Ultrasound Triggering of Liposomal Nanodrugs for Cancer Therapy: A Review

Efficient conventional chemotherapy is limited by its nonspecific nature, which causes severe systemic toxicity that can lead to patient discomfort and low therapeutic efficacy. The emergence of smart drug delivery systems (SDDSs) utilizing nanoparticles as drug nanocarriers has shown great potential in enhancing the targetability of anticancer agents and limiting their side effects. Liposomes are among the most investigated nanoplatforms due to their promising capabilities of encapsulating hydrophilic, lipophilic, and amphiphilic drugs, biocompatibility, physicochemical and biophysical properties. Liposomal nanodrug systems have demonstrated the ability to alter drugs’ biodistribution by sufficiently delivering the entrapped chemotherapeutics at the targeted diseased sites, sparing normal cells from undesired cytotoxic effects. Combining liposomal treatments with ultrasound, as an external drug release triggering modality, has been proven effective in spatially and temporally controlling and stimulating drug release. Therefore, this paper reviews recent literature pertaining to the therapeutic synergy of triggering nanodrugs from liposomes using ultrasound. It also highlights the effects of multiple physical and chemical factors on liposomes’ sonosensetivity, several ultrasound-induced drug release mechanisms, and the efficacy of ultrasound-responsive liposomal systems in cancer therapy. Overall, liposomal nanodrug systems triggered by ultrasound are promising cancer therapy platforms that can potentially alleviate the detriments of conventional cancer treatments

Acoustically-Activated Liposomal Nanocarriers to Mitigate the Side Effects of Conventional Chemotherapy with a Focus on Emulsion-Liposomes

To improve currently available cancer treatments, nanomaterials are employed as smart drug delivery vehicles that can be engineered to locally target cancer cells and respond to stimuli. Nanocarriers can entrap chemotherapeutic drugs and deliver them to the diseased site, reducing the side effects associated with the systemic administration of conventional anticancer drugs. Upon accumulation in the tumor cells, the nanocarriers need to be potentiated to release their therapeutic cargo. Stimulation can be through endogenous or exogenous modalities, such as temperature, electromagnetic irradiation, ultrasound (US), pH, or enzymes. This review discusses the acoustic stimulation of different sonosensitive liposomal formulations. Emulsion liposomes, or eLiposomes, are liposomes encapsulating phase-changing nanoemulsion droplets, which promote acoustic droplet vaporization (ADV) upon sonication. This gives eLiposomes the advantage of delivering the encapsulated drug at low intensities and short exposure times relative to liposomes. Other formulations integrating microbubbles and nanobubbles are also discussed

Recent Advances in Nanoparticle-Based Co-Delivery Systems for Cancer Therapy

Cancer therapies have advanced tremendously throughout the last decade, yet multiple factors still hinder the success of the different cancer therapeutics. The traditional therapeutic approach has been proven insufficient and lacking in the suppression of tumor growth. The simultaneous delivery of multiple small-molecule chemotherapeutic drugs and genes improves the effectiveness of each treatment, thus optimizing efficacy and improving synergistic effects. Nanomedicines integrating inorganic, lipid, and polymeric-based nanoparticles have been designed to regulate the spatiotemporal release of the encapsulated drugs. Multidrug-loaded nanocarriers are a potential strategy to fight cancer and the incorporation of co-delivery systems as a feasible treatment method has projected synergistic benefits and limited undesirable effects. Moreover, the development of co-delivery systems for maximum therapeutic impact necessitates better knowledge of the appropriate therapeutic agent ratio as well as the inherent heterogeneity of the cancer cells. Co-delivery systems can simplify clinical processes and increase patient quality of life, even though such systems are more difficult to prepare than single drug delivery systems. This review highlights the progress attained in the development and design of nano carrier-based co-delivery systems and discusses the limitations, challenges, and future perspectives in the design and fabrication of co-delivery systems

Thermosensitive Polymers and Thermo-Responsive Liposomal Drug Delivery Systems

Temperature excursions within a biological milieu can be effectively used to induce drug release from thermosensitive drug-encapsulating nanoparticles. Oncological hyperthermia is of particular interest, as it is proven to synergistically act to arrest tumor growth when combined with optimally-designed smart drug delivery systems (DDSs). Thermoresponsive DDSs aid in making the drugs more bioavailable, enhance the therapeutic index and pharmacokinetic trends, and provide the spatial placement and temporal delivery of the drug into localized anatomical sites. This paper reviews the fundamentals of thermosensitive polymers, with a particular focus on thermoresponsive liposomal-based drug delivery systems

Gold-Nanoparticle Hybrid Nanostructures for Multimodal Cancer Therapy

With the urgent need for bio-nanomaterials to improve the currently available cancer treatments, gold nanoparticle (GNP) hybrid nanostructures are rapidly rising as promising multimodal candidates for cancer therapy. Gold nanoparticles (GNPs) have been hybridized with several nanocarriers, including liposomes and polymers, to achieve chemotherapy, photothermal therapy, radiotherapy, and imaging using a single composite. The GNP nanohybrids used for targeted chemotherapy can be designed to respond to external stimuli such as heat or internal stimuli such as intratumoral pH. Despite their promise for multimodal cancer therapy, there are currently no reviews summarizing the current status of GNP nanohybrid use for cancer theragnostics. Therefore, this review fulfills this gap in the literature by providing a critical analysis of the data available on the use of GNP nanohybrids for cancer treatment with a specific focus on synergistic approaches (i.e., triggered drug release, photothermal therapy, and radiotherapy). It also highlights some of the challenges that hinder the clinical translation of GNP hybrid nanostructures from bench to bedside. Future studies that could expedite the clinical progress of GNPs, as well as the future possibility of improving GNP nanohybrids for cancer theragnostics, are also summarized

A Comparative Analysis of Numerical Methods for Solving the Leaky Integrate and Fire Neuron Model

The human nervous system is one of the most complex systems of the human body. Understanding its behavior is crucial in drug discovery and developing medical devices. One approach to understanding such a system is to model its most basic unit, neurons. The leaky integrate and fire (LIF) method models the neurons’ response to a stimulus. Given the fact that the model’s equation is a linear ordinary differential equation, the purpose of this research is to compare which numerical analysis method gives the best results for the simplified version of this model. Adams predictor and corrector (AB4-AM4) and Heun’s methods were then used to solve the equation. In addition, this study further researches the effects of different current input models on the LIF’s voltage output. In terms of the computational time, Heun’s method was 0.01191 s on average which is much less than that of the AB-AM4 method (0.057138) for a constant DC input. As for the root mean square error, the AB-AM4 method had a much lower value (0.0061) compared to that of Heun’s method (0.3272) for the same constant input. Therefore, our results show that Heun’s method is best suited for the simplified LIF model since it had the lowest computation time of 36 ms, was stable over a larger range, and had an accuracy of 72% for the varying sinusoidal current input model

Encapsulation, Release, and Cytotoxicity of Doxorubicin Loaded in Liposomes, Micelles, and Metal-Organic Frameworks: A Review

Doxorubicin (DOX) is one of the most widely used anthracycline anticancer drugs due to its high efficacy and evident antitumoral activity on several cancer types. However, its effective utilization is hindered by the adverse side effects associated with its administration, the detriment to the patients’ quality of life, and general toxicity to healthy fast-dividing cells. Thus, delivering DOX to the tumor site encapsulated inside nanocarrier-based systems is an area of research that has garnered colossal interest in targeted medicine. Nanoparticles can be used as vehicles for the localized delivery and release of DOX, decreasing the effects on neighboring healthy cells and providing more control over the drug’s release and distribution. This review presents an overview of DOX-based nanocarrier delivery systems, covering loading methods, release rate, and the cytotoxicity of liposomal, micellar, and metal organic frameworks (MOFs) platforms

A Comparative Analysis of Numerical Methods for Solving the Leaky Integrate and Fire Neuron Model

The human nervous system is one of the most complex systems of the human body. Understanding its behavior is crucial in drug discovery and developing medical devices. One approach to understanding such a system is to model its most basic unit, neurons. The leaky integrate and fire (LIF) method models the neurons’ response to a stimulus. Given the fact that the model’s equation is a linear ordinary differential equation, the purpose of this research is to compare which numerical analysis method gives the best results for the simplified version of this model. Adams predictor and corrector (AB4-AM4) and Heun’s methods were then used to solve the equation. In addition, this study further researches the effects of different current input models on the LIF’s voltage output. In terms of the computational time, Heun’s method was 0.01191 s on average which is much less than that of the AB-AM4 method (0.057138) for a constant DC input. As for the root mean square error, the AB-AM4 method had a much lower value (0.0061) compared to that of Heun’s method (0.3272) for the same constant input. Therefore, our results show that Heun’s method is best suited for the simplified LIF model since it had the lowest computation time of 36 ms, was stable over a larger range, and had an accuracy of 72% for the varying sinusoidal current input model

Tumor vasculature vs tumor cell targeting: Understanding the latest trends in using functional nanoparticles for cancer treatment

Delivering drugs to tumors using nanoparticles (NPs) has shown promising potential in promoting targeted drug delivery of antineoplastic agents to enhance their efficiency while reducing the associated systemic toxicity. This review highlights the different types of NPs and the physiological characteristics of the tumor microenvironment (TME), and the mechanisms undertaken to safely deliver drugs to specific lesions. We review the principles and latest developments in the field of targeted NPs designed to target tumor vasculature compared to those designed to target cancer cells and their correlation with the TME. We discuss the advantages and limitations of each targeted drug delivery mechanism and future directions aiming to maximize their potential