Computational modelling of drug delivery to solid tumour: Understanding the interplay between chemotherapeutics and biological system for optimised delivery systems

Microneedle patch capable of dual drug release for drug delivery to brain tumors

Primary brain tumors are mostly managed using surgical resection procedures. Nevertheless, in certain cases, a thin layer of tumors may remain outside of the resection process due to the possibility of permanent injury; these residual tumors expose patients to the risk of tumor recurrence. This study has introduced the use of microneedle patches implanted after surgery with a dual-release mechanism for the administration of doxorubicin. The proposed patches possess the capability to administer drugs directly to the residual tumors and initiate chemotherapy immediately following surgical procedures. Three-dimensional simulation of drug delivery to residual tumors in the brain has been performed based on a finite element method. The impact of four important parameters on drug delivery has been investigated, involving the fraction of drug released in the burst phase, the density of microneedles on the patch, the length of microneedles, and the microvascular density of the tumor. The simulation findings indicate that lowering the fraction of drug released in the initial burst phase reduces the maximum average concentration, but the sustained release that continues for a longer period, increasing the bioavailability of free drug. However, the area under curve (AUC) for different release rates remains unchanged due to the fact that an identical dose of drug is supplied in each instance. By increasing the density of microneedles on the patch, concentration accumulation is provided over an extensive region of tumor, which in turn induces more cancer cell death. A comparative analysis of various lengths reveals that longer microneedles facilitate profound penetration into the tumor layers and present better therapeutic response due to extensive area of the tumor which is exposure to chemotherapeutic drugs. Furthermore, high microvascular density, as a characteristic of the tumor microenvironment, is shown to have a significant impact on the blood microvessels drainage of drugs and consequently lower therapeutic response outcome. Our approach offers a computational framework for creating localized drug delivery systems and addressing the challenges related to residual brain tumors.

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

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.

In silico study about the influence of electroporation parameters on the cellular internalization, spatial uniformity, and cytotoxic effects of chemotherapeutic drugs using the Method of Fundamental Solutions

Reversible electroporation is a suitable technique to aid the internalization of medicaments in cancer tissues without inducing permanent cellular damage, allowing the enhancement of cytotoxic effects without incurring in electric-driven necrotic or apoptotic processes by the presence of non-reversible aqueous pores. An adequate selection of electroporation parameters acquires relevance to reach these goals and avoid opposite effects. This work applies the Method of Fundamental Solutions (MFS) for drug transport simulations in electroporated cancer tissues, using a continuum tumor cord approach and considering both electro-permeabilization and vasoconstriction effects. The MFS algorithm is validated with published results, obtaining satisfactory accuracy and convergence. Then, MFS simulations are executed to study the influence of electric field magnitude [Formula: see text], number of electroporation treatments [Formula: see text], and electroporation time [Formula: see text] on three assessment parameters of electrochemotherapy: the internationalization efficacy accounting for the ability of the therapy to introduce moles into viable cells, cell-kill capacity indicating the faculty to reduce the survival fraction of cancer cells, and distribution uniformity specifying the competence to supply drug homogeneously through the whole tissue domain. According to numerical results, when [Formula: see text] is the reversibility threshold, a positive influence on the first two parameters is only possible once specific values of [Formula: see text] and [Formula: see text] have been exceeded; when [Formula: see text] is just the irreversibility threshold, any combination of [Formula: see text] and [Formula: see text] is beneficial. On the other hand, the drug distribution uniformity is always adversely affected by the application of electric pulses, being this more noticeable as [Formula: see text], [Formula: see text], and [Formula: see text] increases.

A multiscale modeling study of nanoparticle-based targeting therapy against atherosclerosis

Although researches on nanoparticle-based (NP-based) drug delivery system for atherosclerosis treatment have grown rapidly in recent years, there are limited studies in quantifying the effects of targeting drugs on plaque components and microenvironment. The purpose of the present study was to quantitatively assess the targeting therapeutic effects against atherosclerosis by establishing a multiscale mathematical model. The multiscale model involved subcellular, cellular and microenvironmental scales to simulate lipid catabolism, macrophage behaviors and dynamics of microenvironmental components, respectively. In vitro and in vivo experimental data were integrated into the mathematical model according to Bayesian statistics, in order to evaluate the therapeutic effects of a proposed NP-based platform for macrophage-specific delivery to simultaneously deliver SR-A siRNA (to reduce LDL uptake) and LXR-L (to stimulate cholesterol efflux). Dosage variation analysis was then performed to investigate the drug efficacy under varied dosage combinations of SR-A siRNA and LXR-L. The simulation results demonstrated that the dynamics of the microenvironmental components presented different developments in Untreated and Treated groups. We also found that the balance of lipid metabolism between uptake and efflux resulted in the improvement of lipid and inflammatory microenvironment, consequently in the plaque regression. In addition, the model predicted optimized dosage combinations according to the co-effect analysis of the two drugs on the lipid microenvironment. This study suggests that multiscale modeling can be a powerful quantitative tool for estimating the therapeutic effects of targeting drugs for plaque regression and designing the enhanced treatment strategies against atherosclerosis.

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 [...].

Conjugated Nanoparticles for Solid Tumor Theranostics: Unraveling the Interplay of Known and Unknown Factors

Cancer diagnoses have been increasing worldwide, and solid tumors are among the leading contributors to patient mortality, creating an enormous burden on the global healthcare system. Cancer is responsible for around 10.3 million deaths worldwide. Solid tumors are one of the most prevalent cancers observed in recent times. On the other hand, early diagnosis is a significant challenge that could save a person's life. Treatment with existing methods has pitfalls that limit the successful elimination of the disorder. Though nanoparticle-based imaging and therapeutics have shown a significant impact in healthcare, current methodologies for solid tumor treatment are insufficient. There are multiple complications associated with the diagnosis and management of solid tumors as well. Recently, surface-conjugated nanoparticles such as lipid nanoparticles, metallic nanoparticles, and quantum dots have shown positive results in solid tumor diagnostics and therapeutics in preclinical models. Other nanotheranostic material platforms such as plasmonic theranostics, magnetotheranostics, hybrid nanotheranostics, and graphene theranostics have also been explored. These nanoparticle theranostics ensure the appropriate targeting of tumors along with selective delivery of cargos (both imaging and therapeutic probes) without affecting the surrounding healthy tissues. Though they have multiple applications, nanoparticles still possess numerous limitations that need to be addressed in order to be fully utilized in the clinic. In this review, we outline the importance of materials and design strategies used to engineer nanoparticles in the treatment and diagnosis of solid tumors and how effectively each method overcomes the drawbacks of the current techniques. We also highlight the gaps in each material platform and how design considerations can address their limitations in future research directions.

Drug transport modeling in solid tumors: A computational exploration of spatial heterogeneity of biophysical properties

Inadequate uptake of therapeutic agents by tumor cells is still a major barrier in clinical cancer therapy. Mathematical modeling is a powerful tool to describe and investigate the transport phenomena involved. However, current models for interstitial flow and drug delivery in solid tumors have not yet embedded the existing heterogeneity of tumor biomechanical properties. The purpose of this study is to introduce a novel and more realistic methodology for computational models of solid tumor perfusion and drug delivery accounting for these regional heterogeneities as well as lymphatic drainage effects. Several tumor geometries were studied using an advanced computational fluid dynamics (CFD) modeling approach of intratumor interstitial fluid flow and drug transport. Hereby, the following novelties were implemented: (i) the heterogeneity of tumor-specific hydraulic conductivity and capillary permeability; (ii) the effect of lymphatic drainage on interstitial fluid flow and drug penetration. Tumor size and shape both have a crucial role on the interstitial fluid flow regime as well as drug transport illustrating a direct correlation with interstitial fluid pressure (IFP) and an inverse correlation with drug penetration, except for large tumors having a diameter larger than 50 mm. The results also suggest that the interstitial fluid flow and drug penetration in small tumors depend on tumor shape. A parameter study on the necrotic core size illustrated that the core effect (i.e. fluid flow and drug penetration alteration) was only profound in small tumors. Interestingly, the impact of a necrotic core on drug penetration differs depending on the tumor shape from having no effect in ideally spherical tumors to a clear effect in elliptical tumors with a necrotic core. A realistic presence of lymphatic vessels only slightly affected tumor perfusion, having no substantial effect on drug delivery. In conclusion, our findings illustrated that our novel parametric CFD modeling strategy in combination with accurate profiling of heterogeneous tumor biophysical properties can provide a powerful tool for better insights into tumor perfusion and drug transport, enabling effective therapy planning.

Hybrid computational modeling highlights reverse warburg effect in breast cancer-associated fibroblasts

Cancer-associated fibroblasts (CAFs) are amongst the key players of the tumor microenvironment (TME) and are involved in cancer initiation, progression, and resistance to therapy. They exhibit aggressive phenotypes affecting extracellular matrix remodeling, angiogenesis, immune system modulation, tumor growth, and proliferation. CAFs phenotypic changes appear to be associated with metabolic alterations, notably a reverse Warburg effect that may drive fibroblasts transformation. However, its precise molecular mechanisms and regulatory drivers are still under investigation. Deciphering the reverse Warburg effect in breast CAFs may contribute to a better understanding of the interplay between TME and tumor cells, leading to new treatment strategies. In this regard, dynamic modeling approaches able to span multiple biological layers are essential to capture the emergent properties of various biological entities when complex and intertwined pathways are involved. This work presents the first hybrid large-scale computational model for breast CAFs covering major cellular signaling, gene regulation, and metabolic processes. It was generated by combining a cell- and disease-specific asynchronous Boolean model with a generic core metabolic network leveraging both data-driven and manual curation approaches. This model reproduces the experimentally observed reverse Warburg effect in breast CAFs and further identifies Hypoxia-Inducible Factor 1 (HIF-1) as its key molecular driver. Targeting HIF-1 as part of a TME-centered therapeutic strategy may prove beneficial in the treatment of breast cancer by addressing the reverse Warburg effect. Such findings in CAFs, in light of our previously published results in rheumatoid arthritis synovial fibroblasts, point to a common HIF-1-driven metabolic reprogramming of fibroblasts in breast cancer and rheumatoid arthritis.

Mathematical modelling of microneedle-mediated transdermal delivery of drug nanocarriers into skin tissue and circulatory system

Microneedle-mediated transdermal delivery using nanocarriers can successfully overcome the barrier of the stratum corneum and protect drugs from elimination in skin tissues. However, the effectiveness of drug delivery to different layers of skin tissues and the circulatory system varies considerably, subject to the properties of the drug delivery system and delivery regime. How to maximise delivery outcomes remains unclear. In this study, mathematical modelling is employed to investigate this transdermal delivery under various conditions, using the skin model that is reconstructed based on the realistic skin anatomical structure. Treatment efficacy is evaluated in terms of drug exposure over time. The modelling results demonstrate the complex dependence of drug accumulation and distribution on the nanocarrier properties, microneedle properties and environment in different skin layers and blood. Specifically, delivery outcomes in the entire skin and blood can be improved by increasing the loading dose and reducing microneedle spacing. However, several parameters need to be optimised with respect to the specific location of the target site in the tissue for better treatment; these include the drug release rate, nanocarrier diffusivity in microneedle and skin tissue, nanocarrier transvascular permeability, nanocarrier partition coefficient between tissue and microneedle, microneedle length, wind speed and relative humidity. The delivery is less sensitive to the diffusivity and physical degradation rate of free drugs in microneedle, and their partition coefficient between tissue and microneedle. Results obtained from this study can be used to improve the design of the microneedle-nanocarrier combined drug delivery system and delivery regime.

Design, physicochemical characterisation, and in vitro cytotoxicity of cisplatin-loaded PEGylated chitosan injectable nano / sub-micron crystals

The study aimed to develop cisplatin-loaded PEGylated chitosan nanoparticles. The optimal batch of cisplatin-loaded PEGylated chitosan nanoparticles had a + 49.9 mV zeta potential, PDI of 0.347, and % PDI of 58.9. Nanoparticle zeta size was 741.4 z. d.nm, the size in diameter was 866.7 ± 470.5 nm, and nanoparticle conductivity in colloidal solution was 0.739 mS/cm. Differential scanning calorimetry (DSC) revealed that cisplatin-loaded PEGylated chitosan nanoparticles had sharp endothermic peaks at temperatures at 168.6 °C. The thermogravimetric analysis (TGA) showed the weight loss of cisplatin-loaded PEGylated chitosan nanoparticles, which was observed as 95% at 262.76 °C. XRD investigation on cisplatin-loaded PEGylated chitosan nanoparticles exhibited distinct peaks at 2θ as 9.7°, 20.4°, 22.1°, 25.3°, 36.1°, 38.1°, 39.5°, 44.3°, and 64.5°, confirming crystalline structure. The ¹H NMR analysis showed the fingerprint region of cisplatin-loaded PEGylated chitosan nanoparticles as 0.85, 1.73, and 1.00 ppm in the proton dimension and de-shielded proton peaks appeared at 3.57, 3.58, 3.58, 3.59, 3.65, 3.67, 3,67, 3,67, 3.70, 3.71, 3.77, 3.78 and 4.71 ppm. The ¹³C NMR spectrum showed specified peaks at 63.18, 69.20, and 70.77 ppm. The FT-IR spectra of cisplatin loaded PEGylated nanoparticles show the existence of many fingerprint regions at 3186.52, 2931.68, 1453.19, 1333.98, 1253.71, 1085.19, 1019.60, 969.98, 929.53, 888.80, 706.13, and 623.67 cm^-1. The drug release kinetics of cisplatin loaded PEGylated chitosan nanoparticles showed zero order kinetics with 48% of drug release linearity fashion which has R² value of 0.9778. Studies on the MCF-7 ATCC human breast cancer cell line in vitro revealed that the IC50 value 82.08 µg /mL. Injectable nanoparticles had good physicochemical and cytotoxic properties. This method is novel since the application of the PEGylation processes leads to an increased solubility of chitosan nanoparticles at near neutral pH.

Nanosized drug delivery strategies in osteosarcoma chemotherapy

Despite recent developments worldwide in the therapeutic care of osteosarcoma (OS), the ongoing challenges in overcoming limitations and side effects of chemotherapy drugs warrant new strategies to improve overall patient survival. Spurred by rapid progress in biomedicine, nanobiotechnology, and materials chemistry, chemotherapeutic drug delivery in treatment of OS has become possible in recent years. Here, we review recent advances in the design of drug delivery system, especially for chemotherapeutic drugs in OS, and discuss the relative merits in trials along with future therapeutic options. These advances may pave the way for novel therapies requisite for patients with OS.

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.

Focused ultrasound-mediated small-molecule delivery to potentiate immune checkpoint blockade in solid tumors

In the last decade, immune checkpoint blockade (ICB) has revolutionized the standard of treatment for solid tumors. Despite success in several immunogenic tumor types evidenced by improved survival, ICB remains largely unresponsive, especially in "cold tumors" with poor lymphocyte infiltration. In addition, side effects such as immune-related adverse events (irAEs) are also obstacles for the clinical translation of ICB. Recent studies have shown that focused ultrasound (FUS), a non-invasive technology proven to be effective and safe for tumor treatment in clinical settings, could boost the therapeutic effect of ICB while alleviating the potential side effects. Most importantly, the application of FUS to ultrasound-sensitive small particles, such as microbubbles (MBs) or nanoparticles (NPs), allows for precise delivery and release of genetic materials, catalysts and chemotherapeutic agents to tumor sites, thus enhancing the anti-tumor effects of ICB while minimizing toxicity. In this review, we provide an updated overview of the progress made in recent years concerning ICB therapy assisted by FUS-controlled small-molecule delivery systems. We highlight the value of different FUS-augmented small-molecules delivery systems to ICB and describe the synergetic effects and underlying mechanisms of these combination strategies. Furthermore, we discuss the limitations of the current strategies and the possible ways that FUS-mediated small-molecule delivery systems could boost novel personalized ICB treatments for solid tumors.

Ultrasonically Enhanced ZD2767P–Carboxypeptidase G2 Deactivates Cisplatin-Resistant Human Lung Cancer Cells

The prodrug–enzyme regimen ZD2767P+CPG2 is limited by low efficacy. Here, ultrasound was used to modulate ZD2767P+CPG2 (i.e., ZD2767P+CPG2+US) against cisplatin-resistant human lung cancer cells. A549 and A549/DDP (resistant subline) cells received ZD2767P+CPG2 or ZD2767P+CPG2+US. Either ZD2767P+CPG2 or ZD2767P+CPG2+US led to cell death and apoptosis, and ZD2767P+CPG2+US produced stronger effects; comet assays revealed that these two means directly caused DNA double-strand break. Z-VAD-fmk and/or ferrostatin-1 increased the cell survival percentage, and Z-VAD-fmk decreased the apoptosis percentage. The level of transferrin was increased in treated cells, but those of ferroportin and glutathione peroxidase 4 (GPX4) were reduced, with higher intracellular levels of reactive oxygen species and of iron. Intracellular pharmacokinetics of ZD2767D (activated drug) indicated that the peak level, area under the drug level vs. time curve, and mean residence time in ZD2767P+CPG2+US were higher than those in ZD2767P+CPG2. Both ZD2767P+CPG2 and ZD2767P+CPG2+US were effective on xenograft tumors in nude mice; inhibitory rates were 39.7% and 63.5% in A549 tumors and 50.0% and 70.1% in A549/DDP tumors, respectively. A higher apoptosis level and a lower GPX4 level were noted in tumors receiving treatments. No severe adverse events were observed. These data demonstrated that ZD2767P+CPG2+US deactivated cancer cells via apoptosis and ferroptosis pathways, being a candidate therapy for cisplatin-resistant lung cancer.

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.

Convection-Enhanced Delivery of Antiangiogenic Drugs and Liposomal Cytotoxic Drugs to Heterogeneous Brain Tumor for Combination Therapy

Simple Summary

Although developed anticancer drugs have shown desirable effects in preclinical trials, the clinical efficacy of chemotherapy against brain cancer remains disappointing. One of the important obstacles is the highly heterogeneous environment in tumors. This study aims to evaluate the performance of an emerging treatment using antiangiogenic and cytotoxic drugs. Our mathematical modelling confirms the advantage of this combination therapy in homogenizing the intratumoral environment for better drug delivery outcomes. In addition, the effects of local microvasculature and cell density on this therapy are also discussed. The results would contribute to the development of more effective treatments for brain cancer.

Abstract

Although convection-enhanced delivery can successfully bypass the blood-brain barrier, its clinical performance remains disappointing. This is primarily attributed to the heterogeneous intratumoral environment, particularly the tumor microvasculature. This study investigates the combined convection-enhanced delivery of antiangiogenic drugs and liposomal cytotoxic drugs in a heterogeneous brain tumor environment using a transport-based mathematical model. The patient-specific 3D brain tumor geometry and the tumor’s heterogeneous tissue properties, including microvascular density, porosity and cell density, are extracted from dynamic contrast-enhanced magnetic resonance imaging data. Results show that antiangiogenic drugs can effectively reduce the tumor microvascular density. This change in tissue structure would inhibit the fluid loss from the blood to prevent drug concentration from dilution, and also reduce the drug loss by blood drainage. The comparisons between different dosing regimens demonstrate that the co-infusion of liposomal cytotoxic drugs and antiangiogenic drugs has the advantages of homogenizing drug distribution, increasing drug accumulation, and enlarging the volume where tumor cells can be effectively killed. The delivery outcomes are susceptible to the location of the infusion site. This combination treatment can be improved by infusing drugs at higher microvascular density sites. In contrast, infusion at a site with high cell density would lower the treatment effectiveness of the whole brain tumor. Results obtained from this study can deepen the understanding of this combination therapy and provide a reference for treatment design and optimization that can further improve survival and patient quality of life.

Combined anti-angiogenic and cytotoxic treatment of a solid tumour: In silico investigation of a xenograft animal model's digital twin

Anti-angiogenic (AA) treatments have received significant research interest due to the key role of angiogenesis in cancer progression. AA agents can have a strong effect on cancer regression, by blocking new vessels and reducing the density of the existing vasculature. Moreover, in a process termed vascular normalisation, AA drugs can improve the abnormal structure and function of the tumour vasculature, enhancing the delivery of chemotherapeutics to the tumour site. Despite their promising potential, an improved understanding of AA treatments is necessary to optimise their administration as a monotherapy or in combination with other cancer treatments. In this work we present an in silico multiscale cancer model which is used to systematically interrogate the role of individual mechanisms of action of AA drugs in tumour regression. Focus is placed on the reduction of vascular density and on vascular normalisation through a parametric study, which are considered either as monotherapies or in combination with conventional/metronomic chemotherapy. The model is specified to data from a mammary carcinoma xenograft in immunodeficient mice, to enhance the physiological relevance of model predictions. Our results suggest that conventional chemotherapy might be more beneficial when combined with AA treatments, hindering tumour growth without causing excessive damage on healthy tissue. Notably, metronomic chemotherapy has shown significant potential in stopping tumour growth with minimal toxicity, even as a monotherapy. Our findings underpin the potential of our in silico framework for non-invasive and cost-effective evaluation of treatment strategies, which can enhance our understanding of combined therapeutic strategies and contribute towards improving cancer treatment management.

High Drug-Loading Nanomedicines for Tumor Chemo-Photo Combination Therapy: Advances and Perspectives

The combination of phototherapy and chemotherapy (chemo−photo combination therapy) is an excellent attempt for tumor treatment. The key requirement of this technology is the high drug-loading nanomedicines, which can load either chemotherapy drugs or phototherapy agents at the same nanomedicines and simultaneously deliver them to tumors, and play a multimode therapeutic role for tumor treatment. These nanomedicines have high drug-loading efficiency (>30%) and good tumor combination therapeutic effect with important clinical application potential. Although there are many reports of high drug-loading nanomedicines for tumor therapy at present, systematic analyses on those nanomedicines remain lacking and a comprehensive review is urgently needed. In this review, we systematically analyze the current status of developed high drug-loading nanomedicines for tumor chemo−photo combination therapy and summarize their types, methods, drug-loading properties, in vitro and in vivo applications. The shortcomings of the existing high drug-loading nanomedicines for tumor chemo−photo combination therapy and the possible prospective development direction are also discussed. We hope to attract more attention for researchers in different academic fields, provide new insights into the research of tumor therapy and drug delivery system and develop these nanomedicines as the useful tool for tumor chemo−photo combination therapy in the future.

Stimuli-responsive nanoassemblies for targeted delivery against tumor and its microenvironment

Despite the emergence of various cancer treatments, such as surgery, chemotherapy, radiotherapy, and immunotherapy, their use remains restricted owing to their limited tumor elimination efficacy and side effects. The use of nanoassemblies as delivery systems in nanomedicine for tumor diagnosis and therapy is flourishing. These nanoassemblies can be designed to have various shapes, sizes, and surface charges to meet the requirements of different applications. It is crucial for nanoassemblies to have enhanced delivery of payloads while inducing minimal to no toxicity to healthy tissues. In this review, stimuli-responsive nanoassemblies capable of combating the tumor microenvironment (TME) are discussed. First, various TME characteristics, such as hypoxia, oxidoreduction, adenosine triphosphate (ATP) elevation, and acidic TME, are described. Subsequently, the unique characteristics of the vascular and stromal TME are differentiated, and multiple barriers that have to be overcome are discussed. Furthermore, strategies to overcome these barriers for successful drug delivery to the targeted site are reviewed and summarized. In conclusion, the possible challenges and prospects of using these nanoassemblies for tumor-targeted delivery are discussed. This review aims at inspiring researchers to develop stimuli-responsive nanoassemblies for tumor-targeted delivery for clinical applications.

Convection-Enhanced Delivery In Silico Study for Brain Cancer Treatment

Brain cancer therapy remains a formidable challenge in oncology. Convection-enhanced delivery (CED) is an innovative and promising local drug delivery method for the treatment of brain cancer, overcoming the challenges of the systemic delivery of drugs to the brain. To improve our understanding about CED efficacy and drug transport, we present an in silico methodology for brain cancer CED treatment simulation. To achieve this, a three-dimensional finite element formulation is utilized which employs a brain model representation from clinical imaging data and is used to predict the drug deposition in CED regimes. The model encompasses biofluid dynamics and the transport of drugs in the brain parenchyma. Drug distribution is studied under various patho-physiological conditions of the tumor, in terms of tumor vessel wall pore size and tumor tissue hydraulic conductivity as well as for drugs of various sizes, spanning from small molecules to nanoparticles. Through a parametric study, our contribution reports the impact of the size of the vascular wall pores and that of the therapeutic agent on drug distribution during and after CED. The in silico findings provide useful insights of the spatio-temporal distribution and average drug concentration in the tumor towards an effective treatment of brain cancer.

Role of Tissue Hydraulic Permeability in Convection-Enhanced Delivery of Nanoparticle-Encapsulated Chemotherapy Drugs to Brain Tumour

PURPOSE

Tissue hydraulic permeability of brain tumours can vary considerably depending on the tissue microstructure, compositions in interstitium and tumour cells. Its effects on drug transport and accumulation remain poorly understood.

METHODS

Mathematical modelling is applied to predict the drug delivery outcomes in tumours with different tissue permeability upon convection-enhanced delivery. The modelling is based on a 3-D realistic tumour model that is extracted from patient magnetic resonance images.

RESULTS

Modelling results show that infusing drugs into a permeable tumour can facilitate a more favourable hydraulic environment for drug transport. The infused drugs will exhibit a relatively uniform distribution and cover a larger tumour volume for effective cell killing. Cross-comparisons show the delivery outcomes are more sensitive to the changes in tissue hydraulic permeability and blood pressure than the fluid flow from the brain ventricle. Quantitative analyses demonstrate that increasing the fluid gain from both the blood and brain ventricle can further improve the interstitial fluid flow, and thereby enhance the delivery outcomes. Furthermore, similar responses to the changes in tissue hydraulic permeability can be found for different types of drugs.

CONCLUSIONS

Tissue hydraulic permeability as an intrinsic property can influence drug accumulation and distribution. Results from this study can deepen the understanding of the interplays between drug and tissues that are involved in the drug delivery processes in chemotherapy.

Interrogating and Quantifying In Vitro Cancer Drug Pharmacodynamics via Agent-Based and Bayesian Monte Carlo Modelling

The effectiveness of chemotherapy in cancer cell regression is often limited by drug resistance, toxicity, and neoplasia heterogeneity. However, due to the significant complexities entailed by the many cancer growth processes, predicting the impact of interference and symmetry-breaking mechanisms is a difficult problem. To quantify and understand more about cancer drug pharmacodynamics, we combine in vitro with in silico cancer models. The anti-proliferative action of selected cytostatics is interrogated on human colorectal and breast adenocarcinoma cells, while an agent-based computational model is employed to reproduce experiments and shed light on the main therapeutic mechanisms of each chemotherapeutic agent. Multiple drug administration scenarios on each cancer cell line are simulated by varying the drug concentration, while a Bayesian-based method for model parameter optimisation is employed. Our proposed procedure of combining in vitro cancer drug screening with an in silico agent-based model successfully reproduces the impact of chemotherapeutic drugs in cancer growth behaviour, while the mechanisms of action of each drug are characterised through model-derived probabilities of cell apoptosis and division. We suggest that our approach could form the basis for the prospective generation of experimentally-derived and model-optimised pharmacological variables towards personalised cancer therapy.

Effect of Particle Size and Surface Charge on Nanoparticles Diffusion in the Brain White Matter

Purpose

Brain disorders have become a serious problem for healthcare worldwide. Nanoparticle-based drugs are one of the emerging therapies and have shown great promise to treat brain diseases. Modifications on particle size and surface charge are two efficient ways to increase the transport efficiency of nanoparticles through brain-blood barrier; however, partly due to the high complexity of brain microstructure and limited visibility of Nanoparticles (NPs), our understanding of how these two modifications can affect the transport of NPs in the brain is insufficient.

Methods

In this study, a framework, which contains a stochastic geometric model of brain white matter (WM) and a mathematical particle tracing model, was developed to investigate the relationship between particle size/surface charge of the NPs and their effective diffusion coefficients (D) in WM.

Results

The predictive capabilities of this method have been validated using published experimental tests. For negatively charged NPs, both particle size and surface charge are positively correlated with D before reaching a size threshold. When Zeta potential (Zp) is less negative than -10 mV, the difference between NPs’ D in WM and pure interstitial fluid (IF) is limited.

Conclusion

A deeper understanding on the relationships between particle size/surface charge of NPs and their D in WM has been obtained. The results from this study and the developed modelling framework provide important tools for the development of nano-drugs and nano-carriers to cure brain diseases.

The Extension of the LeiCNS-PK3.0 Model in Combination with the "Handshake" Approach to Understand Brain Tumor Pathophysiology

Micrometastatic brain tumor cells, which cause recurrence of malignant brain tumors, are often protected by the intact blood–brain barrier (BBB). Therefore, it is essential to deliver effective drugs across not only the disrupted blood-tumor barrier (BTB) but also the intact BBB to effectively treat malignant brain tumors. Our aim is to predict pharmacokinetic (PK) profiles in brain tumor regions with the disrupted BTB and the intact BBB to support the successful drug development for malignant brain tumors. LeiCNS-PK3.0, a comprehensive central nervous system (CNS) physiologically based pharmacokinetic (PBPK) model, was extended to incorporate brain tumor compartments. Most pathophysiological parameters of brain tumors were obtained from literature and two missing parameters of the BTB, paracellular pore size and expression level of active transporters, were estimated by fitting existing data, like a “handshake”. Simultaneous predictions were made for PK profiles in extracellular fluids (ECF) of brain tumors and normal-appearing brain and validated on existing data for six small molecule anticancer drugs. The LeiCNS-tumor model predicted ECF PK profiles in brain tumor as well as normal-appearing brain in rat brain tumor models and high-grade glioma patients within twofold error for most data points, in combination with estimated paracellular pore size of the BTB and active efflux clearance at the BTB. Our model demonstrated a potential to predict PK profiles of small molecule drugs in brain tumors, for which quantitative information on pathophysiological alterations is available, and contribute to the efficient and successful drug development for malignant brain tumors.

Nanotechnology-based advances in the efficient delivery of melatonin

N-[2-(5-methoxy-1H-indol-3-yl) ethyl] or simply melatonin is a biogenic amine produced by pineal gland and recently recognized various other organs. Because of a broad range of biological function melatonin is considered as a therapeutic agent with high efficacy in the treatment of multiple disorders, such as cancer, degenerative disorders and immune disease. However, since melatonin can affect receptors on the cellular membrane, in the nucleus and can act as an anti-oxidant molecule, some unwanted effects may be observed after administration. Therefore, the entrapment of melatonin in biocompatible, biodegradable and safe nano-delivery systems can prevent its degradation in circulation; decrease its toxicity with increased half-life, enhanced pharmacokinetic profile leading to improved patient compliance. Because of this, nanoparticles have been used to deliver melatonin in multiple studies, and the present article aims to cumulatively illustrate their findings.

Mathematical modelling of nanoparticle-mediated topical drug delivery to skin tissue

Nanoparticles have been extensively studied to improve drug delivery outcomes, however, their use in topical delivery remains controversial. Although the feasibility to cross the human skin barrier has been demonstrated in experiments, the risk of low drug concentration in deep tissue still limits the application. In this study, mathematical modelling is employed to examine the performance of nanoparticle-mediated topical delivery for sending drugs into the deep skin tissue. The pharmacokinetic effect is evaluated based on the drug exposure over time. As compared to the delivery using plain drugs, nanoparticle-mediated topical delivery has the potential to significantly improve the drug exposure in deep skin tissue. Modelling predictions denote that the importance of sufficient long-term drug-skin contact in achieving effective drug deposition in the deep skin tissue. The delivery outcomes are highly sensitive to the release rate. Accelerating the release from nanoparticles in stratum corneum is able to improve the drug exposure in stratum corneum and viable epidermis while resulting in the reductions in dermis and blood. The release rate in stratum corneum and viable epidermis should be well-designed below a threshold for generating effective drug accumulation in dermis and blood. A more localised drug accumulation can be achieved in the capillary-rich region of dermis by increasing the local release rate. The release rate in dermis needs to be optimised to increase the drug exposure in the dermis region where there are fewer blood and lymphatics capillaries. Results from this study can be used to improve the regimen of topical delivery for localised treatment.

Quantitative Evaluation of Dendritic Nanoparticles in Mice: Biodistribution Dynamics and Downstream Tumor Efficacy Outcomes

A physiologically based pharmacokinetic model was developed to describe the tissue distribution kinetics of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) in plasma, liver, spleen, and tumors. Tumor growth data from MV-4-11 tumor-bearing mice were incorporated to investigate the exposure/efficacy relationship. The nanoparticle demonstrated improved antitumor activity compared to the conventional API formulation, owing to the extended released API concentrations at the site of action. Model simulations further enabled the identification of critical parameters that influence API exposure in tumors and downstream efficacy outcomes upon nanoparticle administration. The model was utilized to explore a range of dosing schedules and their effect on tumor growth kinetics, demonstrating the improved antitumor activity of nanoparticles with less frequent dosing compared to the same dose of naked APIs in conventional formulations.

Ultra-performance liquid chromatography-tandem mass spectrometry for simultaneous determination of 12 anti-tumor drugs in human plasma and its application in therapeutic drug monitoring

The effectiveness and safety of anti-tumor drugs are clinically important issues, and their therapeutic drug monitoring (TDM) is recommended. This study aimed to develop an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for simultaneous TDM and exploration of clinical pharmacokinetics of anti-tumor drugs, including cyclophosphamide, ifosfamide, cisplatin, methotrexate, pemetrexed disodium, capecitabine, 5-fluorouracil, gemcitabine, doxorubicin, fulvestrant, tamoxifen, and irinotecan. After magnetic solid-phase extraction of plasma samples, the isotope internal standards and 12 anti-tumor drugs were separated using a ZORBAX Eclipse Plus C18 column (50.0 × 2.1 mm, 1.7 µm) with water containing 0.1% formic acid and acetonitrile as the mobile phase in a total run time of 5.0 min. The developed UPLC-MS/MS method was validated based on the Chinese Pharmacopoeia and the US Food and Drug Administration guidelines for bioanalytical method validation, including assessment of specificity, calibration curves, carryover, accuracy, crosstalk, precision, stability, recovery, dilution integrity, incurred sample reanalysis, and matrix effect. The results showed that a simple, fast, reliable, and specific UPLC-MS/MS method was developed and validated, and all the performance characteristics of the method met the requirements. The response function was established for concentration range of 0.10-25.00 μg/mL for gemcitabine, cyclophosphamide, ifosfamide, methotrexate, pemetrexed disodium, capecitabine, 5-fluorouracil, and cisplatin, and 0.05-12.50 μg/mL for doxorubicin, fulvestrant, tamoxifen, and irinotecan, with a coefficient of correlation of>0.9984 for all the compounds. The precision and accuracy of all the analytes were<6.5% and 5.9%, respectively. Hence, it could be used for TDM and exploration of pharmacokinetics of the aforementioned 12 anti-tumor drugs.

Enzyme-induced morphological transformation of drug carriers: Implications for cytotoxicity and the retention time of antitumor agents

Nanocarriers have been widely employed to deliver chemotherapeutic drugs for cancer treatment. However, the insufficient accumulation of nanoparticles in tumors is an important reason for the poor efficacy of nanodrugs. In this study, a novel drug delivery system with a self-assembled amphiphilic peptide was designed to respond specifically to alkaline phosphatase (ALP), a protease overexpressed in cancer cells. The amphiphilic peptide self-assembled into spherical and fibrous nanostructures, and it easily assembled into spherical drug-loaded peptide nanoparticles after loading of a hydrophobic chemotherapeutic drug. The cytotoxicity of the drug carriers was enhanced against tumor cells over time. These spherical nanoparticles transformed into nanofibers under the induction of ALP, leading to efficient release of the encapsulated drug. This drug delivery strategy relying on responsiveness to an enzyme present in the tumor microenvironment can enhance local drug accumulation at the tumor site. The results of live animal imaging showed that the residence time of the morphologically transformable drug-loaded peptide nanoparticles at the tumor site was prolonged in vivo, confirming their potential use in antitumor therapy. These findings can contribute to a better understanding of the influence of drug carrier morphology on intracellular retention.

Computational model of silica nanoparticle penetration into tumor spheroids: Effects of methoxy and carboxy PEG surface functionalization and hyperthermia

Drug delivery to tumors suffers from poor solubility, specificity, diffusion through the tumor micro-environment and nonoptimal interactions with components of the extracellular matrix and cell surface receptors. Nanoparticles and drug-polymer complexes address many of these problems. However, large size exasperates the problem of slow diffusion through the tumor. Three-dimensional tumor spheroids are good models to evaluate approaches to mitigate these difficulties and aid in design strategies to improve the delivery of drugs to treat cancer effectively. Diffusion of drug carriers is highly dependent on cell uptake rate parameters (association/dissociation) and temperature. Hyperthermia increases molecular transport and is known to act synergistically with chemotherapy to improve treatment. This study presents a new inverse estimation approach based on Bayesian probability for estimating nanoparticle cell uptake rates from experiments. The parameters were combined with a finite element computational model of nanoparticle transport under hyperthermia conditions to explore its effect on tumor porosity, diffusion and particle binding (association and dissociation) at cell surfaces. Carboxy-PEG-silane (cPEGSi) nanoparticles showed higher cell uptake compared to methoxy-PEG-silane (mPEGSi) nanoparticles. Simulations were consistent with experimental results from Skov-3 ovarian cancer spheroids. Amorphous silica (cPEGSi) nanoparticles (58 nm) concentrated at the periphery of the tumor spheroids at 37°C but mild hyperthermia (43°C) increased nanoparticle penetration. Thus, hyperthermia may enhance cancer treatment by improving blood delivery to tumors, enhancing extravasation and penetration into tumors, trigger release of drug from the carrier at the tumor site and possibly lead to synergistic anti-cancer activity with the drug.

Multiphysics Modeling and Simulation of Subcutaneous Injection and Absorption of Biotherapeutics: Model Development

PURPOSE

Many monoclonal antibodies (mAbs) are administered via subcutaneous (SC) injection. Local transport and absorption kinetics and mechanisms, however, remain poorly understood. A multiphysics computational model was developed to simulate the injection and absorption processes of a protein solution in the SC tissue.

METHODS

Quantitative relationships among tissue properties and transport behaviors of an injected solution were described by respective physical laws. SC tissue was treated as a 3-dimensional homogenous, poroelastic medium, in which vasculatures and lymphatic vessels were implicitly treated. Tissue deformation was considered, and interstitial fluid flow was modeled by Darcy's law. Transport of the drug mass was described based on diffusion and advection, which was integrated with tissue mechanics and interstitial fluid dynamics.

RESULTS

Injection and absorption of albumin and IgG solutions were simulated. Upon injection, a sharp rise in tissue pressure, porosity, and fluid velocity could be observed at the injection tip. Largest tissue deformation appeared at the model surface. Transport of drug mass out of the injection zone was minimal. Absorption by local lymphatics was found to last several weeks.

CONCLUSIONS

A bottom-up method was developed to simulate drug transport and absorption of protein solutions in skin tissue base on physical principles. The results appear to match experimental observations.

Electrokinetic Convection-Enhanced Delivery of Solutes to the Brain

Pressure-induced infusion of solutions into brain tissue is used both in research and in medicine. In medicine, convection enhanced delivery (CED) may be used to deliver agents to localized areas of the brain, such as with gene therapy to functional targets or with deep tumors not readily amenable to resection. However, clinical trials have demonstrated mixed results from CED. CED is limited by a lack of control of the infusion flow path and may cause damage or even neurological deficits due to neuronal distortion. In laboratory research, infusions may be achieved using pressure or using brief bursts of electrical current in iontophoresis. Electrokinetic convection enhanced delivery (ECED) has the potential to deliver drugs and other bioactive substances to local regions in the brain with improved control and lower applied pressures than pressure-based CED. ECED improves control over the infusion profile because the fluid follows the electrical current path and thus can be directed. Both small molecules and macromolecules can be delivered. Here we demonstrate proof-of-principal that electrokinetic (electroosmosis and electrophoresis) convection-enhanced delivery is a viable means for delivering solutes to the brain. We assessed the volume of tissue exposed to the infusates tris(2,2'-bipyridine)ruthenium(II) and fluorescent dextrans. Control of the direction of the transport was also achieved over distances ranging from several hundred micrometers to more than 4 mm. Electrokinetic delivery has the potential to improve control over infusions.

Human intratumoral therapy: Linking drug properties and tumor transport of drugs in clinical trials

Cancer therapies aim to kill tumor cells directly or engage the immune system to fight malignancy. Checkpoint inhibitors, oncolytic viruses, cell-based immunotherapies, cytokines, and adjuvants have been applied to prompt the immune system to recognize and attack cancer cells. However, systemic exposure of cancer therapies can induce unwanted adverse events. Intratumoral administration of potent therapies utilizes small amounts of drugs, in an effort to minimize systemic exposure and off-target toxicities. Here, we discuss the properties of the tumor microenvironment and transport considerations for intratumoral drug delivery. Specifically, we consider various tumor tissue factors and physicochemical factors that can affect tumor retention after intratumoral injection. We also review approved and clinical-stage intratumoral therapies and consider how the molecular and biophysical properties (e.g. size and charge) of these therapies influences intratumoral transport (e.g. tumor retention and cellular uptake). Finally, we offer a critical review and highlight several emerging approaches to promote tumor retention and limit systemic exposure of potent intratumoral therapies.

Mathematical Model of Muscle Wasting in Cancer Cachexia

Cancer cachexia is a debilitating condition characterized by an extreme loss of skeletal muscle mass, which negatively impacts patients' quality of life, reduces their ability to sustain anti-cancer therapies, and increases the risk of mortality. Recent discoveries have identified the myostatin/activin A/ActRIIB pathway as critical to muscle wasting by inducing satellite cell quiescence and increasing muscle-specific ubiquitin ligases responsible for atrophy. Remarkably, pharmacological blockade of the ActRIIB pathway has been shown to reverse muscle wasting and prolong the survival time of tumor-bearing animals. To explore the implications of this signaling pathway and potential therapeutic targets in cachexia, we construct a novel mathematical model of muscle tissue subjected to tumor-derived cachectic factors. The model formulation tracks the intercellular interactions between cancer cell, satellite cell, and muscle cell populations. The model is parameterized by fitting to colon-26 mouse model data, and the analysis provides insight into tissue growth in healthy, cancerous, and post-cachexia treatment conditions. Model predictions suggest that cachexia fundamentally alters muscle tissue health, as measured by the stem cell ratio, and this is only partially recovered by anti-cachexia treatment. Our mathematical findings suggest that after blocking the myostatin/activin A pathway, partial recovery of cancer-induced muscle loss requires the activation and proliferation of the satellite cell compartment with a functional differentiation program.

Ginsenoside Rh2 pretreatment and withdrawal reactivated the pentose phosphate pathway to ameliorate intracellular redox disturbance and promoted intratumoral penetration of adriamycin

Improving the limited penetration, accumulation and therapeutic effects of antitumor drugs in the avascular region of the tumor mass is crucial during chemotherapy. P-gp inhibitors have achieved little success despite significant efforts. Excessive P-gp inhibition disturbed the kinetic balance between intracellular accumulation and intercellular penetration, thus resulting in a more inhomogeneous distribution of substrate drugs. Here, we found that ginsenoside Rh2 pretreatment mildly downregulated P-gp expression through reactivating the pentose phosphate pathway and rebalancing redox status. This mild P-gp inhibition not only significantly increased the growth inhibition effect and accumulation profile of adriamycin (ADR) throughout the multicellular tumor spheroid (MCTS) but also had unique advantages in improving drug penetration. Furthermore, we developed a novel individual-cell-based PK-PD integrated model and proved that metabolic reprogramming and redox rebalancing-based P-gp regulation was sufficient to increase the ADR effect in both central and peripheral cells of MCTS. Thus, a “ginsenoside Rh2-ADR” sequential regimen was proposed and exhibited a potent antitumor effect in vivo. This novel P-gp inhibition via metabolic reprogramming and redox rebalancing provided a new idea for achieving better antitumor effects in the tumor avascular region during chemotherapy.

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Rh2 pretreatment downregulated P-gp expression through metabolic reprogramming and redox rebalancing.

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Rh2-pretreatment improved ADR penetration into the core of MCTS and tumour mass.

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“Ginsenoside Rh2-ADR” sequential regimen exhibited potent antitumor effects in vivo.

Effects of Focused-Ultrasound-and-Microbubble-Induced Blood-Brain Barrier Disruption on Drug Transport under Liposome-Mediated Delivery in Brain Tumour: A Pilot Numerical Simulation Study

Focused ultrasound (FUS) coupled with microbubbles (MB) has been found to be a promising approach to disrupt the blood-brain barrier (BBB). However, how this disruption affects drug transport remains unclear. In this study, drug transport in combination therapy of liposomes and FUS-MB-induced BBB disruption (BBBD) was investigated based on a multiphysics model. A realistic 3D brain tumour model extracted from MR images was applied. The results demonstrated the advantage of liposomes compared to free doxorubicin injection in further improving treatment when the BBB is opened under the same delivery conditions using burst sonication. This improvement was mainly due to the BBBD-enhanced transvascular transport of free doxorubicin and the sustainable supply of the drug by long-circulating liposomes. Treatment efficacy can be improved in different ways. Disrupting the BBB simultaneously with liposome bolus injection enables more free drug molecules to cross the vessel wall, while prolonging the BBBD duration could accelerate liposome transvascular transport for more effective drug release. However, the drug release rate needs to be well controlled to balance the trade-off among drug release, transvascular exchange and elimination. The results obtained in this study could provide suggestions for the future optimisation of this FUS-MB–liposome combination therapy against brain cancer.

A low-intensity focused ultrasound-assisted nanocomposite for advanced triple cancer therapy: local chemotherapy, therapeutic extracellular vesicles and combined immunotherapy

CCs-SF/DOX nanocomposite based triple therapies of “local chemotherapy-therapeutic EVs-synergistic immunotherapy” irradiated by LIFU.

Convection enhanced delivery of anti-angiogenic and cytotoxic agents in combination therapy against brain tumour

Convection enhanced delivery is an effective alternative to routine delivery methods to overcome the blood brain barrier. However, its treatment efficacy remains disappointing in clinic owing to the rapid drug elimination in tumour tissue. In this study, multiphysics modelling is employed to investigate the combination delivery of anti-angiogenic and cytotoxic drugs from the perspective of intratumoural transport. Simulations are based on a 3-D realistic brain tumour model that is reconstructed from patient magnetic resonance images. The tumour microvasculature is targeted by bevacizumab, and six cytotoxic drugs are included, as doxorubicin, carmustine, cisplatin, fluorouracil, methotrexate and paclitaxel. The treatment efficacy is evaluated in terms of the distribution volume where the drug concentration is above the corresponding LD90. Results demonstrate that the infusion of bevacizumab can slightly improve interstitial fluid flow, but is significantly efficient in reducing the fluid loss from the blood circulatory system to inhibit the concentration dilution. As the transport of bevacizumab is dominated by convection, its spatial distribution and anti-angiogenic effectiveness present high sensitivity to the directional interstitial fluid flow. Infusing bevacizumab could enhance the delivery outcomes of all the six drugs, however, the degree of enhancement differs. The delivery of doxorubicin can be improved most, whereas, the impacts on methotrexate and paclitaxel are limited. Fluorouracil could cover the comparable distribution volume as paclitaxel in the combination therapy for effective cell killing. Results obtain in this study could be a guide for the design of this co-delivery treatment.

A quantitative in silico platform for simulating cytotoxic and nanoparticle drug delivery to solid tumours

The role of tumour-host mechano-biology and the mechanisms involved in the delivery of anti-cancer drugs have been extensively studied using in vitro and in vivo models. A complementary approach is offered by in silico models, which can also potentially identify the main factors affecting the transport of tumour-targeting molecules. Here, we present a generalized three-dimensional in silico modelling framework of dynamic solid tumour growth, angiogenesis and drug delivery. Crucially, the model allows for drug properties-such as size and binding affinity-to be explicitly defined, hence facilitating investigation into the interaction between the changing tumour-host microenvironment and cytotoxic and nanoparticle drugs. We use the model to qualitatively recapitulate experimental evidence of delivery efficacy of cytotoxic and nanoparticle drugs on matrix density (and hence porosity). Furthermore, we predict a highly heterogeneous distribution of nanoparticles after delivery; that nanoparticles require a high porosity extracellular matrix to cause tumour regression; and that post-injection transvascular fluid velocity depends on matrix porosity, and implicitly on the size of the drug used to treat the tumour. These results highlight the utility of predictive in silico modelling in better understanding the factors governing efficient cytotoxic and nanoparticle drug delivery.

Monte Carlo simulations in drug release

We present methods based on simple sampling Monte Carlo simulations that are used in the study of controlled drug release from devices of various shapes and characteristics. The manuscript is part of a special tribute issue for Prof. Panos Macheras and we have chosen applications of the Monte Carlo method in the field of drug release that were pioneered by him and his research group. Thus, we focus on the investigation of diffusion based release and we present methods that go beyond the application of the classical fickian diffusion equation. We describe methods that have proven to be effective in illuminating the profound effects of the substrate heterogeneity on the drug release profiles and demonstrate some of the most powerful applications of agent based simulations and numerical methods in the field of pharmacokinetics.