Modelling the Transport of Nanoparticles under Blood Flow using an Agent-based Approach

Blood-mediated nanoparticle delivery is a new and growing field in the development of therapeutics and diagnostics. Nanoparticle properties such as size, shape and surface chemistry can be controlled to improve their performance in biological systems. This enables modulation of immune system interactions, blood clearance profile and interaction with target cells, thereby aiding effective delivery of cargo within cells or tissues. Their ability to target and enter tissues from the blood is highly dependent on their behaviour under blood flow. Here we have produced an agent-based model of nanoparticle behaviour under blood flow in capillaries. We demonstrate that red blood cells are highly important for effective nanoparticle distribution within capillaries. Furthermore, we use this model to demonstrate how nanoparticle size can selectively target tumour tissue over normal tissue. We demonstrate that the polydispersity of nanoparticle populations is an important consideration in achieving optimal specificity and to avoid off-target effects. In future this model could be used for informing new nanoparticle design and to predict general and specific uptake properties under blood flow.

[1]  Erkki Ruoslahti,et al.  Tissue-penetrating delivery of compounds and nanoparticles into tumors. , 2009, Cancer cell.

[2]  Guillermo Hauke,et al.  a Unified Approach to Compressible and Incompressible Flows and a New Entropy-Consistent Formulation of the K - Model. , 1994 .

[3]  S M Moghimi,et al.  Long-circulating and target-specific nanoparticles: theory to practice. , 2001, Pharmacological reviews.

[4]  Jun Fang,et al.  The EPR effect: Unique features of tumor blood vessels for drug delivery, factors involved, and limitations and augmentation of the effect. , 2011, Advanced drug delivery reviews.

[5]  Hui Yang,et al.  Virtual screening and optimization of Type II inhibitors of JAK2 from a natural product library. , 2014, Chemical communications.

[6]  H. Maeda,et al.  Tumor vascular permeability and the EPR effect in macromolecular therapeutics: a review. , 2000, Journal of controlled release : official journal of the Controlled Release Society.

[7]  M. E. Muller,et al.  A Note on the Generation of Random Normal Deviates , 1958 .

[8]  David A. Steinman,et al.  Image-Based Computational Fluid Dynamics Modeling in Realistic Arterial Geometries , 2002, Annals of Biomedical Engineering.

[9]  V. V. Kleandrova,et al.  Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents. , 2012, Bioorganic & medicinal chemistry.

[10]  R. Skalak,et al.  Deformation of Red Blood Cells in Capillaries , 1969, Science.

[11]  J. McWhirter,et al.  Flow-induced clustering and alignment of vesicles and red blood cells in microcapillaries , 2009, Proceedings of the National Academy of Sciences.

[12]  R. Wells,et al.  Influence of Deformability of Human Red Cells upon Blood Viscosity , 1969, Circulation research.

[13]  M Ferrari,et al.  The adhesive strength of non-spherical particles mediated by specific interactions. , 2006, Biomaterials.

[14]  Erkki Ruoslahti,et al.  Coadministration of a Tumor-Penetrating Peptide Enhances the Efficacy of Cancer Drugs , 2010, Science.

[15]  Mariam Kiran,et al.  An Approach to the Parallelisation of Agent-Based Applications , 2010, ERCIM News.

[16]  Ferran Sanz,et al.  A Multiscale Simulation System for the Prediction of Drug-Induced Cardiotoxicity , 2011, J. Chem. Inf. Model..

[17]  Jiaqi Lin,et al.  Penetration of lipid membranes by gold nanoparticles: insights into cellular uptake, cytotoxicity, and their relationship. , 2010, ACS nano.

[18]  L. Perlemuter [From theory to practice]. , 1997, Soins. Psychiatrie.

[19]  H. Maeda,et al.  Exploiting the enhanced permeability and retention effect for tumor targeting. , 2006, Drug discovery today.

[20]  Mark E. Davis,et al.  Nanoparticle therapeutics: an emerging treatment modality for cancer , 2008, Nature Reviews Drug Discovery.

[21]  V. Ginzburg,et al.  Modeling the thermodynamics of the interaction of nanoparticles with cell membranes. , 2007, Nano letters.

[22]  Nicholas A Peppas,et al.  Opsonization, biodistribution, and pharmacokinetics of polymeric nanoparticles. , 2006, International journal of pharmaceutics.

[23]  D. Bazile,et al.  Effect of PEO surface density on long-circulating PLA-PEO nanoparticles which are very low complement activators. , 1996, Biomaterials.

[24]  Robert C. Wolpert,et al.  A Review of the , 1985 .

[25]  D. Gebauer,et al.  Hydration-driven transport of deformable lipid vesicles through fine pores and the skin barrier. , 2003, Biophysical journal.

[26]  Kazunori Kataoka,et al.  PEGylated nanoparticles for biological and pharmaceutical applications. , 2003, Advanced drug delivery reviews.

[27]  D. Bray,et al.  Stochastic simulation of chemical reactions with spatial resolution and single molecule detail , 2004, Physical biology.

[28]  Aleksander S Popel,et al.  Red blood cell aggregation and dissociation in shear flows simulated by lattice Boltzmann method. , 2008, Journal of biomechanics.

[29]  E. Merrill,et al.  Influence of flow properties of blood upon viscosity-hematocrit relationships. , 1962, The Journal of clinical investigation.

[30]  Eric Pridgen,et al.  Factors Affecting the Clearance and Biodistribution of Polymeric Nanoparticles , 2008, Molecular pharmaceutics.

[31]  J. McWhirter,et al.  Deformation and clustering of red blood cells in microcapillary flows , 2011 .

[32]  R. Weissleder,et al.  A long-circulating co-polymer in "passive targeting" to solid tumors. , 1997, Journal of drug targeting.

[33]  E. Kinney Primer of Biostatistics , 1987 .

[34]  G. Palade,et al.  Surface Densities of Diaphragmed Fenestrae and Transendothelial Channels in Different Murine Capillary Beds , 1985, Circulation research.

[35]  Samir Mitragotri,et al.  Long Circulating Nanoparticles via Adhesion on Red Blood Cells: Mechanism and Extended Circulation , 2007, Experimental biology and medicine.

[36]  J. Auwerx,et al.  Novel potent and selective bile acid derivatives as TGR5 agonists: biological screening, structure-activity relationships, and molecular modeling studies. , 2008, Journal of medicinal chemistry.

[37]  Antony Thomas,et al.  Influence of Red Blood Cells on Nanoparticle Targeted Delivery in Microcirculation. , 2011, Soft matter.

[38]  S. MacNeil,et al.  Translocation of flexible polymersomes across pores at the nanoscale. , 2014, Biomaterials science.

[39]  Sara Linse,et al.  Understanding the nanoparticle–protein corona using methods to quantify exchange rates and affinities of proteins for nanoparticles , 2007, Proceedings of the National Academy of Sciences.

[40]  Gerhard Gompper,et al.  Deformation and dynamics of red blood cells in flow through cylindrical microchannels. , 2014, Soft matter.

[41]  K. Katada,et al.  Magnitude and Role of Wall Shear Stress on Cerebral Aneurysm: Computational Fluid Dynamic Study of 20 Middle Cerebral Artery Aneurysms , 2004, Stroke.

[42]  L. Zhang,et al.  Nanoparticles in Medicine: Therapeutic Applications and Developments , 2008, Clinical pharmacology and therapeutics.

[43]  Kenneth A. Dawson,et al.  Nanoparticle size and surface properties determine the protein corona with possible implications for biological impacts , 2008, Proceedings of the National Academy of Sciences.

[44]  Robert E. Knop Remark on algorithm 334 [G5]: normal random deviates , 1969, CACM.

[45]  R. Abagyan,et al.  Structure-based discovery of natural-product-like TNF-α inhibitors. , 2010, Angewandte Chemie.

[46]  Hans Vink,et al.  The Endothelial Glycocalyx Protects Against Myocardial Edema , 2003, Circulation research.

[47]  G. Biros,et al.  Why do red blood cells have asymmetric shapes even in a symmetric flow? , 2009, Physical review letters.