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Physiologically Based Pharmacokinetic Modeling of Nanoparticles.
Yuan, Dongfen; He, Hua; Wu, Yun; Fan, Jianghong; Cao, Yanguang.
Afiliación
  • Yuan D; Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599.
  • He H; China Pharmaceutical University, Nanjing, China.
  • Wu Y; Department of Biomedical Engineering, University at Buffalo, The State University of New York, 332 Bonner Hall, Buffalo, New York 14260.
  • Fan J; Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993.
  • Cao Y; Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599. Electron
J Pharm Sci ; 108(1): 58-72, 2019 Jan.
Article en En | MEDLINE | ID: mdl-30385282
ABSTRACT
Nanoparticles are frequently designed to improve the pharmacokinetics profiles and tissue distribution of small molecules to prolong their systemic circulation, target specific tissue, or widen the therapeutic window. The multifunctionality of nanoparticles is frequently presented as an advantage but also results in distinct and complicated in vivo disposition properties compared with a conventional formulation of the same molecules. Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool in characterizing and predicting the systemic disposition, target exposure, and efficacy and toxicity of various types of drugs when coupled with pharmacodynamic modeling. Here we review the unique disposition characteristics of nanoparticles, assess how PBPK modeling takes into account the unique disposition properties of nanoparticles, and comment on the applications and challenges of PBPK modeling in characterizing and predicting the disposition and biological effects of nanoparticles.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Nanopartículas Tipo de estudio: Prognostic_studies Idioma: En Revista: J Pharm Sci Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Nanopartículas Tipo de estudio: Prognostic_studies Idioma: En Revista: J Pharm Sci Año: 2019 Tipo del documento: Article