物学背景来基准渗透率数据。首先,我们为计算渗透性的三种方法制定了分析框架:基于过渡计数或非均匀溶解度扩散方法的硅分析,使用2D或3D几何形状培养的细胞的体外渗透性分析,以及使用原位脑灌注或多时间点回归分析的体内分析。然后,我们演示了在体外和体内进行系统的计算机基准测试,描述了每种基准测试对分析设计的选择敏感的方式。最后,我们概述了渗透率基准测试的七个最佳实践建议,并强调了量身定制的渗透率测定在推动药物输送研究和开发方面的重要性。我们的探索涵盖了“通用”和组织特异性生物屏障的讨论,包括血脑屏障(BBB),这是治疗药物进入大脑的主要障碍。通过解决模拟数据与实验分析相协调的挑战,我们的目标是为优化渗透率建模的准确性和可靠性提供必要的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Permeability Benchmarking: Guidelines for Comparing in Silico, in Vitro, and in Vivo Measurements

Permeability is a measure of the degree to which cells can transport molecules across biological barriers. Units of permeability are distance per unit time (typically cm/s), where accurate measurements are needed to define drug delivery in homeostasis and to model dysfunction occurring during disease. This perspective offers a set of community-led guidelines to benchmark permeability data across multidisciplinary approaches and different biological contexts. First, we lay out the analytical framework for three methodologies to calculate permeability: in silico assays using either transition-based counting or the inhomogeneous-solubility diffusion approaches, in vitro permeability assays using cells cultured in 2D or 3D geometries, and in vivo assays utilizing in situ brain perfusion or multiple time-point regression analysis. Then, we demonstrate a systematic benchmarking of in silico to both in vitro and in vivo, depicting the ways in which each benchmarking is sensitive to the choices of assay design. Finally, we outline seven recommendations for best practices in permeability benchmarking and underscore the significance of tailored permeability assays in driving advancements in drug delivery research and development. Our exploration encompasses a discussion of “generic” and tissue-specific biological barriers, including the blood–brain barrier (BBB), which is a major hurdle for the delivery of therapeutic agents into the brain. By addressing challenges in reconciling simulated data with experimental assays, we aim to provide insights essential for optimizing accuracy and reliability in permeability modeling.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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