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Author(s): Summers, HD
Gomes, CP
Varela-Moreira, A
Spencer, AP
Gomez-Lazaro, M
Pêgo, AP
Rees, P
Title: Data-driven modeling of the cellular pharmacokinetics of degradable chitosan-based nanoparticles
Publisher: MDPI
Issue Date: 2021
Abstract: Nanoparticle drug delivery vehicles introduce multiple pharmacokinetic processes, with the delivery, accumulation, and stability of the therapeutic molecule influenced by nanoscale pro-cesses. Therefore, considering the complexity of the multiple interactions, the use of data-driven models has critical importance in understanding the interplay between controlling processes. We demonstrate data simulation techniques to reproduce the time-dependent dose of trimethyl chi-tosan nanoparticles in an ND7/23 neuronal cell line, used as an in vitro model of native peripheral sensory neurons. Derived analytical expressions of the mean dose per cell accurately capture the pharmacokinetics by including a declining delivery rate and an intracellular particle degradation process. Comparison with experiment indicates a supply time constant, t = 2 h. and a degradation rate constant, b = 0.71 h-1. Modeling the dose heterogeneity uses simulated data distributions, with time dependence incorporated by transforming data-bin values. The simulations mimic the dynamic nature of cell-to-cell dose variation and explain the observed trend of increasing numbers of high-dose cells at early time points, followed by a shift in distribution peak to lower dose between 4 to 8 h and a static dose profile beyond 8 h.
Subject: Data-driven models
Drug delivery
Imaging flow cytometry
Nanoparticle dosimetry
Source: Nanomaterials, vol.11(10):2606
Related Information: info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FBIM%2F04293%2F2013/PT
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04293%2F2020/PT
Document Type: Artigo em Revista Científica Internacional
Rights: openAccess
Appears in Collections:I3S - Artigo em Revista Científica Internacional

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