Numerical modeling of high-intensity focused ultrasound-mediated intraperitoneal delivery of thermosensitive liposomal doxorubicin for cancer chemotherapy

Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy

Personalised drug delivery enables a tailored treatment plan for each patient compared to conventional drug delivery, where a generic strategy is commonly employed. It can not only achieve precise treatment to improve effectiveness but also reduce the risk of adverse effects to improve patients' quality of life. Drug delivery involves multiple interconnected physiological and physicochemical processes, which span a wide range of time and length scales. How to consider the impact of individual differences on these processes becomes critical. Multiphysics models are an open system that allows well-controlled studies on the individual and combined effects of influencing factors on drug delivery outcomes while accommodating the patient-specific in vivo environment, which is not economically feasible through experimental means. Extensive modelling frameworks have been developed to reveal the underlying mechanisms of drug delivery and optimise effective delivery plans. This review provides an overview of currently available models, their integration with advanced medical imaging modalities, and code packages for personalised drug delivery. The potential to incorporate new technologies (i.e., machine learning) in this field is also addressed for development.

Improving tumor treatment through intratumoral injection of drug-loaded magnetic nanoparticles and low-intensity ultrasound

The intratumoral injection of therapeutic agents responsive to external stimuli has gained considerable interest in treating accessible tumors due to its biocompatibility and capacity to reduce side effects. For the first time, a novel approach is explored to investigate the feasibility of utilizing low-intensity ultrasound in combination with intratumoral injection of drug-loaded magnetic nanoparticles (MNPs) to thermal necrosis and chemotherapy with the objective of maximizing tumor damage while avoiding harm to surrounding healthy tissue. In this study, a mathematical framework is proposed based on a multi-compartment model to evaluate the effects of ultrasound transducer's specifications, MNPs size and distribution, and drug release in response to the tumor microenvironment characteristics. The results indicate that while a higher injection rate may increase interstitial fluid pressure, it also simultaneously enhances the concentration of the therapeutic agent. Moreover, by increasing the power and frequency of the transducer, the acoustic pressure and intensity can be enhanced. This, in turn, increases the impact on accumulated MNPs, resulting in a rise in temperature and localized heat generation. Results have demonstrated that smaller MNPs have a lower capacity to generate heat compared to larger MNPs, primarily due to the impact of sound waves on them. It is worth noting that smaller MNPs have been observed to have enhanced diffusion, allowing them to effectively spread within the tumor. However, their smaller size also leads to rapid elimination from the extracellular space into the bloodstream. To summarize, this study demonstrated that the local injection of MNPs carrying drugs not only enables localized chemotherapy but also enhances the effectiveness of low-intensity ultrasound in inducing tissue thermal necrosis. The findings of this study can serve as a valuable and reliable resource for future research in this field and contribute to the development of personalized medicine.

Ultrasound-mediated nano-sized drug delivery systems for cancer treatment: Multi-scale and multi-physics computational modeling

Computational modeling enables researchers to study and understand various complex biological phenomena in anticancer drug delivery systems (DDSs), especially nano-sized DDSs (NSDDSs). The combination of NSDDSs and therapeutic ultrasound (TUS), that is, focused ultrasound and low-intensity pulsed ultrasound, has made significant progress in recent years, opening many opportunities for cancer treatment. Multiple parameters require tuning and optimization to develop effective DDSs, such as NSDDSs, in which mathematical modeling can prove advantageous. In silico computational modeling of ultrasound-responsive DDS typically involves a complex framework of acoustic interactions, heat transfer, drug release from nanoparticles, fluid flow, mass transport, and pharmacodynamic governing equations. Owing to the rapid development of computational tools, modeling the different phenomena in multi-scale complex problems involved in drug delivery to tumors has become possible. In the present study, we present an in-depth review of recent advances in the mathematical modeling of TUS-mediated DDSs for cancer treatment. A detailed discussion is also provided on applying these computational models to improve the clinical translation for applications in cancer treatment. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Multi-Scale and Multi-Physics Models of the Transport of Therapeutic/Diagnostic Cancer Agents

The effectiveness of tumor treatment heavily relies on the successful delivery of anticancer drugs [...].

Stimuli-sensitive nano-drug delivery with programmable size changes to enhance accumulation of therapeutic agents in tumors

Nano-based drug delivery systems hold significant promise for cancer therapies. Presently, the poor accumulation of drug-carrying nanoparticles in tumors has limited their success. In this study, based on a combination of the paradigms of intravascular and extravascular drug release, an efficient nanosized drug delivery system with programmable size changes is introduced. Drug-loaded smaller nanoparticles (secondary nanoparticles), which are loaded inside larger nanoparticles (primary nanoparticles), are released within the microvascular network due to temperature field resulting from focused ultrasound. This leads to the scale of the drug delivery system decreasing by 7.5 to 150 times. Subsequently, smaller nanoparticles enter the tissue at high transvascular rates and achieve higher accumulation, leading to higher penetration depths. In response to the acidic pH of tumor microenvironment (according to the distribution of oxygen), they begin to release the drug doxorubicin at very slow rates (i.e., sustained release). To predict the performance and distribution of therapeutic agents, a semi-realistic microvascular network is first generated based on a sprouting angiogenesis model and the transport of therapeutic agents is then investigated based on a developed multi-compartment model. The results show that reducing the size of the primary and secondary nanoparticles can lead to higher cell death rate. In addition, tumor growth can be inhibited for a longer time by enhancing the bioavailability of the drug in the extracellular space. The proposed drug delivery system can be very promising in clinical applications. Furthermore, the proposed mathematical model is applicable to broader applications to predict the performance of drug delivery systems.

A comparative study between conventional chemotherapy and photothermal activated nano-sized targeted drug delivery to solid tumor

Delivery of chemotherapeutic medicines to solid tumors is critical for optimal therapeutic success and minimal adverse effects. We mathematically developed a delivery method using thermosensitive nanocarriers activated by light irradiation. To assess its efficacy and identify critical events and parameters affecting therapeutic response, we compared this method to bolus and continuous infusions of doxorubicin for both single and multiple administrations. A hybrid sprouting angiogenesis approach generates a semi-realistic microvascular network to evaluate therapeutic drug distribution and microvascular heterogeneity. A pharmacodynamics model evaluates treatment success based on tumor survival cell percentage. The study found that whereas bolus injection boosted extracellular drug concentration levels by 90%, continuous infusion improved therapeutic response due to improved bioavailability. Cancer cell death increases by 6% with several injections compared to single injections due to prolonged chemotherapeutic medication exposure. However, responsive nanocarriers supply more than 2.1 times more drug than traditional chemotherapy in extracellular space, suppressing tumor development longer. Also, controlled drug release decreases systemic side effects substantial through diminishing the concentration of free drug in the circulation. The primary finding of this work highlights the significance of high bioavailability in treatment response. The results indicate that responsive nanocarriers contribute to increased bioavailability, leading to improved therapeutic benefits. By including drug delivery features in a semi-realistic model, this numerical study sought to improve drug-bio interaction comprehension. The model provides a good framework for understanding preclinical and clinical targeted oncology study outcomes.

Image-Based Modeling of Drug Delivery during Intraperitoneal Chemotherapy in a Heterogeneous Tumor Nodule

Intraperitoneal (IP) chemotherapy is a promising treatment approach for patients diagnosed with peritoneal carcinomatosis, allowing the direct delivery of therapeutic agents to the tumor site within the abdominal cavity. Nevertheless, limited drug penetration into the tumor remains a primary drawback of this method. The process of delivering drugs to the tumor entails numerous complications, primarily stemming from the specific pathophysiology of the tumor. Investigating drug delivery during IP chemotherapy and studying the parameters affecting it are challenging due to the limitations of experimental studies. In contrast, mathematical modeling, with its capabilities such as enabling single-parameter studies, and cost and time efficiency, emerges as a potent tool for this purpose. In this study, we developed a numerical model to investigate IP chemotherapy by incorporating an actual image of a tumor with heterogeneous vasculature. The tumor's geometry is reconstructed using image processing techniques. The model also incorporates drug binding and uptake by cancer cells. After 60 min of IP treatment with Doxorubicin, the area under the curve (AUC) of the average free drug concentration versus time curve, serving as an indicator of drug availability to the tumor, reached 295.18 mol·m-3·s-1. Additionally, the half-width parameter W1/2, which reflects drug penetration into the tumor, ranged from 0.11 to 0.14 mm. Furthermore, the treatment resulted in a fraction of killed cells reaching 20.4% by the end of the procedure. Analyzing the spatial distribution of interstitial fluid velocity, pressure, and drug concentration in the tumor revealed that the heterogeneous distribution of tumor vasculature influences the drug delivery process. Our findings underscore the significance of considering the specific vascular network of a tumor when modeling intraperitoneal chemotherapy. The proposed methodology holds promise for application in patient-specific studies.

A Quantitative Study of Thermal and Non-thermal Mechanisms in Ultrasound-Induced Nano-drug Delivery

OBJECTIVE

The primary objective of this study was to quantify the contributions to drug release for thermal and non-thermal mechanisms in ultrasound-induced release from gold nanoparticles (GNPs) for the first time.

METHODS

We studied doxorubicin (DOX) and curcumin release from the surface of GNPs using two different methods to induce drug release in an ex vivo tissue model: (i) localized tissue heating with a water bath and (ii) low-intensity pulsed ultrasound (LIPUS) exposure. Both methods have similar temperature profiles and can induce the release of both hydrophobic (curcumin) and hydrophilic (DOX) drugs from the surface of GNPs. Quantitative drug release in both cases was compared via fluorescence measurements.

DISCUSSION

The water bath heating method induced drug release using thermal effects only, whereas LIPUS exposure induced drug release used a combination of thermal and non-thermal mechanisms. It was found that there were increases of 70 ± 16% (curcumin) and 127 ± 20% (DOX) in drug release when LIPUS was used to induce drug release (both thermal and non-thermal mechanisms) as compared with the water bath (thermal mechanisms only) mediated release.

CONCLUSION

We determined that non-thermal mechanisms account for 41 ± 3% of curcumin release and 56 ± 4% of DOX release. It was concluded that in our ex vivo tissue model, the non-thermal mechanisms play a significant role in LIPUS-induced drug release from GNP drug carriers and that the contributions of non-thermal mechanisms to drug release depend on the type of anticancer drug loaded on the GNP surface.

FEM thermal assessment of a 3-D irregular tumor with capillaries in magnetic nanoparticle hyperthermia via dissimilar injection points

In this study, simulation of magnetic nanoparticle hyperthermia is performed on a 3D tumor model constructed based on a CT image of a tumor. In the first step, magnetic nanoparticles are injected into two points of the tumor tissue with the same parameters. Results show that temperature profiles in the vicinity of the injection points are not similar due to the presence of blood capillaries. Therefore, the effects of using dissimilar injection parameters for the two injection points on the heating pattern and damage fraction of the tumor are investigated. The results demonstrate that using dissimilar values for injection parameters such as injection rate, injection time, and nanofluid volume fraction is a way to achieve a higher damage fraction of the tumor cells, but, the asynchronous injections strategy does not lead to more significant damage to the tumor. None of the cases showed significant improvement in the uniformity of the temperature distribution, suggesting that conducting injections under the same conditions is the best way to create an almost uniform temperature profile. The numerical simulation validation results also advocate the accuracy of the model used in this study. This research can serve as a guide for designing parameters for future studies.

Multi-dimensional modeling of nanoparticles transportation from capillary bed into the tumor microenvironment

In this study, we examined the extravasation of pharmaceutical inorganic nanoparticles (NPs) with a new approach from the leaky endothelium of tumor microvasculature (TMV) into the tumor microenvironment (TME) multi-dimensionally. We proposed a combination of prevailing macroscopic and microscopic methods and addressed the effect of interstitial fluid (IF) retention in solid tumor as an imperative parameter in drug delivery modeling. The Navier-Stokes equations and Darcy's law were utilized for blood flow and porous media, and the Starling's law was brought in for coupling effect. The blood flow was simulated as a non-Newtonian fluid alongside the Newtonian IF. We applied the Galerkin finite element method for the simulations. Our parametric study includes examining the effect of IF retention and TMV pressure on the distribution of tumor interstitial fluid pressure (TIFP), NPs concentration, and diameter on the penetration process, together with the time effect, on two-dimensional (2D) delivery of NPs. Our findings indicate that the IF retention in tumor cells increases TIFP depending on the amount of TMV pressure and IF retained. In addition to doubling pressure in the tumor necrotic region rather than the rest of TME, it enhances the TIFP which is an important parameter in drug delivery to solid tumors. By decreasing pressure drop within the TMV, pressure distribution within the TME becomes more uniform, creating a better condition for homogeneous penetration of NPs. Increasing both inlet pressure and NPs concentration leads to a nonlinear increase in the average concentration of tumor. Decreasing the diameter of NPs increases the penetration of NPs with a higher ratio in the TME.

Side-effects of hyperthermic intraperitoneal chemotherapy in patients with gastrointestinal cancers

Background

Hyperthermic intraperitoneal chemotherapy (HIPEC) produces unwanted side-effects that are mainly caused by chemotherapeutic drugs in the treatment of gastrointestinal (GI) cancers, and these effects have not been systematically summarized. The aim of this article was to provide a comprehensive overview of the side-effects of HIPEC for GI cancers and propose practical strategies for adverse event management.

Methodology

PubMed, Web of Science, and the Cochrane Library were systematically searched for side-effects of HIPEC in GI cancers prior to October 20, 2022. A total of 79 articles were included in this review.

Results

Adverse events, such as enterocutaneous digestive fistulas, GI tract perforation, neutropenia, postoperative bleeding, ventricular tachycardia, hyperglycemia, hypocalcemia, renal impairment, encapsulating peritoneal sclerosis, scrotal ulceration, and sarcopenia were described, and their clinical management was discussed. These side-effects involve the digestive, hematopoietic, circulatory, metabolic, and urinary systems. Effective methods for adverse event management included an expert multidisciplinary team, replacing chemotherapy drugs, using Chinese medicine, and careful preoperative assessments.

Conclusion

The side-effects of HIPEC are frequent and can be minimized by several effective methods. This study proposes practical strategies for adverse event management of HIPEC to assist physicians in choosing the optimal treatment method.

Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools

Cancer treatment and pharmaceutical development require targeted treatment and less toxic therapeutic intervention to achieve real progress against this disease. In this scenario, nanomedicine emerged as a reliable tool to improve drug pharmacokinetics and to translate to the clinical biologics based on large molecules. However, the ability of our body to recognize foreign objects together with carrier transport heterogeneity derived from the combination of particle physical and chemical properties, payload and surface modification, make the designing of effective carriers very difficult. In this scenario, physiologically based pharmacokinetic modeling can help to design the particles and eventually predict their ability to reach the target and treat the tumor. This effort is performed by scientists with specific expertise and skills and familiarity with artificial intelligence tools such as advanced software that are not usually in the “cords” of traditional medical or material researchers. The goal of this review was to highlight the advantages that computational modeling could provide to nanomedicine and bring together scientists with different background by portraying in the most simple way the work of computational developers through the description of the tools that they use to predict nanoparticle transport and tumor targeting in our body.

Spatiotemporal multi-scale modeling of radiopharmaceutical distributions in vascularized solid tumors

We present comprehensive mathematical modeling of radiopharmaceutical spatiotemporal distributions within vascularized solid tumors. The novelty of the presented model is at mathematical level. From the mathematical viewpoint, we provide a general modeling framework for the process of radiopharmaceutical distribution in the tumor microenvironment to enable an analysis of the effect of various tumor-related parameters on the distribution of different radiopharmaceuticals. We argue that partial differential equations (PDEs), beyond conventional methods, including ODE-based kinetic compartment modeling, can be used to evaluate radiopharmaceutical distribution in both time and space. In addition, we consider the spatially-variable dynamic structure of tumor microvascular networks to simulate blood flow distribution. To examine the robustness of the model, the effects of microvessel density (MVD) and tumor size, as two important factors in tumor prognosis, on the radiopharmaceutical distribution within the tumor are investigated over time (in the present work, we focus on the radiopharmaceutical [¹⁸F]FDG, yet the framework is broadly applicable to radiopharmaceuticals). Results demonstrate that the maximum total uptake of [¹⁸F]FDG at all time frames occurs in the tumor area due to the high capillary permeability and lack of a functional lymphatic system. As the MVD of networks increases, the mean total uptake in the tumor is also enhanced, where the rate of diffusion from vessel to tissue has the highest contribution and the rate of convection transport has the lowest contribution. The results of this study can be used to better investigate various phenomena and bridge a gap among cancer biology, mathematical oncology, medical physics, and radiology.

Application of a multicomponent model of convectional reaction-diffusion to description of glucose gradients in a neurovascular unit

A supply of glucose to a nervous tissue is fulfilled by a cerebrovascular network, and further diffusion is known to occur at both an arteriolar and a microvascular level. Despite a direct relation, a blood flow dynamic and reaction-diffusion of metabolites are usually considered separately in the mathematical models. In the present study they are coupled in a multiphysical approach which allows to evaluate the effects of capillary blood flow changes on near-vessels nutrient concentration gradients evidently. Cerebral blood flow (CBF) was described by the non-steady-state Navier-Stokes equations for a non-Newtonian fluid whose constitutive law is given by the Carreau model. A three-level organization of blood–brain barrier (BBB) is modelled by the flux dysconnectivity functions including densities and kinetic properties of glucose transporters. The velocity of a fluid flow in brain extracellular space (ECS) was estimated using Darcy’s law. The equations of reaction-diffusion with convection based on a generated flow field for continues and porous media were used to describe spatial-time gradients of glucose in the capillary lumen and brain parenchyma of a neurovascular unit (NVU), respectively. Changes in CBF were directly simulated using smoothing step-like functions altering the difference of intracapillary pressure in time. The changes of CBF cover both the decrease (on 70%) and the increase (on 50%) in a capillary flow velocity. Analyzing the dynamics of glucose gradients, it was shown that a rapid decrease of a capillary blood flow yields an enhanced level of glucose in a near-capillary nervous tissue if the contacts between astrocytes end-feet are not tight. Under the increased CBF velocities the amplitude of glucose concentration gradients is always enhanced. The introduced approach can be used for estimation of blood flow changes influence not only on glucose but also on other nutrients concentration gradients and for the modelling of distributions of their concentrations near blood vessels in other tissues as well.

Drug delivery through nanoparticles in solid tumors: a mechanistic understanding

Aim: In this study, the main goal was to apply a multi-scale computational model in evaluating nano-sized drug-delivery systems, following extracellular drug release, into solid tumors in order to predict treatment efficacy. Methods: The impact of several parameters related to tumor (size, shape, vessel-wall pore size, and necrotic core size) and therapeutic agents (size of nanoparticles, binding affinity of drug, drug release rate from nanoparticles) are examined in detail. Results: This study illustrates that achieving a higher treatment efficacy requires smaller nanoparticles (NPs) or a low binding affinity and drug release rate. Long-term analysis finds that a slow release rate in extracellular space does not always improve treatment efficacy compared with a rapid release rate; NP size as well as binding affinity of drug are also highly influential. Conclusions: The presented methodology can be used as a step forward towards optimization of patient-specific nanomedicine plans.

The Basic Study of Liposome in Temperature-Sensitive Gel at Body Temperature for Treatment of Peritoneal Dissemination

Peritoneal dissemination is a disease that is difficult to treat surgically because it is widely scattered and proliferates in the abdominal cavity. It is a challenge that even if the drug is administered directly into the abdominal cavity, it rapidly disappears from the abdominal cavity, and the therapeutic effect is not optimal, as expected. In this study, for a liposomal paclitaxel in temperature-sensitive gel that is a suspension before administration and a gel after intraperitoneal administration, the antitumor effect of this formulation was evaluated. Temperature-sensitive gels were prepared using methylcellulose, sodium citrate, and macrogol 4000 and mixed with liposomal paclitaxel. Liposomal paclitaxel containing temperature-sensitive gel in the body was administered into the peritoneal cavity of a mouse model of peritoneal dissemination; the number of cells was significantly reduced compared to a paclitaxel solution of liposomal paclitaxel. These results showed that the liposome in temperature-sensitive gel inhibited cell proliferation in the abdominal cavity. This formulation can be administered easily at room temperature, and it gels and remains in the abdominal cavity for a long period, resulting in a more substantial effect than the existing drug.

Mathematical Modeling of Targeted Drug Delivery Using Magnetic Nanoparticles during Intraperitoneal Chemotherapy

Intraperitoneal (IP) chemotherapy has emerged as a promising method for the treatment of peritoneal malignancies (PMs). However, microenvironmental barriers in the tumor limit the delivery of drug particles and their deep penetration into the tumor, leading to reduced efficiency of treatment. Therefore, new drug delivery systems should be developed to overcome these microenvironmental barriers. One promising technique is magnetically controlled drug targeting (MCDT) in which an external magnetic field is utilized to concentrate drug-coated magnetic nanoparticles (MNPs) to the desired area. In this work, a mathematical model is developed to investigate the efficacy of MCDT in IP chemotherapy. In this model, considering the mechanism of drug binding and internalization into cancer cells, the efficacy of drug delivery using MNPs is evaluated and compared with conventional IP chemotherapy. The results indicate that over 60 min of treatment with MNPs, drug penetration depth increased more than 13 times compared to conventional IPC. Moreover, the drug penetration area (DPA) increased more than 1.4 times compared to the conventional IP injection. The fraction of killed cells in the tumor in magnetic drug delivery was 6.5%, which shows an increase of more than 2.5 times compared to that of the conventional method (2.54%). Furthermore, the effects of magnetic strength, the distance of the magnet to the tumor, and the magnetic nanoparticles’ size were evaluated. The results show that MDT can be used as an effective technique to increase the efficiency of IP chemotherapy.

Towards principled design of cancer nanomedicine to accelerate clinical translation

Nanotechnology in medical applications, especially in oncology as drug delivery systems, has recently shown promising results. However, although these advances have been promising in the pre-clinical stages, the clinical translation of this technology is challenging. To create drug delivery systems with increased treatment efficacy for clinical translation, the physicochemical characteristics of nanoparticles such as size, shape, elasticity (flexibility/rigidity), surface chemistry, and surface charge can be specified to optimize efficiency for a given application. Consequently, interdisciplinary researchers have focused on producing biocompatible materials, production technologies, or new formulations for efficient loading, and high stability. The effects of design parameters can be studied in vitro, in vivo, or using computational models, with the goal of understanding how they affect nanoparticle biophysics and their interactions with cells. The present review summarizes the advances and technologies in the production and design of cancer nanomedicines to achieve clinical translation and commercialization. We also highlight existing challenges and opportunities in the field.

Engineered strategies to enhance tumor penetration of drug-loaded nanoparticles

Nanocarriers have been widely employed in preclinical studies and clinical trials for the delivery of anticancer drugs. The most important causes of failure in clinical translation of nanocarriers is their inefficient accumulation and penetration which arises from special characteristics of tumor microenvironment such as insufficient blood supply, dense extracellular matrix, and elevated interstitial fluid pressure. Various strategies such as engineering extracellular matrix, optimizing the physicochemical properties of nanocarriers have been proposed to increase the depth of tumor penetration; however, these strategies have not been very successful so far. Novel strategies such as transformable nanocarriers, transcellular transport of peptide-modified nanocarriers, and bio-inspired carriers have recently been emerged as an advanced generation of drug carriers. In this study, the latest developments of nanocarrier-based drug delivery to solid tumor are presented with their possible limitations. Then, the prospects of advanced drug delivery systems are discussed in detail.

Computational modeling of thermal combination therapies by magneto-ultrasonic heating to enhance drug delivery to solid tumors

For the first time, inspired by magnetic resonance imaging-guidance high intensity focused ultrasound (MR-HIFU) technology, i.e., medication therapy and thermal ablation in one session, in a preclinical setting based on a developed mathematical model, the performance of doxorubicin (Dox) and its encapsulation have been investigated in this study. Five different treatment methods, that combine medication therapy with mild hyperthermia by MRI contrast (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma -{Fe}_{2}{O}_{3}$$\end{document}γ-Fe2O3) and thermal ablation via HIFU, are investigated in detail. A comparison between classical chemotherapy and thermochemistry shows that temperature can improve the therapeutic outcome by stimulating biological properties. On the other hand, the intravascular release of ThermoDox increases the concentration of free drug by 2.6 times compared to classical chemotherapy. The transport of drug in interstitium relies mainly on the diffusion mechanism to be able to penetrate deeper and reach the cancer cells in the inner regions of the tumor. Due to the low drug penetration into the tumor center, thermal ablation has been used for necrosis of the central areas before thermochemotherapy and ThermoDox therapy. Perfusion of the region around the necrotic zone is found to be damaged, while cells in the region are alive and not affected by medication therapy; so, there is a risk of tumor recurrence. Therefore, it is recommended that ablation be performed after the medication therapy. Our model describes a comprehensive assessment of MR-HIFU technology, taking into account many effective details, which can be a reliable guide towards the optimal use of drug delivery systems.

Development and evaluation studies of Corylin loaded nanostructured lipid carriers gel for topical treatment of UV-induced skin aging

We prepared nanostructured lipid carriers (NLC) to promote skin permeation of Corylin so that it can increase its effect on photoaging. Corylin-NLCs were prepared and characterized based on morphology, particle size, zeta potentials, FTIR and DSC. In vitro, we assess the cytotoxicity and lactate dehydrogenase (LDH) of HaCaT cells irradiated by UVB. Expression of antioxidant enzymes was evaluated by commercial kits. The effects of Corylin-NLC on apoptosis were confirmed by flow cytometry and western blotting. In vivo, we use UV irradiated mouse as the oxidative stress model to assess the therapeutic effect of Corylin loaded NLC gel. We identified the Corylin-NLCs can significantly suppress the LDH release, decrease MDA content, increase in CAT, SOD, GSH-Px activity, increase the expression of Bcl-2/Bax protein and reduce the expression of cleaved caspase-3/caspase-3 protein on UVB induced HaCaT cells. The histopathological lesions were significantly improved and observably decreased MDA level, increase in antioxidant enzymes activity in serum of mice by pretreatment of Corylin-NLCs gel. Overall, this study proposes a promising strategy for improving the therapeutic efficacy of photoaging.

Enhanced Drug Delivery to Solid Tumors via Drug-Loaded Nanocarriers: An Image-Based Computational Framework

Objective

Nano-sized drug delivery systems (NSDDSs) offer a promising therapeutic technology with sufficient biocompatibility, stability, and drug-loading rates towards efficient drug delivery to solid tumors. We aim to apply a multi-scale computational model for evaluating drug delivery to predict treatment efficacy.

Methodology

Three strategies for drug delivery, namely conventional chemotherapy (one-stage), as well as chemotherapy through two- and three-stage NSDDSs, were simulated and compared. A geometric model of the tumor and the capillary network was obtained by processing a real image. Subsequently, equations related to intravascular and interstitial flows as well as drug transport in tissue were solved by considering real conditions as well as details such as drug binding to cells and cellular uptake. Finally, the role of periodic treatments was investigated considering tumor recurrence between treatments. The impact of different parameters, nanoparticle (NP) size, binding affinity of drug, and the kinetics of release rate, were additionally investigated to determine their therapeutic efficacy.

Results

Using NPs considerably increases the fraction of killed cells (FKCs) inside the tumor compared to conventional chemotherapy. Tumoral FKCs for two-stage DDS with smaller NP size (20nm) is higher than that of larger NPs (100nm), in all investigate release rates. Slower and continuous release of the chemotherapeutic agents from NPs have better treatment outcomes in comparison with faster release rate. In three-stage DDS, for intermediate and higher binding affinities, it is desirable for the secondary particle to be released at a faster rate, and the drug with slower rate. In lower binding affinities, high release rates have better performance. Results also demonstrate that after 5 treatments with three-stage DDS, 99.6% of tumor cells (TCs) are killed, while two-stage DDS and conventional chemotherapy kill 95.6% and 88.5% of tumor cells in the same period, respectively.

Conclusion

The presented framework has the potential to enable decision making for new drugs via computational modeling of treatment responses and has the potential to aid oncologists with personalized treatment plans towards more optimal treatment outcomes.

Enhancing Clinical Translation of Cancer Using Nanoinformatics

Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, i.e., nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients.

Microfluidic platform for synthesis and optimization of chitosan-coated magnetic nanoparticles in cisplatin delivery

In this study, magnetic core/chitosan shell Nanoparticles (NPs) containing cisplatin were synthesized via cisplatin complexation with tripolyphosphate as the chitosan crosslinker using two different procedures: a conventional batch flow method and a microfluidic approach. An integrated microfluidic device composed of three stages was developed to provide precise and highly controllable mixing. The comparison of the results revealed that NPs synthesized in microchannels were monodisperse 104 ± 14.59 nm (n = 3) in size with optimal morphological characteristics, whereas polydisperse 423 ± 53.33 nm (n = 3) nanoparticles were obtained by the conventional method. Furthermore, cisplatin was loaded in NPs without becoming inactivated, and the microfluidic technique demonstrated higher encapsulation efficiency, controlled release, and consequently lower IC50 values during exposure to the A2780 cell line proving that microfluidic synthesized NPs were able to enter the cells and release the drug more efficiently. The developed microfluidic platform presents valuable features that could potentially provide the clinical translation of NPs in drug delivery.

Controlled anti-cancer drug release through advanced nano-drug delivery systems: Static and dynamic targeting strategies

Advances in nanomedicine, including early cancer detection, targeted drug delivery, and personalized approaches to cancer treatment are on the rise. For example, targeted drug delivery systems can improve intracellular delivery because of their multifunctionality. Novel endogenous-based and exogenous-based stimulus-responsive drug delivery systems have been proposed to prevent the cancer progression with proper drug delivery. To control effective dose loading and sustained release, targeted permeability and individual variability can now be described in more-complex ways, such as by combining internal and external stimuli. Despite these advances in release control, certain challenges remain and are identified in this research, which emphasizes the control of drug release and applications of nanoparticle-based drug delivery systems. Using a multiscale and multidisciplinary approach, this study investigates and analyzes drug delivery and release strategies in the nanoparticle-based treatment of cancer, both mathematically and clinically.

PLGA Nanoparticles for the Intraperitoneal Administration of CBD in the Treatment of Ovarian Cancer: In Vitro and In Ovo Assessment

The intraperitoneal administration of chemotherapeutics has emerged as a potential route in ovarian cancer treatment. Nanoparticles as carriers for these agents could be interesting by increasing the retention of chemotherapeutics within the peritoneal cavity. Moreover, nanoparticles could be internalised by cancer cells and let the drug release near the biological target, which could increase the anticancer efficacy. Cannabidiol (CBD), the main nonpsychotropic cannabinoid, appears as a potential anticancer drug. The aim of this work was to develop polymer nanoparticles as CBD carriers capable of being internalised by ovarian cancer cells. The drug-loaded nanoparticles (CBD-NPs) exhibited a spherical shape, a particle size around 240 nm and a negative zeta potential (-16.6 ± 1.2 mV). The encapsulation efficiency was high, with values above 95%. A controlled CBD release for 96 h was achieved. Nanoparticle internalisation in SKOV-3 epithelial ovarian cancer cells mainly occurred between 2 and 4 h of incubation. CBD antiproliferative activity in ovarian cancer cells was preserved after encapsulation. In fact, CBD-NPs showed a lower IC₅₀ values than CBD in solution. Both CBD in solution and CBD-NPs induced the expression of PARP, indicating the onset of apoptosis. In SKOV-3-derived tumours formed in the chick embryo model, a slightly higher-although not statistically significant-tumour growth inhibition was observed with CBD-NPs compared to CBD in solution. To sum up, poly-lactic-co-glycolic acid (PLGA) nanoparticles could be a good strategy to deliver CBD intraperitoneally for ovarian cancer treatment.

Evaluation of inverse methods for estimation of mechanical parameters in solid tumors

To treat cancer, knowledge of mechanical parameters can be essential. This study proposes a new approach for estimating hydraulic conductivity (k) and hydraulic conductivity ratio (α) of a living tissue, based on inverse methods, allowing tissue parameter estimation using only a limited set of measurements. First, two population-based algorithms (Levenberg-Marquardt (LM) method and conjugate gradient (CG) method) and two gradient-based algorithms (genetic algorithm (GA) and particle swarm optimization (PSO) algorithm) are considered, and a comparative study between these different inverse methods is performed to determine which methods have a good performance in terms of convergence rate and stability. CG method is shown to perform well in the case of noise-free input data; however, in the case of noisy input data, it fails to converge. The other three methods (LM, GA, and PSO) converge with estimation errors <10% in both noise-free and noisy input data, suggesting their utility to tackle this problem. In the second part, the effectiveness and good accuracy of these robust algorithms (LM, GA, and PSO) are validated with experimental results. The hydraulic conductivity and hydraulic conductivity ratio of a specific living tumor tissue are then estimated for mammary adenocarcinoma (R3230AC). Moreover, assuming measurement of only one-point interstitial pressure inside the tumor, the effect of the location of this one-point on estimation accuracy of hydraulic conductivity is investigated. We show that estimation errors for points measured near the surface and center of the tumor are greater than at other points.

Potential drug delivery nanosystems for improving tumor penetration

Nanosystems, as one of the most important drug delivery systems, play a crucial rule in tumor therapy. However, the deep tumor penetration is retarded by the tumor physiological factors and nanomedicine properties. In this review, we firstly elaborate the factors which impact tumor penetration, including the tumor physiological factors and nanomedicine properties. Then, the latest and potential drug delivery nanosystems for improving tumor penetration are summarized and analyzed in detail. Moreover, recent combination therapies for improving penetration are described to enhance penetration. Finally, we summarize the typical clinical therapies of potential drug delivery nanosystems.