SpatialCNS-PBPK: An R/Shiny Web-Based Application for Physiologically Based Pharmacokinetic Modeling of Spatial Pharmacokinetics in the Human Central Nervous System and Brain Tumors.

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Charuka D Wickramasinghe, Seongho Kim, Jing Li
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Abstract

Quantitative understanding of drug penetration and exposure in the human central nervous system (CNS) and brain tumors is essential for the rational development of new drugs and optimal use of existing drugs for brain cancer. To address this need, we developed and validated a novel 9-compartment permeability-limited CNS (9-CNS) physiologically based pharmacokinetic (PBPK) model, enabling mechanistic and quantitative prediction of spatial pharmacokinetics for systemically administered small-molecule drugs across different regions of the human brain, cerebrospinal fluid, and brain tumors. To make the 9-CNS model accessible to a broad range of users, we developed the SpatialCNS-PBPK app, a user-friendly, web-based R/Shiny platform built with R and Shiny programming. The app provides key functionalities for model simulation, sensitivity analysis, and pharmacokinetic parameter calculation. This tutorial introduces the development and evaluation of the SpatialCNS-PBPK app, highlights its key features and functions, and provides a step-by-step user guide for practical applications. By enhancing our ability to predict the spatial pharmacokinetics of anticancer drugs in the human CNS and brain tumors, the SpatialCNS-PBPK app serves as an invaluable computational tool and data-driven approach for advancing drug development and optimizing treatment strategies for more effective treatment of brain cancer.

SpatialCNS-PBPK:基于R/Shiny的基于生理的人类中枢神经系统和脑肿瘤空间药代动力学建模的web应用程序。
定量了解药物在人类中枢神经系统和脑肿瘤中的渗透和暴露,对于合理开发新的脑癌药物和优化现有药物的使用至关重要。为了满足这一需求,我们开发并验证了一种新的基于9室渗透性有限的中枢神经系统(9-CNS)生理的药代动力学(PBPK)模型,能够对系统给药的小分子药物在人类大脑、脑脊液和脑肿瘤的不同区域的空间药代动力学进行机制和定量预测。为了使9-CNS模型能够被更广泛的用户访问,我们开发了SpatialCNS-PBPK应用程序,这是一个基于R和Shiny编程的用户友好的基于web的R/Shiny平台。该应用程序提供了模型模拟,灵敏度分析和药代动力学参数计算的关键功能。本教程介绍了SpatialCNS-PBPK应用程序的开发和评估,重点介绍了其主要特性和功能,并为实际应用提供了一步一步的用户指南。通过提高我们预测抗癌药物在人类中枢神经系统和脑肿瘤中的空间药代动力学的能力,SpatialCNS-PBPK应用程序作为一种宝贵的计算工具和数据驱动的方法,促进药物开发和优化治疗策略,以更有效地治疗脑癌。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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