Alex Foster-Powell, Amin Rostami-Hodjegan, Guy Meno-Tetang, Donald E Mager, Kayode Ogungbenro
{"title":"Mathematical Modeling of Neuroinflammation in Neurodegenerative Diseases.","authors":"Alex Foster-Powell, Amin Rostami-Hodjegan, Guy Meno-Tetang, Donald E Mager, Kayode Ogungbenro","doi":"10.1002/psp4.70064","DOIUrl":null,"url":null,"abstract":"<p><p>Age-related neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD) and Parkinson's disease (PD) are an increasing public health concern. Whereas the pathology of these diseases is complex, chronic central inflammation, or neuroinflammation, is commonly observed across many neurodegenerative diseases. Despite a huge wealth of resources and promising preclinical testing, effective disease-modifying therapies do not exist. This failure is owing to a combination of poor biological understanding of this response, unsuitable animal models, and poor scaling from pathway up to clinical levels. In order to address these challenges, systems-level mathematical models may be utilized. Here, we provide a background on neuroinflammation and summarize available mathematical models of this response. Models described by ordinary, partial, and delay differential equations, and Boolean logic are introduced and discussed. The results as discussed in this review suggest logic-based modeling as a formalism capable of managing the challenges associated with the modeling of CNS diseases.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CPT: Pharmacometrics & Systems Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/psp4.70064","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Age-related neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD) and Parkinson's disease (PD) are an increasing public health concern. Whereas the pathology of these diseases is complex, chronic central inflammation, or neuroinflammation, is commonly observed across many neurodegenerative diseases. Despite a huge wealth of resources and promising preclinical testing, effective disease-modifying therapies do not exist. This failure is owing to a combination of poor biological understanding of this response, unsuitable animal models, and poor scaling from pathway up to clinical levels. In order to address these challenges, systems-level mathematical models may be utilized. Here, we provide a background on neuroinflammation and summarize available mathematical models of this response. Models described by ordinary, partial, and delay differential equations, and Boolean logic are introduced and discussed. The results as discussed in this review suggest logic-based modeling as a formalism capable of managing the challenges associated with the modeling of CNS diseases.