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Data-Driven Modeling of the Cellular Pharmacokinetics of Degradable Chitosan-Based Nanoparticles

Huw Summers Orcid Logo, Carla P. Gomes, Aida Varela-Moreira, Ana P. Spencer, Maria Gomez-Lazaro, Ana P. Pêgo, Paul Rees Orcid Logo

Nanomaterials, Volume: 11, Issue: 10, Start page: 2606

Swansea University Authors: Huw Summers Orcid Logo, Paul Rees Orcid Logo

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DOI (Published version): 10.3390/nano11102606

Abstract

Nanoparticle drug delivery vehicles introduce multiple pharmacokinetic processes, with the delivery, accumulation, and stability of the therapeutic molecule influenced by nanoscale processes. Therefore, considering the complexity of the multiple interactions, the use of data-driven models has critic...

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Published in: Nanomaterials
ISSN: 2079-4991
Published: MDPI AG 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58254
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Abstract: Nanoparticle drug delivery vehicles introduce multiple pharmacokinetic processes, with the delivery, accumulation, and stability of the therapeutic molecule influenced by nanoscale processes. 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 chitosan 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, τ = 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.
Keywords: nanoparticle dosimetry; pharmacokinetics; imaging flow cytometry; nanomedicine; drug delivery; data-driven models
College: College of Engineering
Funders: This research was funded by Portuguese funds through FCT/MCTES in the framework of the projects UID/BIM/04293/2013, UIDB/04293/2020, SFRH/BD/137073/2018, PTDC/CTMNAN/115124/2009, and by the UK Engineering and Physical Sciences Research Council under project EP/ /N013506/1
Issue: 10
Start Page: 2606