Direct nanodrug delivery for tumor targeting subject to shear-augmented diffusion in blood flow

Advancing Cancer Drug Delivery with Nanoparticles: Challenges and Prospects in Mathematical Modeling for In Vivo and In Vitro Systems

Mathematical models are crucial for predicting the behavior of drug conjugate nanoparticles and optimizing drug delivery systems in cancer therapy. These models simulate interactions among nanoparticle properties, tumor characteristics, and physiological conditions, including drug resistance and targeting specificity. However, they often rely on assumptions that may not accurately reflect in vivo conditions. In vitro studies, while useful, may not fully capture the complexities of the in vivo environment, leading to an overestimation of nanoparticle-based therapy effectiveness. Advancements in mathematical modeling, supported by preclinical data and artificial intelligence, are vital for refining nanoparticle-based therapies and improving their translation into effective clinical treatments.

Lagrangian flow networks for passive dispersal: Tracers versus finite-size particles

The transport and distribution of organisms such as larvae, seeds, or litter in the ocean as well as particles in industrial flows is often approximated by a transport of tracer particles. We present a theoretical investigation to check the accuracy of this approximation by studying the transport of inertial particles between different islands embedded in an open hydrodynamic flow aiming at the construction of a Lagrangian flow network reflecting the connectivity between the islands. To this end, we formulate a two-dimensional kinematic flow field which allows the placement of an arbitrary number of islands at arbitrary locations in a flow of prescribed direction. To account for the mixing in the flow, we include a von Kármán vortex street in the wake of each island. We demonstrate that the transport probabilities of inertial particles making up the links of the Lagrangian flow network essentially depend on the properties of the particles, i.e., their Stokes number, the properties of the flow, and the geometry of the setup of the islands. We find a strong segregation between aerosols and bubbles. Upon comparing the mobility of inertial particles to that of tracers or neutrally buoyant particles, it becomes apparent that the tracer approximation may not always accurately predict the probability of movement. This can lead to inconsistent forecasts regarding the fate of marine organisms, seeds, litter, or particles in industrial flows.

An Updated Review on EPR-Based Solid Tumor Targeting Nanocarriers for Cancer Treatment

The enhanced permeability and retention (EPR) effect in cancer treatment is one of the key mechanisms that enables drug accumulation at the tumor site. However, despite a plethora of virus/inorganic/organic-based nanocarriers designed to rely on the EPR effect to effectively target tumors, most have failed in the clinic. It seems that the non-compliance of research activities with clinical trials, goals unrelated to the EPR effect, and lack of awareness of the impact of solid tumor structure and interactions on the performance of drug nanocarriers have intensified this dissatisfaction. As such, the asymmetric growth and structural complexity of solid tumors, physicochemical properties of drug nanocarriers, EPR analytical combination tools, and EPR description goals should be considered to improve EPR-based cancer therapeutics. This review provides valuable insights into the limitations of the EPR effect in therapeutic efficacy and reports crucial perspectives on how the EPR effect can be modulated to improve the therapeutic effects of nanomedicine.

FEM based simulation of magnetic drug targeting in a multibranched vessel model

BACKGROUND AND OBJECTIVE

Magnetic drug targeting (MDT) is a promising technology to improve cancer therapy. MDT describes the accumulation of drug loaded superparamagnetic iron oxide nanoparticles (SPIONs) at a desired location, e. g. a tumor, by application of a magnetic field. Here, we evaluate the effectivity of MDT for an endoscopic placement of two different configurations of magnet arrays, i. e. six magnets with same poles facing each other and a Halbach array. Compared to conventional magnet setups outside the body, this endoscopic placement gives the possibility to achieve higher magnetic field gradients inside the tumor.

METHODS

For such a MDT concept, we present FEM based simulations of MDT tracing single SPIONs in a 3D geometry of eight multibranched vessels with sizes in the range of capillaries. In these simulations, the effect of the magnetic field gradient as well as of magnet distance to the vessel geometry, magnetic flux density of the magnets, SPIONs hydrodynamic diameter and magnetic moment on the MDT effectivity is calculated. The blood flow is modelled as an incompressible Newtonian fluid and the SPIONs are suspended in the blood flow. Statistical significance of the targeting effectivity results is tested with the Mann-Whitney-U-Test.

RESULTS

The results show that the magnetic targeting effectivity is up to 32 % higher than the one calculated without the presence of a magnetic field. In the investigated vessel network, this effect on the targeting effectivity is dependent on the number of local magnetic field maxima that are approached with a high gradient and is noticeable up to 200 µm distance of the magnet to the vessel geometry.

CONCLUSIONS

We conclude that for an effective application of MDT, the magnet configuration needs to be placed close to the tumor and should yield a large number of magnetic field maxima that are approached with a high gradient.

Investigating the Effect of Aging on the Pharmacokinetics and Tumor Delivery of Nanomaterials using Mathematical Modeling

The application of nanomedicine for diagnosis and treatment of cancer has immense potential, but has witnessed only limited clinical success, in part due to insufficient understanding of the role of nanomaterial properties and physiological variables in governing nanoparticle (NP) pharmacology. Here, we present a multiscale mathematical model to examine the effects of physiological changes associated with patient age on the pharmacokinetics and tumor delivery efficiency of NPs. We show that physiological changes due to aging prolong the residence of NPs in the systemic circulation, thereby improving passive accumulation of NPs in tumors.Clinical Relevance - Understanding the effect of inter-individual variability on the pharmacological behavior of nanomaterials will improve their clinical translatability.

Multiple Particle Manipulation under Dielectrophoresis Effect: Modeling and Experiments

The dissipative particle dynamics (DPD) technique was employed to design multiple microfluidic devices for investigating the motion of bioparticles at low Reynolds numbers. A DPD in-house FORTRAN code was developed to simulate the trajectories of two microparticles in the presence of hydrodynamic and transverse deflecting force fields via considering interparticle interaction forces. The particle-particle interactions were described by using a simplified version of the Morse potential. The transverse deflecting force considered in this microfluidic application was the dielectrophoresis (DEP) force. Multiple microfluidic devices with different configurations of microelectrodes were numerically designed to investigate the dielectrophoretic behavior of bioparticles for their trajectories and the focusing of bioparticles into a single stream in the middle of the microchannel. The DPD simulation results were verified and validated against previously reported numerical and experimental works in the literature. The computationally designed microdevices were fabricated by employing standard lithographic techniques, and experiments were conducted via taking red blood cells as the representative bioparticles. The experimental results for the trajectories and focusing showed good agreement with the numerical results.

A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery

Towards clinical translation of cancer nanomedicine, it is important to systematically investigate the various parameters related to nanoparticle (NP) physicochemical properties, tumor characteristics, and inter-individual variability that affect the tumor delivery efficiency of therapeutic nanomaterials. Comprehensive investigation of these parameters using traditional experimental approaches is impractical due to the vast parameter space; mathematical models provide a more tractable approach to navigate through such a multidimensional space. To this end, we have developed a predictive mathematical model of whole-body NP pharmacokinetics and their tumor delivery in vivo, and have conducted local and global sensitivity analyses to identify the factors that result in low tumor delivery efficiency and high off-target accumulation of NPs. Our analyses reveal that NP degradation rate, tumor blood viscosity, NP size, tumor vascular fraction, and tumor vascular porosity are the key parameters in governing NP kinetics in the tumor interstitium. The impact of these parameters on tumor delivery efficiency of NPs is discussed, and optimal values for maximizing NP delivery are presented.

Peristaltic Blood Flow of Couple Stress Fluid Suspended with Nanoparticles under the Influence of Chemical Reaction and Activation Energy

The present study gives a remedy for the malign tissues, cells, or clogged arteries of the heart by means of permeating a slim tube (i.e., catheter) in the body. The tiny size gold particles drift in free space of catheters having flexible walls with couple stress fluid. To improve the efficiency of curing and speed up the process, activation energy has been added to the process. The modified Arrhenius function and Buongiorno model, respectively, moderate the inclusion of activation energy and nanoparticles of gold. The effects of chemical reaction and activation energy on peristaltic transport of nanofluids are also taken into account. It is found that the golden particles encapsulate large molecules to transport essential drugs efficiently to the effected part of the organ.

Heterogeneous blood flow in microvessels with applications to nanodrug transport and mass transfer into tumor tissue

Nanodrug transport in tumor microvasculature and deposition/extravasation into tumor tissue are an important link in the nanodrug delivery process. Considering heterogeneous blood flow, such a dual process is numerically studied. The hematocrit distribution is solved by directly considering the forces experienced by the red blood cells (RBCs), i.e., the wall lift force and the random cell collision force. Using a straight microvessel as a test bed, validated computer simulations are performed to determine blood flow characteristics as well as the resulting nanodrug distribution and extravasation. The results confirm that RBCs migrate away from the vessel wall, leaving a cell-free layer (CFL). Nanodrug particles tend to preferentially accumulate in the CFL, leading to increased concentration near the endothelial surface layer. However, shear-induced NP diffusion is diminished within the CFL, causing to a much slower lateral transport rate into tumor tissue. These competing effects determine the NP deposition/extravasation rates. The present modeling framework and NP flux results provide new physical insight. The analysis can be readily extended to simulations of NP transport in blood microvessels of actual tumors.