Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles

Abstract The pharmacokinetics of nanoparticle-borne drugs targeting tumors depends critically on nanoparticle design. Empirical approaches to evaluate such designs in order to maximize treatment efficacy are time- and cost-intensive. We have recently proposed the use of computational modeling of nan...

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Autores principales:	Ibrahim M. Chamseddine, Hermann B. Frieboes, Michael Kokkolaras
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8a0167d8fb7d4229940e465c3c64bf84
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spelling	oai:doaj.org-article:8a0167d8fb7d4229940e465c3c64bf842021-12-02T14:59:13ZMulti-objective optimization of tumor response to drug release from vasculature-bound nanoparticles10.1038/s41598-020-65162-22045-2322https://doaj.org/article/8a0167d8fb7d4229940e465c3c64bf842020-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-65162-2https://doaj.org/toc/2045-2322Abstract The pharmacokinetics of nanoparticle-borne drugs targeting tumors depends critically on nanoparticle design. Empirical approaches to evaluate such designs in order to maximize treatment efficacy are time- and cost-intensive. We have recently proposed the use of computational modeling of nanoparticle-mediated drug delivery targeting tumor vasculature coupled with numerical optimization to pursue optimal nanoparticle targeting and tumor uptake. Here, we build upon these studies to evaluate the effect of tumor size on optimal nanoparticle design by considering a cohort of heterogeneously-sized tumor lesions, as would be clinically expected. The results indicate that smaller nanoparticles yield higher tumor targeting and lesion regression for larger-sized tumors. We then augment the nanoparticle design optimization problem by considering drug diffusivity, which yields a two-fold tumor size decrease compared to optimizing nanoparticles without this consideration. We quantify the tradeoff between tumor targeting and size decrease using bi-objective optimization, and generate five Pareto-optimal nanoparticle designs. The results provide a spectrum of treatment outcomes – considering tumor targeting vs. antitumor effect – with the goal to enable therapy customization based on clinical need. This approach could be extended to other nanoparticle-based cancer therapies, and support the development of personalized nanomedicine in the longer term.Ibrahim M. ChamseddineHermann B. FrieboesMichael KokkolarasNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ibrahim M. Chamseddine Hermann B. Frieboes Michael Kokkolaras Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
description	Abstract The pharmacokinetics of nanoparticle-borne drugs targeting tumors depends critically on nanoparticle design. Empirical approaches to evaluate such designs in order to maximize treatment efficacy are time- and cost-intensive. We have recently proposed the use of computational modeling of nanoparticle-mediated drug delivery targeting tumor vasculature coupled with numerical optimization to pursue optimal nanoparticle targeting and tumor uptake. Here, we build upon these studies to evaluate the effect of tumor size on optimal nanoparticle design by considering a cohort of heterogeneously-sized tumor lesions, as would be clinically expected. The results indicate that smaller nanoparticles yield higher tumor targeting and lesion regression for larger-sized tumors. We then augment the nanoparticle design optimization problem by considering drug diffusivity, which yields a two-fold tumor size decrease compared to optimizing nanoparticles without this consideration. We quantify the tradeoff between tumor targeting and size decrease using bi-objective optimization, and generate five Pareto-optimal nanoparticle designs. The results provide a spectrum of treatment outcomes – considering tumor targeting vs. antitumor effect – with the goal to enable therapy customization based on clinical need. This approach could be extended to other nanoparticle-based cancer therapies, and support the development of personalized nanomedicine in the longer term.
format	article
author	Ibrahim M. Chamseddine Hermann B. Frieboes Michael Kokkolaras
author_facet	Ibrahim M. Chamseddine Hermann B. Frieboes Michael Kokkolaras
author_sort	Ibrahim M. Chamseddine
title	Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
title_short	Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
title_full	Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
title_fullStr	Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
title_full_unstemmed	Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
title_sort	multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/8a0167d8fb7d4229940e465c3c64bf84
work_keys_str_mv	AT ibrahimmchamseddine multiobjectiveoptimizationoftumorresponsetodrugreleasefromvasculatureboundnanoparticles AT hermannbfrieboes multiobjectiveoptimizationoftumorresponsetodrugreleasefromvasculatureboundnanoparticles AT michaelkokkolaras multiobjectiveoptimizationoftumorresponsetodrugreleasefromvasculatureboundnanoparticles
_version_	1718389213069574144

Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles

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