Date

2022-09-19

Author

Akalın, Ali Aykut
Özçelikkale, Altuğ

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Despite significant advances in recent decades, diagnosis and treatment of cancer remain to be a major challenge. Advances in nanotechnology have enabled numerous nanoparticle (NP) formulations for efficient delivery of drugs and diagnostic agents to the target tumor site. The size, shape, charge, and surface characteristics of so-called nanomedicine can be tuned to affect the interactions of the NP with the physiological environment [1]. However, design efforts to develop nanomedicine for efficient delivery to tumor is complicated by a lack of clear understanding of NP transport characteristics. NP delivery is a multistage process that involves the transport of NPs across tissue-tissue interfaces such as the vascular wall as well as within tumor interstitium where NP transport can be hindered by various physiological barriers posed by the tumor microenvironment such as high interstitial fluid pressure and dense extracellular matrix ECM [2,3]. In particular, the relationships between NP design characteristics, tumor microstructure, and NP advective and diffusive transport across tumor tissue are not widely available and need to be established. To address this challenge, this study adopts an integrative approach that involves computational modeling and characterization of NP transport at two distinct length/time scales [4]. In particular, hydraulic conductivity, effective diffusivity, and retardation of NPs in collagen ECM are estimated for varying NP design characteristics, tissue microstructure, and interstitial flow conditions based on (i) microscale modeling of fluid flow, Brownian dynamics of NPs, and particle-fluid-structure interactions within the fibrous interstitial space, (ii) continuum modeling of fluid and NP transport within porous media and fitting of the model to spatiotemporal NP concentration measured on a microfluidic model of tumor ECM. The transport properties estimated by computational and experimental methodologies are compared for validation of the integrative approach. It is anticipated that the findings of this study will be ultimately useful in advancing rational design of nanomedicine for tumor delivery.References:[1] Ozcelikkale, A., Ghosh, S. & Han, B. Multifaceted Transport Characteristics of Nanomedicine: Needs for Characterization in Dynamic Environment. Mol Pharm 10, 2111–2126 (2013).[2] Stillman, N. R., Kovacevic, M., Balaz, I. & Hauert, S. In silico modelling of cancer nanomedicine, across scales and transport barriers. npj Comput Mater 6, 92 (2020).[3] Chrastina, A., Massey, K. A. & Schnitzer, J. E. Overcoming in vivo barriers to targeted nanodelivery. Wiley Interdisciplinary Reviews-Nanomedicine and Nanobiotechnology 3, 421–437 (2011).[4] Akalın, A. A., Dedekargınoğlu, B., Choi, S. R., Han, B. & Ozcelikkale, A. Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty. Pharm Res (2022) doi:10.1007/s11095-022-03298-8.

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https://nanotr.org/en/
https://hdl.handle.net/11511/98956

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Department of Mechanical Engineering, Conference / Seminar