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

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.

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Publication Details

Journal
CPT Pharmacometrics & Systems Pharmacology
Published
2025-04-04
DOI
https://doi.org/10.1002/psp4.70026
Citations
1
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.63

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article

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

Jing Li, Charuka D. Wickramasinghe, Seongho Kim
1 citations
CPT Pharmacometrics & Systems Pharmacology
Glioma Diagnosis and Treatment
1.63
article

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

Jing Li, Charuka D. Wickramasinghe, Seongho Kim
article en
1 citations

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.

CPT Pharmacometrics & Systems PharmacologyVol. 14(5)
Wayne State University (US), The Barbara Ann Karmanos Cancer Institute (US)
Barbara Ann Karmanos Cancer Institute, National Institutes of Health, National Cancer Institute
Good health and well-being
Openalex Percentile: Top 19%
Glioma Diagnosis and Treatment
1.63
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