In-vitro tumor microenvironment models containing physical and biological barriers for modelling multidrug resistance mechanisms and multidrug delivery strategies.

The complexity and heterogeneity of the three-dimensional (3D) tumor microenvironment have brought challenges to tumor studies and cancer treatment. The complex functions and interactions of cells involved in tumor microenvironment have led to various multidrug resistance (MDR) and raised challenges for cancer treatment. Traditional tumor models are limited in their ability to simulate the resistance mechanisms and not conducive to the discovery of multidrug resistance and delivery processes. New technologies for making 3D tissue models have shown the potential to simulate the 3D tumor microenvironment and identify mechanisms underlying the MDR. This review overviews the main barriers against multidrug delivery in the tumor microenvironment and highlights the advances in microfluidic-based tumor models with the success in simulating several drug delivery barriers. It also presents the progress in modeling various genetic and epigenetic factors involved in regulating the tumor microenvironment as a noticeable insight in 3D microfluidic tumor models for recognizing multidrug resistance and delivery mechanisms. Further correlation between the results obtained from microfluidic drug resistance tumor models and the clinical MDR data would open up avenues to gain insight into the performance of different multidrug delivery treatment strategies.

Mathematical and computational modeling of nano-engineered drug delivery systems.

While the advent of nano-engineered drug delivery systems (DDSs) has revived hopes for better management of a wide range of pathologies, critical appraisal of the field has shown that further improvement of nanomedicine demands a paradigmatic shift in design and development approaches currently employed by drug developers. In this review, we portray various theoretical modeling frameworks as influential tools to furnish future design and development of DDSs. The rational design of nanomedicines should be premised on taking into account the sui generis nature of DDSs within a multiplex biological milieu in vivo. Technical limitations, however, remain a bottleneck to the faithful reconstruction of such biomimetic models. Computational and mathematical modeling tools have shown potential as a promising technique to broaden the horizon of nanomedicine by addressing blind spots of current empirical models. Through integration with modern imaging and microfluidic technologies, in silico modeling is expected to expedite the clinical translation of nanomedicine.

Magnetic aerosol drug targeting in lung cancer therapy using permanent magnet.

Primary bronchial cancer accounts for almost 20% of all cancer death worldwide. One of the emerging techniques with tremendous power for lung cancer therapy is magnetic aerosol drug targeting (MADT). The use of a permanent magnet for effective drug delivery in a desired location throughout the lung requires extensive optimization, but it has not been addressed yet. In the present study, the possibility of using a permanent magnet for trapping the particles on a lung tumor is evaluated numerically in the Weibel's model from G0 to G3. The effect of different parameters is considered on the efficiency of particle deposition in a tumor located on a distant position of the lung bronchi and bronchioles. Also, the effective position of the magnetic source, tumor size, and location are the objectives for particle deposition. The results show that a limited particle deposition occurs on the lung branches in passive targeting. However, the incorporation of a permanent magnet next to the tumor enhanced the particle deposition fraction on G2 to up to 49% for the particles of 7 µm diameter. Optimizing the magnet size could also improve the particle deposition fraction by 68%. It was also shown that the utilization of MADT is essential for effective drug delivery to the tumors located on the lower wall of airway branches given the dominance of the air velocity and resultant drag force in this region. The results demonstrated the high competence and necessity of MADT as a noninvasive drug delivery method for lung cancer therapy.

Mathematical Modeling of the Function of Warburg Effect in Tumor Microenvironment.

Tumor cells are known for their increased glucose uptake rates even in the presence of abundant oxygen. This altered metabolic shift towards aerobic glycolysis is known as the Warburg effect. Despite an enormous number of studies conducted on the causes and consequences of this phenomenon, little is known about how the Warburg effect affects tumor growth and progression. We developed a multi-scale computational model to explore the detailed effects of glucose metabolism of cancer cells on tumorigenesis behavior in a tumor microenvironment. Despite glycolytic tumors, the growth of non-glycolytic tumor is dependent on a congruous morphology without markedly interfering with glucose and acid concentrations of the tumor microenvironment. Upregulated glucose metabolism helped to retain oxygen levels above the hypoxic limit during early tumor growth, and thus obviated the need for neo-vasculature recruitment. Importantly, simulating growth of tumors within a range of glucose uptake rates showed that there exists a spectrum of glucose uptake rates within which the tumor is most aggressive, i.e. it can exert maximal acidic stress on its microenvironment and most efficiently compete for glucose supplies. Moreover, within the same spectrum, the tumor could grow to invasive morphologies while its size did not markedly shrink.

Magnetically assisted intraperitoneal drug delivery for cancer chemotherapy.

Intraperitoneal (IP) chemotherapy has revived hopes during the past few years for the management of peritoneal disseminations of digestive and gynecological cancers. Nevertheless, a poor drug penetration is one key drawback of IP chemotherapy since peritoneal neoplasms are notoriously resistant to drug penetration. Recent preclinical studies have focused on targeting the aberrant tumor microenvironment to improve intratumoral drug transport. However, tumor stroma targeting therapies have limited therapeutic windows and show variable outcomes across different cohort of patients. Therefore, the development of new strategies for improving the efficacy of IP chemotherapy is a certain need. In this work, we propose a new magnetically assisted strategy to elevate drug penetration into peritoneal tumor nodules and improve IP chemotherapy. A computational model was developed to assess the feasibility and predictability of the proposed active drug delivery method. The key tumor pathophysiology, including a spatially heterogeneous construct of leaky vasculature, nonfunctional lymphatics, and dense extracellular matrix (ECM), was reconstructed in silico. The transport of intraperitoneally injected magnetic nanoparticles (MNPs) inside tumors was simulated and compared with the transport of free cytotoxic agents. Our results on magnetically assisted delivery showed an order of magnitude increase in the final intratumoral concentration of drug-coated MNPs with respect to free cytotoxic agents. The intermediate MNPs with the radius range of 200-300 nm yield optimal magnetic drug targeting (MDT) performance in 5-10 mm tumors while the MDT performance remains essentially the same over a large particle radius range of 100-500 nm for a 1 mm radius small tumor. The success of MDT in larger tumors (5-10 mm in radius) was found to be markedly dependent on the choice of magnet strength and tumor-magnet distance while these two parameters were less of a concern in small tumors. We also validated in silico results against experimental results related to tumor interstitial hypertension, conventional IP chemoperfusion, and magnetically actuated movement of MNPs in excised tissue.

Translational models of tumor angiogenesis: A nexus of in silico and in vitro models.

Emerging evidence shows that endothelial cells are not only the building blocks of vascular networks that enable oxygen and nutrient delivery throughout a tissue but also serve as a rich resource of angiocrine factors. Endothelial cells play key roles in determining cancer progression and response to anti-cancer drugs. Furthermore, the endothelium-specific deposition of extracellular matrix is a key modulator of the availability of angiocrine factors to both stromal and cancer cells. Considering tumor vascular network as a decisive factor in cancer pathogenesis and treatment response, these networks need to be an inseparable component of cancer models. Both computational and in vitro experimental models have been extensively developed to model tumor-endothelium interactions. While informative, they have been developed in different communities and do not yet represent a comprehensive platform. In this review, we overview the necessity of incorporating vascular networks for both in vitro and in silico cancer models and discuss recent progresses and challenges of in vitro experimental microfluidic cancer vasculature-on-chip systems and their in silico counterparts. We further highlight how these two approaches can merge together with the aim of presenting a predictive combinatorial platform for studying cancer pathogenesis and testing the efficacy of single or multi-drug therapeutics for cancer treatment.

Delivery of magnetic micro/nanoparticles and magnetic-based drug/cargo into arterial flow for targeted therapy.

Magnetic drug targeting (MDT) and magnetic-based drug/cargo delivery are emerging treatment methods which attracting the attention of many researchers for curing different cancers and artery diseases such as atherosclerosis. Herein, computational studies are accomplished by utilizing magnetic approaches for cancer and artery atherosclerosis drug delivery, including nanomagnetic drug delivery and magnetic-based drug/cargo delivery. For the first time, the four-layer structural model of the artery tissue and its porosity parameters are modeled in this study which enables the interaction of particles with the tissue walls in blood flow. The effects of parameters, including magnetic field strength (MFS), magnet size, particle size, the initial position of particles, and the relative magnetic permeability of particles, on the efficacy of MDT through the artery walls are characterized. The magnetic particle penetration into artery layers and fibrous cap (the covering layer over the inflamed part of the artery) is further simulated. The MDT in healthy and diseased arteries demonstrates that some of the particles stuck in these tissues due to the collision of particles or blood flow deviation in the vicinity of the inflamed part of the artery. Therefore the geometry of artery and porosity of its layers should be considered to show the real interaction of particles with the artery walls. Also, the results show that increasing the particles/drug/cargo size and MFS leads to more particles/drug/cargo retention within the tissue. The present work provides insights into the decisive factors in arterial MDT with an obvious impact on locoregional cancer treatment, tissue engineering, and regenerative medicine.