Computational and experimental approaches for investigating nanoparticle-based drug delivery systems

Para- and Transcellular Transport Kinetics of Nanoparticles across Lymphatic Endothelial Cells

Lymphatic vessels have received significant attention as drug delivery targets, as they shuttle materials from peripheral tissues to the lymph nodes, where adaptive immunity is formed. Delivery of immune modulatory materials to the lymph nodes via lymphatic vessels has been shown to enhance their efficacy and also improve the bioavailability of drugs when delivered to intestinal lymphatic vessels. In this study, we generated a three-compartment model of a lymphatic vessel with a set of kinematic differential equations to describe the transport of nanoparticles from the surrounding tissues into lymphatic vessels. We used previously published data and collected additional experimental parameters, including the transport efficiency of nanoparticles over time, and also examined how nanoparticle formulation affected the cellular transport mechanisms using small molecule inhibitors. These experimental data were incorporated into a system of kinematic differential equations, and nonlinear, least-squares curve fitting algorithms were employed to extrapolate transport coefficients within our model. The subsequent computational framework produced some of the first parameters to describe transport kinetics across lymphatic endothelial cells and allowed for the quantitative analysis of the driving mechanisms of transport into lymphatic vessels. Our model indicates that transcellular mechanisms, such as micro- and macropinocytosis, drive transport into lymphatics. This information is crucial to further design strategies that will modulate lymphatic transport for drug delivery, particularly in diseases like lymphedema, where normal lymphatic functions are impaired.

Layer-by-layer assembly of nanotheranostic particles for simultaneous delivery of docetaxel and doxorubicin to target osteosarcoma

Osteosarcoma (OS) is a rare form of primary bone cancer, impacting approximately 3.4 × 106 individuals worldwide each year, primarily afflicting children. Given the limitations of existing cancer therapies, the emergence of nanotheranostic platforms has generated considerable research interest in recent decades. These platforms seamlessly integrate therapeutic potential of drug compounds with the diagnostic capabilities of imaging probes within a single construct. This innovation has opened avenues for enhanced drug delivery to targeted sites while concurrently enabling real-time monitoring of the vehicle's trajectory. In this study, we developed a nanotheranostic system employing the layer-by-layer (LbL) technique on a core containing doxorubicin (DOXO) and in-house synthesized carbon quantum dots. By utilizing chitosan and chondroitin sulfate as polyelectrolytes, we constructed a multilayered coating to encapsulate DOXO and docetaxel, achieving a coordinated co-delivery of both drugs. The LbL-functionalized nanoparticles exhibited an approximate size of 150 nm, manifesting a predominantly uniform and spherical morphology, with an encapsulation efficiency of 48% for both drugs. The presence of seven layers in these systems facilitated controlled drug release over time, as evidenced by in vitro release tests. Finally, the impact of the LbL-functionalized nanoparticles was evaluated on U2OS and Saos-2 osteosarcoma cells. The synergistic effect of the two drugs was found to be crucial in inducing cell death, particularly in Saos-2 cells treated with nanoparticles at concentrations higher than 10 μg/ml. Transmission electron microscopy analysis confirmed the internalization of the nanoparticles into both cell types through endocytic mechanisms, revealing an underlying mechanism of necrosis-induced cell death.

Structured soft particulate matters for delivery of bioactive compounds in foods and functioning in the colon

The present review discusses challenges, perspectives, and current needs of delivering bioactive compounds (BCs) using soft particulate matters (SPMs) for gut health. SPMs can entrap BCs for incorporation in foods, preserve their bioactivities during processing, storage, and gastrointestinal digestion, and deliver BCs to functioning sites in the colon. To enable these functions, physical, chemical, and biological properties of BCs are integrated in designing various types of SPMs to overcome environmental factors reducing the bioavailability and bioactivity of BCs. The design principles are applied using food grade molecules with the desired properties to produce SPMs by additionally considering the cost, sustainability, and scalability of manufacturing processes. Lastly, to make delivery systems practical, impacts of SPMs on food quality are to be evaluated case by case, and health benefits of functional foods incorporated with delivery systems are to be confirmed and must outweigh the cost of preparing SPMs.

MTTLm6A: A multi-task transfer learning approach for base-resolution mRNA m6A site prediction based on an improved transformer

N6-methyladenosine (m6A) is a crucial RNA modification involved in various biological activities. Computational methods have been developed for the detection of m6A sites in Saccharomyces cerevisiae at base-resolution due to their cost-effectiveness and efficiency. However, the generalization of these methods has been hindered by limited base-resolution datasets. Additionally, RMBase contains a vast number of low-resolution m6A sites for Saccharomyces cerevisiae, and base-resolution sites are often inferred from these low-resolution results through post-calibration. We propose MTTLm6A, a multi-task transfer learning approach for base-resolution mRNA m6A site prediction based on an improved transformer. First, the RNA sequences are encoded by using one-hot encoding. Then, we construct a multi-task model that combines a convolutional neural network with a multi-head-attention deep framework. This model not only detects low-resolution m6A sites, it also assigns reasonable probabilities to the predicted sites. Finally, we employ transfer learning to predict base-resolution m6A sites based on the low-resolution m6A sites. Experimental results on Saccharomyces cerevisiae m6A and Homo sapiens m1A data demonstrate that MTTLm6A respectively achieved area under the receiver operating characteristic (AUROC) values of 77.13% and 92.9%, outperforming the state-of-the-art models. At the same time, it shows that the model has strong generalization ability. To enhance user convenience, we have made a user-friendly web server for MTTLm6A publicly available at http://47.242.23.141/MTTLm6A/index.php.

Looking to the Future: Drug Delivery and Targeting in the Prophylaxis and Therapy of Severe and Chronic Diseases

High molecular weight actives and cell-based therapy have the potential to revolutionize the prophylaxis and therapy of severe diseases. Yet, the size and nature of the agents - proteins, nucleic acids, cells - challenge drug delivery and thus formulation development. Moreover, off-target effects may result in severe adverse drug reactions. This makes delivery and targeting an essential component of high-end drug development. Loading to nanoparticles facilitates delivery and enables targeted mRNA vaccines and tumor therapeutics. Stem cell therapy opens up a new horizon in diabetes type 1 among other domains which may enhance the quality of life and life expectancy. Cell encapsulation protects transplants against the recipient's immune system, may ensure long-term efficacy, avoid severe adverse reactions, and simplify the management of rare and fatal diseases.The knowledge gained so far encourages to widen the spectrum of potential indications. Co-development of the active agent and the vehicle has the potential to accelerate drug research. One recommended starting point is the use of computational approaches. Transferability of preclinical data to humans will benefit from performing studies first on validated human 3D disease models reflecting the target tissue, followed by studies on validated animal models. This makes approaching a new level in drug development a multidisciplinary but ultimately worthwhile and attainable challenge. Intense monitoring of the patients after drug approval and periodic reporting to physicians and scientists remain essential for the safe use of drugs especially in rare diseases and pave future research.

Recent advancements in the targeted delivery of etoposide nanomedicine for cancer therapy: A comprehensive review

Etoposide (ETO), a popular anticancer drug that inhibits topoisomerase II enzymes, may be administered more effectively and efficiently due to nanomedicine. The therapeutic application of ETO is constrained by its limited solubility, weak absorption, and severe side effects. This article summarizes substantial progress made in the development of ETO nanomedicine for the treatment of cancer. It discusses various organic and inorganic nanostructures used to load or affix ETOs, such as lipids, liposomes, polymeric nanoparticles (NPs), dendrimers, micelles, gold NPs, iron oxide NPs, and silica NPs. In addition, it evaluates the structural properties of these nanostructures, such as their size, zeta potential, encapsulation efficiency, and drug release mechanism, as well as their in vitro or in vivo performance. The article also emphasizes the co-delivery of ETO with other medications or agents to produce synergistic effects or combat drug resistance in the treatment of cancer. It concludes with a discussion of the challenges and potential avenues for clinical translation of ETO nanomedicine.

Computational modeling of passive transport of functionalized nanoparticles

Functionalized nanoparticles (NPs) are complex objects present in a variety of systems ranging from synthetic grafted nanoparticles to viruses. The morphology and number of the decorating groups can vary widely between systems. Thus, the modeling of functionalized NPs typically considers simplified spherical objects as a first-order approximation. At the nanoscale label, complex hydrodynamic interactions are expected to emerge as the morphological features of the particles change, and they can be further amplified when the NPs are confined or near walls. Direct estimation of these variations can be inferred via diffusion coefficients of the NPs. However, the evaluation of the coefficients requires an improved representation of the NPs morphology to reproduce important features hidden by simplified spherical models. Here, we characterize the passive transport of free and confined functionalized nanoparticles using the Rigid Multi-Blob (RMB) method. The main advantage of RMB is its versatility to approximate the mobility of complex structures at the nanoscale with significant accuracy and reduced computational cost. In particular, we investigate the effect of functional groups' distribution, size, and morphology over nanoparticle translational and rotational diffusion. We identify that the presence of functional groups significantly affects the rotational diffusion of the nanoparticles; moreover, the morphology of the groups and number induce characteristic mobility reduction compared to non-functionalized nanoparticles. Confined NPs also evidenced important alterations in their diffusivity, with distinctive signatures in the off-diagonal contributions of the rotational diffusion. These results can be exploited in various applications, including biomedical, polymer nanocomposite fabrication, drug delivery, and imaging.

A review on microfluidic-assisted nanoparticle synthesis, and their applications using multiscale simulation methods

Recent years have witnessed an increased interest in the development of nanoparticles (NPs) owing to their potential use in a wide variety of biomedical applications, including drug delivery, imaging agents, gene therapy, and vaccines, where recently, lipid nanoparticle mRNA-based vaccines were developed to prevent SARS-CoV-2 causing COVID-19. NPs typically fall into two broad categories: organic and inorganic. Organic NPs mainly include lipid-based and polymer-based nanoparticles, such as liposomes, solid lipid nanoparticles, polymersomes, dendrimers, and polymer micelles. Gold and silver NPs, iron oxide NPs, quantum dots, and carbon and silica-based nanomaterials make up the bulk of the inorganic NPs. These NPs are prepared using a variety of top-down and bottom-up approaches. Microfluidics provide an attractive synthesis alternative and is advantageous compared to the conventional bulk methods. The microfluidic mixing-based production methods offer better control in achieving the desired size, morphology, shape, size distribution, and surface properties of the synthesized NPs. The technology also exhibits excellent process repeatability, fast handling, less sample usage, and yields greater encapsulation efficiencies. In this article, we provide a comprehensive review of the microfluidic-based passive and active mixing techniques for NP synthesis, and their latest developments. Additionally, a summary of microfluidic devices used for NP production is presented. Nonetheless, despite significant advancements in the experimental procedures, complete details of a nanoparticle-based system cannot be deduced from the experiments alone, and thus, multiscale computer simulations are utilized to perform systematic investigations. The work also details the most common multiscale simulation methods and their advancements in unveiling critical mechanisms involved in nanoparticle synthesis and the interaction of nanoparticles with other entities, especially in biomedical and therapeutic systems. Finally, an analysis is provided on the challenges in microfluidics related to nanoparticle synthesis and applications, and the future perspectives, such as large-scale NP synthesis, and hybrid formulations and devices.

Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty

Computational modeling of drug delivery is becoming an indispensable tool for advancing drug development pipeline, particularly in nanomedicine where a rational design strategy is ultimately sought. While numerous in silico models have been developed that can accurately describe nanoparticle interactions with the bioenvironment within prescribed length and time scales, predictive design of these drug carriers, dosages and treatment schemes will require advanced models that can simulate transport processes across multiple length and time scales from genomic to population levels. In order to address this problem, multiscale modeling efforts that integrate existing discrete and continuum modeling strategies have recently emerged. These multiscale approaches provide a promising direction for bottom-up in silico pipelines of drug design for delivery. However, there are remaining challenges in terms of model parametrization and validation in the presence of variability, introduced by multiple levels of heterogeneities in disease state. Parametrization based on physiologically relevant in vitro data from microphysiological systems as well as widespread adoption of uncertainty quantification and sensitivity analysis will help address these challenges.

Fluorescent Multifunctional Organic Nanoparticles for Drug Delivery and Bioimaging: A Tutorial Review

Fluorescent organic nanoparticles (FONs) are a large family of nanostructures constituted by organic components that emit light in different spectral regions upon excitation, due to the presence of organic fluorophores. FONs are of great interest for numerous biological and medical applications, due to their high tunability in terms of composition, morphology, surface functionalization, and optical properties. Multifunctional FONs combine several functionalities in a single nanostructure (emission of light, carriers for drug-delivery, functionalization with targeting ligands, etc.), opening the possibility of using the same nanoparticle for diagnosis and therapy. The preparation, characterization, and application of these multifunctional FONs require a multidisciplinary approach. In this review, we present FONs following a tutorial approach, with the aim of providing a general overview of the different aspects of the design, preparation, and characterization of FONs. The review encompasses the most common FONs developed to date, the description of the most important features of fluorophores that determine the optical properties of FONs, an overview of the preparation methods and of the optical characterization techniques, and the description of the theoretical approaches that are currently adopted for modeling FONs. The last part of the review is devoted to a non-exhaustive selection of some recent biomedical applications of FONs.

Exploring the mechanisms of drug-delivery by decorated ZnO nanoparticles through predictive ReaxFF molecular dynamics simulations

Herein, we study the assembling of a drug delivery nanocarrier through reactive molecular dynamics simulations based on an appropriately tuned force field. First, we focus on the combination of the various components (all selected in agreement with experiments), namely nanoparticle (ZnO), functional chains (oleic acid), drug (carfilzomib), and solvent molecules (ethanol), and then on the ability of the assembled nanotool to release its cargo in a physiological environment (water). The simulation results reveal that reactivity is crucial for characterizing the stability of the functionalized ZnONP, its dynamics, and its interactions with lipid chains and drug molecules. The chains are stably chemisorbed on the ZnONP through monodentate or bidentate binding of the carboxyls to the Zn atoms (the hydrogens are released to the surface oxygens). Chains' self-interactions reinforce the lipid cover's stability and distribution on the ZnONP interface. The added drug migrates from the solution to the nano assembly and is captured by the lipids. The molecules are entrapped among the oleic acid chains and adsorbed on the uncoated regions of the nanoparticle surface, partially physisorbed or chemisorbed. The analysis of the simulations confirms that the supramolecular assembly is compact and stable in ethanol. However, upon injection into the water, the size of the aggregate gradually increases, and the lipids start to swell with the aqueous medium. The system evolves towards an unpacked structure where the chains are elongated, separated, and prone to release the cargo depending on local water activity and depth of cargo insertion. All the results agree with the literature confirming the reliability of our predictive computational procedure for disclosing the structure and dynamics of complex materials relevant to the medicinal chemistry field.

Nucleation and growth of gold nanoparticles in the presence of different surfactants. A dissipative particle dynamics study

Nanoparticles (NPs) show promising applications in biomedicine, catalysis, and energy harvesting. This applicability relies on controlling the material’s features at the nanometer scale. Surfactants, a unique class of surface-active molecules, have a remarkable ability to tune NPs activity; provide specific functions, avoid their aggregation, and create stable colloidal solutions. Surfactants also control nanoparticles’ nucleation and growth processes by modifying nuclei solubility and surface energy. While nucleation seems independent from the surfactant, NP’s growth depends on it. NP`s size is influenced by the type of functional group (C, O, S or N), length of its C chain and NP to surfactant ratio. In this paper, gold nanoparticles (Au NPs) are taken as model systems to study how nucleation and growth processes are affected by the choice of surfactants by Dissipative Particle Dynamics (DPD) simulations. DPD has been mainly used for studying biochemical structures, like lipid bilayer models. However, the study of solid NPs, and their conjugates, needs the introduction of a new metallic component. To represent the collective phenomena of these large systems, their degrees of freedom are reduced by Coarse-Grained (CG) models. DPD behaved as a powerful tool for studying complex systems and shedding some light on some experimental observations, otherwise difficult to explain.

Anti-Inflammatory and Anti-Rheumatic Potential of Selective Plant Compounds by Targeting TLR-4/AP-1 Signaling: A Comprehensive Molecular Docking and Simulation Approaches

Plants are an important source of drug development and numerous plant derived molecules have been used in clinical practice for the ailment of various diseases. The Toll-like receptor-4 (TLR-4) signaling pathway plays a crucial role in inflammation including rheumatoid arthritis. The TLR-4 binds with pro-inflammatory ligands such as lipopolysaccharide (LPS) to induce the downstream signaling mechanism such as nuclear factor κappa B (NF-κB) and mitogen activated protein kinases (MAPKs). This signaling activation leads to the onset of various diseases including inflammation. In the present study, 22 natural compounds were studied against TLR-4/AP-1 signaling, which is implicated in the inflammatory process using a computational approach. These compounds belong to various classes such as methylxanthine, sesquiterpene lactone, alkaloid, flavone glycosides, lignan, phenolic acid, etc. The compounds exhibited different binding affinities with the TLR-4, JNK, NF-κB, and AP-1 protein due to the formation of multiple hydrophilic and hydrophobic interactions. With TLR-4, rutin had the highest binding energy (−10.4 kcal/mol), poncirin had the highest binding energy (−9.4 kcal/mol) with NF-κB and JNK (−9.5 kcal/mol), respectively, and icariin had the highest binding affinity (−9.1 kcal/mol) with the AP-1 protein. The root means square deviation (RMSD), root mean square fraction (RMSF), and radius of gyration (RoG) for 150 ns were calculated using molecular dynamic simulation (MD simulation) based on rutin’s greatest binding energy with TLR-4. The RMSD, RMSF, and RoG were all within acceptable limits in the MD simulation, and the complex remained stable for 150 ns. Furthermore, these compounds were assessed for the potential toxic effect on various organs such as the liver, heart, genotoxicity, and oral maximum toxic dose. Moreover, the blood–brain barrier permeability and intestinal absorption were also predicted using SwissADME software (Lausanne, Switzerland). These compounds exhibited promising physico-chemical as well as drug-likeness properties. Consequently, these selected compounds portray promising anti-inflammatory and drug-likeness properties.

Computational Insights into the Role of Cholesterol in Inverted Hexagonal Phase Stabilization and Endosomal Drug Release

Cholesterol is a major component of many lipid-based drug delivery systems, including cationic lipid nanoparticles. Despite its critical role in the drug release stage, the underlying molecular mechanism by which cholesterol assists in endosomal escape remains unclear. An efficient drug release from the endosome requires endosomal disruption. This disruption is believed to involve a lamellar-to-inverted hexagonal (L_α-H_II) phase transition upon fusion of the lipid nanoparticle with the endosomal membrane. We used molecular dynamics simulations to study the structural properties of H_II systems composed of an anionic lipid distearoyl phosphatidylserine (DSPS), an ionizable cationic lipid (KC2H), and cholesterol for several hydration levels and molar ratios. This system corresponds to the lipid mixtures in the hypothesized H_II structure formed upon fusion and is of interest for the rational design of ionizable cationic lipids, including KC2, for an optimal drug release. Simulations suggest a geometry- and symmetry-driven lipid sorting and cholesterol-DSPS co-location around the water cores. Cholesterol preferentially co-locates with negatively charged saturated DSPS lipids at interstitial angles. The observed cholesterol-DSPS co-location results in an overall increase in the DSPS acyl chains' order parameters, which we propose to assist in stabilizing the H_II phase by stretching the DSPS acyl chains for filling the voids formed by three adjacent lipid tubules. Furthermore, a systematic increase in the cholesterol concentration increased the lattice plane spacing and the water core radius but decreased the undulations along the lipid tubule axis. We propose that cholesterol and the degree of saturation/polyunsaturation of the lipid acyl chains, and not the lipid charge, are the main contributors in facilitating the L_α-H_II phase transition and stabilizing/destabilizing the formed H_II phase, whereas the positive charge of the ionizable cationic lipid promotes the LNP-endosomal membrane adhesion and assists in initiating the fusion process at the local contact area. We also propose that the effect of cholesterol on the H_II structure and curvature is the main underlying reason for the well-documented H_II stabilization and destabilization at low and high molar concentrations of cholesterol, respectively.

Medicinal plants mediated the green synthesis of silver nanoparticles and their biomedical applications

The alarming effect of antibiotic resistance prompted the search for alternative medicine to resolve the microbial resistance conflict. Over the last two decades, scientists have become increasingly interested in metallic nanoparticles to discover their new dimensions. Green nano synthesis is a rapidly expanding field of interest in nanotechnology due to its feasibility, low toxicity, eco‐friendly nature, and long‐term viability. Some plants have long been used in medicine because they contain a variety of bioactive compounds. Silver has long been known for its antibacterial properties. Silver nanoparticles have taken a special place among other metal nanoparticles. Silver nanotechnology has a big impact on medical applications like bio‐coating, novel antimicrobial agents, and drug delivery systems. This review aims to provide a comprehensive understanding of the pharmaceutical qualities of medicinal plants, as well as a convenient guideline for plant‐based silver nanoparticles and their antimicrobial activity.

Coarse-Grained Molecular Dynamics Simulations of Paclitaxel-Loaded Polymeric Micelles

A continuous manufacturing technology based on coaxial turbulent jet in coflow was previously developed to produce paclitaxel-loaded polymeric micelles. Herein, coarse-grained molecular dynamics (CG-MD) simulations were implemented to better understand the effect of the material attributes (i.e., the drug-polymer ratio and the ethanol concentration) and process parameters (i.e., temperature) on the self-assembly process of polymeric micelles as well as to provide molecular details on micelle instability. An all-atom (AA) poly (ethylene glycol)-poly (lactic acid) (PEG-PLA) polymer model was developed as the reference for parameterizing a coarse-grained (CG) model, and the AA polymer model was further validated with experimental glass transition temperature (T_g). The model transferability was verified by comparing structural properties between the AA and CG models. The CG model was further validated with experimental data, including micelle particle size measurements and drug encapsulation efficiency. Furthermore, the encapsulation of paclitaxel into the polymeric micelles was included in the simulations, taking into consideration the interactions between the paclitaxel and the polymers. The results from various points of view demonstrated a strong dependence of the shape of the micelles on the drug encapsulation, with micelles transitioning from spherical to ellipsoidal structures with an increasing paclitaxel amount. Simulation data were also used to identify the critical aggregation number (i.e., the number of polymer and drug molecules required for transition from one shape to another). Improved micellar structural stability was found with a larger micellar size and less solvent accessibility. Lastly, an evaluation was performed on the micellar dissociation free energy using a steered molecular dynamics simulation over a range of temperatures and ethanol concentrations. These simulations revealed that at higher ethanol and temperature conditions, micelles become destabilized, resulting in greater paclitaxel release. The increased drug release was determined to originate from the solvation of the hydrophobic core, which promoted micellar swelling and an associated reduction in hydrophobic interactions, leading to a loosely packed micellar structure.

An in Silico Approach to Reveal the Nanodisc Formulation of Doxorubicin

Molecular dynamic behaviors of nanodisc (ND) formulations of free doxorubicin (DOX) and DOX conjugated lipid prodrug molecules were investigated by molecular dynamics (MD) simulations. We have unveiled how formulation design affects the drug release profile and conformational stability of ND assemblies. Our simulation results indicate that free DOX molecules loaded in the ND system experienced rapid dissociation due to the unfavorable orientation of DOX attached to the lipid surface. It is found that DOX tends to form aggregates with higher drug quantities. In contrast, lipidated DOX-prodrugs incorporated in ND formulations exhibited sufficient ND conformational stability. The drug loading capacity is dependent on the type of lipid molecules grafted on the DOX-prodrug, and the drug loading quantities in a fixed area of NDs follow the order: DOX-BMPH-MP > DOX-BMPH-TC > DOX-BMPH-PTE. To gain further insight into the dynamic characteristics of ND formulations governed by different kinds of lipidation, we investigated the conformational variation of ND components, intermolecular interactions, the solvent accessible surface area, and individual MSP1 residue flexibility. We found that the global conformational stability of DOX-prodrug-loaded ND assemblies is influenced by the molecular flexibility and lipidated forms of DOX-prodrug. We also found that the spontaneous self-aggregation of DOX-prodrugs with increasing quantities on ND could reduce the membrane fluidity and enhance the conformational stability of ND formulations.

Recent Advances in Drug Design and Delivery Across Biological Barriers using Computational Models

Abstract:

The systemic delivery of pharmacological substances generally exhibits several significant limitations associated with the bio-distribution of active drugs in the body. As per consequence, human body’s defense mechanisms become impediments to drug delivery. Various technologies to overcome these limitations have been evolved including computational approaches and advanced drug delivery. As the body of human has evolved to defend itself from hostile biological as well as chemical invaders, along with that these biological barriers such as ocular barriers, blood-brain barriers, intestinal and skin barriers also limit the passage of drugs across desired sites. Therefore, efficient delivery remains an utmost challenge for researchers and scientists. The present review focuses on the techniques to deliver the drugs with efficient therapeutic efficacy at the targeted sites. This review article considered the insights into main biological barriers along with the application of computational or numerical methods dealing with different barriers by determining the drug flow, temperature and various other parameters. It also summarizes the advanced implantable drug delivery system to circumvent the inherent resistance showed by these biological barriers and in turn to improve the drug delivery.

Biosensing, Characterization of Biosensors, and Improved Drug Delivery Approaches Using Atomic Force Microscopy: A Review

Since its invention, atomic force microscopy (AFM) has come forth as a powerful member of the “scanning probe microscopy” (SPM) family and an unparallel platform for high-resolution imaging and characterization for inorganic and organic samples, especially biomolecules, biosensors, proteins, DNA, and live cells. AFM characterizes any sample by measuring interaction force between the AFM cantilever tip (the probe) and the sample surface, and it is advantageous over other SPM and electron micron microscopy techniques as it can visualize and characterize samples in liquid, ambient air, and vacuum. Therefore, it permits visualization of three-dimensional surface profiles of biological specimens in the near-physiological environment without sacrificing their native structures and functions and without using laborious sample preparation protocols such as freeze-drying, staining, metal coating, staining, or labeling. Biosensors are devices comprising a biological or biologically extracted material (assimilated in a physicochemical transducer) that are utilized to yield electronic signal proportional to the specific analyte concentration. These devices utilize particular biochemical reactions moderated by isolated tissues, enzymes, organelles, and immune system for detecting chemical compounds via thermal, optical, or electrical signals. Other than performing high-resolution imaging and nanomechanical characterization (e.g., determining Young’s modulus, adhesion, and deformation) of biosensors, AFM cantilever (with a ligand functionalized tip) can be transformed into a biosensor (microcantilever-based biosensors) to probe interactions with a particular receptors of choice on live cells at a single-molecule level (using AFM-based single-molecule force spectroscopy techniques) and determine interaction forces and binding kinetics of ligand receptor interactions. Targeted drug delivery systems or vehicles composed of nanoparticles are crucial in novel therapeutics. These systems leverage the idea of targeted delivery of the drug to the desired locations to reduce side effects. AFM is becoming an extremely useful tool in figuring out the topographical and nanomechanical properties of these nanoparticles and other drug delivery carriers. AFM also helps determine binding probabilities and interaction forces of these drug delivery carriers with the targeted receptors and choose the better agent for drug delivery vehicle by introducing competitive binding. In this review, we summarize contributions made by us and other researchers so far that showcase AFM as biosensors, to characterize other sensors, to improve drug delivery approaches, and to discuss future possibilities.

Goserelin/PLGA solid dispersion used to prepare long-acting microspheres with reduced initial release and reduced fluctuation of drug serum concentration in vivo

To prepare Goserelin (GOS) loaded long-acting microspheres with reduced initial release and prolonged drug release time of GOS, GOS/PLGA solid dispersion (by hot-melt extrusion, HME) was dissolved/dispersed in dichloromethane (DCM) to prepare microspheres by O/W method. From results of molecular dynamics simulation, PLGA and GOS molecules completely and uniformly dissolved and dispersed in DCM, respectively. In F5 microspheres (prepared by HME-O/W method), GOS existed as molecular or amorphous state, but not aggregation. Burst release of F5 microspheres (2.75%) was similar with Zoladex^TM implant (0.39%) and less than F10 microspheres (prepared by S/O/W method, 25.92%). After lag phase, GOS released rapidly from F5 microspheres and the cumulative release on the 45^th days was 95.14%. After injection of F5 microspheres, GOS serum concentration was relative steady at the range of 27.64-175.27 ng/mL for nearly 35 days. AUC_{(0-35 day)} of F5 microspheres was almost 2 times that of F10 microspheres. Pharmacodynamics study also showed potential effect of F5 microspheres on inhibiting the secretion of testosterone in male rats. HME-O/W method is potential to establish long-acting PLGA microspheres (loading water-soluble drug) , exhibiting stable drug serum concentration in vivo, and without large concentration fluctuation or serious pain/side effects.

Complex nanoemulsion for vitamin delivery: droplet organization and interaction with skin membranes

Lipid nanoemulsions are promising nanomaterials for drug delivery applications in food, pharmaceutical and cosmetic industries. Despite the noteworthy commercial interest, little is known about their supramolecular organization, especially about how such multicomponent formulations interact with cell membranes. In the present work, coarse-grained molecular dynamics simulations have been employed to study the self-assembly of a 15-component lipid nanoemulsion droplet containing vitamins A and E for skin delivery. Our results display aspects of the unique "onion-like" agglomeration between the chemical constituents in the different layers of the lipid nanodroplet. Vitamin E molecules are more concentrated in the center of the droplet together with other hydrophobic constituents such as the triglycerides with long tails. On the other hand, vitamin A occupies an intermediate layer between the core and the co-emulsifier surface of the nanodroplet, together with lecithin phospholipids. Coarse-grained molecular dynamics simulations were also performed to provide insight into the first steps involved in absorption and penetration of the nanodroplet through skin membrane models, representing an intracellular (hair follicle infundibulum) and intercellular pathway (stratum corneum) through the skin. Our data provide a first view on the complex organization of commercial nanoemulsion and its interaction with skin membranes. We expect our results to open the way towards the rational design of such nanomaterials.

Coronene-based quantum dots for the delivery of the doxorubicin anticancer drug: a computational study

The coronene family could serve as a useful platform for the delivery of and tracking the release of the anticancer DOX drug.

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.

Designing amphiphilic Janus nanoparticles with tunable lipid raft affinity via molecular dynamics simulation

Due to the differential interactions among lipids and proteins, the plasma membrane can segregate into a series of functional nanoscale membrane domains ("lipid rafts"), which are essential in multiple biological processes such as signaling transduction, protein trafficking and endocytosis. On the other hand, Janus nanoparticles (NPs) have shown great promise in various biomedical applications due to their asymmetric characteristics and can integrate different surface properties and thus synergetic functions. Hence, in this work, we aim to design an amphiphilic Janus NP to target and regulate lipid rafts via tuning its surface ligand amphiphilicity using coarse-grained molecular dynamics (MD) simulations. Our μs-scale free coarse-grained MD simulations as well as umbrella sampling free energy calculations indicated that the hydrophobicity of the hydrophobic surface ligands not only determined the lateral membrane partitioning thermodynamics of Janus NPs in phase-separated lipid membranes, but also the difficulty in their insertion into different membrane domains of the lipid membrane. These two factors jointly regulated the lipid raft affinity of Janus NPs. Meanwhile, the hydrophilicity of the hydrophilic surface ligands could affect the insertion ability of Janus NPs. Besides, the ultra-small size could ensure the membrane-bound behavior of Janus NPs without disrupting the overall structure and phase separation kinetics of the lipid membrane. These results may provide valuable insights into the design of functional NPs targeting and controllably regulating lipid rafts.

Quantifying and controlling bond multivalency for advanced nanoparticle targeting to cells

Nanoparticles have drawn intense interest as delivery agents for diagnosing and treating various cancers. Much of the early success was driven by passive targeting mechanisms such as the enhanced permeability and retention (EPR) effect, but this has failed to lead to the expected clinical successes. Active targeting involves binding interactions between the nanoparticle and cancer cells, which promotes tumor cell-specific accumulation and internalization. Furthermore, nanoparticles are large enough to facilitate multiple bond formation, which can improve adhesive properties substantially in comparison to the single bond case. While multivalent binding is universally believed to be an attribute of nanoparticles, it is a complex process that is still poorly understood and difficult to control. In this review, we will first discuss experimental studies that have elucidated roles for parameters such as nanoparticle size and shape, targeting ligand and target receptor densities, and monovalent binding kinetics on multivalent nanoparticle adhesion efficiency and cellular internalization. Although such experimental studies are very insightful, information is limited and confounded by numerous differences across experimental systems. Thus, we focus the second part of the review on theoretical aspects of binding, including kinetics, biomechanics, and transport physics. Finally, we discuss various computational and simulation studies of nanoparticle adhesion, including advanced treatments that compare directly to experimental results. Future work will ideally continue to combine experimental data and advanced computational studies to extend our knowledge of multivalent adhesion, as well as design the most powerful nanoparticle-based agents to treat cancer.

Fibrinspecific liposomes as a potential method of delivery of the thrombolytic preparation streptokinase

The use of streptokinase (SK) in the clinic is limited by the lack of fibrin-specificity and the short half-life of the drug. We have developed a new dosage form of streptokinase (immunoliposome), which consists of "free" native streptokinase and "bound" encapsulated in liposomes conjugated through carboxylated dextran with fibrin-specific monoclonal antibodies FnI-3C (IgG2 class), in a ratio of 60 and 40%, respectively, and studied their physicochemical properties, pharmacokinetic parameters, and the ability of fibrin-specific liposomes with SK for targeted delivery to fibrin in an in vivo experiment. The obtained immunoliposomes had a hydrodynamic diameter of ~ 140 nm, a zeta potential of - 19.6 mV, and entrapment efficiency of 14.1%. Fluorescent labels bound to immunoliposomes with streptokinase selectively accumulated in model rat vein thrombi at sites containing fibrin in 30 min after injection. Studies of pharmacokinetic parameters showed that the administration of immunoliposomes with streptokinase to rats was accompanied by an increase in the half-life from 1.8 to 24.1 min, the time to reach the maximum concentration from 15 to 30 min, and a decrease in the elimination constant by about 13 times compared with the native streptokinase preparation. Further studies are needed to evaluate the thrombolytic efficacy a new dosage form of streptokinase in experiment in vivo.

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.

Molecular-Level Examination of Amorphous Solid Dispersion Dissolution

Amorphous solid dispersions (ASDs) are commonly used to orally deliver small-molecule drugs that are poorly water-soluble. ASDs consist of drug molecules in the amorphous form which are dispersed in a hydrophilic polymer matrix. Producing a high-performance ASD is critical for effective drug delivery and depends on many factors such as solubility of the drug in the matrix and the rate of drug release in aqueous medium (dissolution), which is linked to bioperformance. Often, researchers perform a large number of design iterations to achieve this objective. A detailed molecular-level understanding of the mechanisms behind ASD dissolution behavior would aid in the screening, designing, and optimization of ASD formulations and would minimize the need for testing a wide variety of prototype formulations. Molecular dynamics and related types of simulations, which model the collective behavior of molecules in condensed phase systems, can provide unique insights into these mechanisms. To study the effectiveness of these simulation techniques in ASD formulation dissolution, we carried out dissipative particle dynamics simulations, which are particularly an efficient form of molecular dynamics calculations. We studied two stages of the dissolution process: the early-stage of the dissolution process, which focuses on the dissolution at the ASD/water interface, and the late-stage of the dissolution process, where significant drug release would have occurred and there would be a mixture of drug and polymer molecules in a predominantly aqueous environment. Experimentally, we used Fourier transform infrared spectroscopy to study the interactions between drugs, polymers, and water in the dry and wet states and the chromatographic technique to study the rate of drug and polymer release. Both experiments and simulations provided evidence of polymer microstructures and drug-polymer interactions as important factors for the dissolution behavior of the investigated ASDs, consistent with previous work by Pudlas et al. (Eur. J. Pharm. Sci. 2015, 67, 21-31). As experimental and simulation results are consistent and complementary, it is clear that there is significant potential for combined experimental and computational research for a detailed understanding of ASD formulations and, hence, formulation optimization.

Simulation of magnetic nanoparticles crossing through a simplified blood-brain barrier model for Glioblastoma multiforme treatment

BACKGROUND AND OBJECTIVES

Glioblastoma multiforme is considered as one of the most aggressive types of cancer, while various treatment techniques have been proposed. Magnetic nanoparticles (MNPs) loaded with drug and magnetically controlled and targeted to tissues affected by disease, is considered as a possible treatment. However, MNPs are difficult to penetrate the central nervous system and approach the unhealthy tissue, because of the blood-brain barrier (BBB). This study investigates numerically the delivery of magnetic nanoparticles through the barrier driven by normal pressure drop and external gradient magnetic fields, employing a simplified geometrical model, computational fluid dynamics and discrete element method. The goal of the study is to provide information regarding the permeability of the BBB under various conditions like the imposed forces and the shape of the domain, as a preliminary predictive tool.

METHODS

To achieve that, the three-dimensional Navier-Stokes equations are solved in the margin of a blood vessel along with a discrete model for the MNPs with various acting forces. The numerical results are compared with experimental measurements showing that the model can predict acceptably the flow behavior.

RESULTS

The effect of nanoparticles' size, external magnetic field and blood flow in the vessel, on the brain-barrier's permeability are investigated. Three different cases of available area among the endothelial cells per the MNPs' size ratio are also examined, showing that the MNPs' size and available area is not the dominant parameter affecting the permeability of the BBB. The results indicate that the applied magnetic field enhances the drug delivery into the central nervous system (CNS). When larger MNPs (∼100 nm) are exposed to an external magnetic field, the permeability can be improved up to 30%, while it is shown that smaller MNPs (∼10 nm) cannot be driven by the applied magnetic field and in this case the permeability remains relatively unchanged. Finally, the blood flow increase leads to a permeability improvement up to 15%.

CONCLUSIONS

The applied magnetic field improves up to 45% the permeability of the BBB for MNPs of 100 nm. The geometric characteristics of the endothelial cells, the nanoparticles' size and the blood flow are not so decisive parameters for the drug delivery into the CNS, compared to the external magnetic force.

Synchronizing In Silico, In Vitro, and In Vivo Studies for the Successful Nose to Brain Delivery of an Anticancer Molecule

Sesamol is a sesame seed constituent with reported activity against many types of cancer. In this work, two types of nanocarriers, solid lipid nanoparticles (SLNs) and polymeric nanoparticles (PNs), were exploited to improve sesamol efficiency against the glioma cancer cell line. The ability of the proposed systems for efficient brain targeting intranasally was also inspected. By the aid of two docking programs, the virtual loading pattern inside these nanocarriers was matched to the real experimental results. Interactions involved in sesamol-carrier binding were also assessed, followed by a discussion of how different scoring functions account for these interactions. The study is an extension of the computer-assisted drug formulation design series, which represents a promising initiative for an upcoming industrial innovation. The results proved the power of combined in silico tools in predicting members with the highest sesamol payload suitable for delivering a sufficient dose to the brain. Among nine carriers, glyceryl monostearate (GMS) and polycaprolactone (PCL) scored the highest sesamol payload practically and computationally. The EE % was 66.09 ± 0.92 and 61.73 ± 0.47 corresponding to a ΔG (binding energy) of -8.85 ± 0.16 and -5.04 ± 0.11, respectively. Dynamic light scattering evidenced the formation of 215.1 ± 7.2 nm and 414.25 ± 1.6 nm nanoparticles, respectively. Both formulations demonstrated an efficient cytotoxic effect and brain-targeting ability compared to the sesamol solution. This was evidenced by low IC₅₀ (38.50 ± 10.37 μM and 27.81 ± 2.76 μM) and high drug targeting efficiency (7.64 ± 1.89-fold and 13.72 ± 4.1-fold) and direct transport percentages (86.12 ± 3.89 and 92.198 ± 2.09) for GMS-SLNs and PCL-PNs, respectively. The results also showed how different formulations, having different compositions and characteristics, could affect the cytotoxic and targeting ability.

Co-delivery systems: hope for clinical application?

Cancer is a multidimensional and challenging disease to handle. Current statistics reveal that we are far from satisfying cancer treatment. Taking advantage of different therapeutic agents that affect multiple pathways has been established as highly productive. Nevertheless, owing to several hindrances to conventional combination therapy, such as lack of tumor targeting, non-uniform pharmacokinetic of the combined drugs, and off-target side effects, it is well documented that this treatment approach is unlikely to address all the difficulties observed in monotherapy. Co-delivery systems could enhance the therapeutic efficacy of the combination therapy by targeting cancer cells and improving the pharmacokinetic and physicochemical properties of the therapeutic agents. Nevertheless, it seems that present knowledge in responding to the challenges in cancer treatment is still inadequate and far from optimal treatment, which highlights the urgent need for systematic studies direct to identify various aspects of co-delivery systems. Accordingly, to gather informative data, save time, and achieve superior results, the following steps are necessary: (1) implementing computational methods to predict drug-drug interactions (DDIs) in vitro and in vivo, (2) meticulous cancer studies at the cellular and molecular levels to obtain specific criteria for selecting preclinical and clinical models, (3) extensive physiological and pharmacokinetic study of nanocarriers behavior in preclinical models, and (4) finding the optimal formulation and analyzing its behavior in cellular and animal models facilitates bridging in vivo models to clinical trials. This review aims to deliver an overview of co-delivery systems, rationales, and suggestions for further studies in this field.

Evolution of the Computational Pharmaceutics Approaches in the Modeling and Prediction of Drug Payload in Lipid and Polymeric Nanocarriers

This review describes different trials to model and predict drug payload in lipid and polymeric nanocarriers. It traces the evolution of the field from the earliest attempts when numerous solubility and Flory-Huggins models were applied, to the emergence of molecular dynamic simulations and docking studies, until the exciting practically successful era of artificial intelligence and machine learning. Going through matching and poorly matching studies with the wet lab-dry lab results, many key aspects were reviewed and addressed in the form of sequential examples that highlighted both cases.

Gold nanoclusters as prospective carriers and detectors of pramipexole

Pramipexole (PPX) is known in the treatment of Parkinson's disease and restless legs syndrome. We carried out a theoretical investigation on pramipexole–Au cluster interactions for the applications of drug delivery and detection. Three Au_N clusters with sizes N = 6, 8 and 20 were used as reactant models to simulate the metallic nanostructured surfaces. Quantum chemical computations were performed in both gas phase and aqueous environments using density functional theory (DFT) with the PBE functional and the cc-pVDZ-PP/cc-pVTZ basis set. The PPX drug is mainly adsorbed on gold clusters via its nitrogen atom of the thiazole ring with binding energies of ca. −22 to −28 kcal mol⁻¹ in vacuum and ca. −18 to −24 kcal mol⁻¹ in aqueous solution. In addition to such Au–N covalent bonding, the metal–drug interactions are further stabilized by electrostatic effects, namely hydrogen-bond NH⋯Au contributions. Surface-enhanced Raman scattering (SERS) of PPX adsorbed on the Au surfaces and its desorption process were also examined. In comparison to Au₈, both Au₆ and Au₂₀ clusters undergo a shorter recovery time and a larger change of energy gap, being possibly conducive to electrical conversion, thus signaling for detection of the drug. A chemical enhancement mechanism for SERS procedure was again established in view of the formation of nonconventional hydrogen interactions Au⋯H–N. The binding of PPX to a gold cluster is expected to be reversible and triggered by the presence of cysteine residues in protein matrices or lower-shifted alteration of environment pH. These findings would encourage either further theoretical probes to reach more accurate views on the efficiency of pramipexole–Au interactions, or experimental attempts to build appropriate gold nanostructures for practical trials, harnessing their potentiality for applications.

Gold clusters as prospective carriers and detectors of pramipexole.

Understanding nano-engineered particle-cell interactions: biological insights from mathematical models

Understanding the interactions between nano-engineered particles and cells is necessary for the rational design of particles for therapeutic, diagnostic and imaging purposes. In particular, the informed design of particles relies on the quantification of the relationship between the physicochemical properties of the particles and the rate at which cells interact with, and subsequently internalise, particles. Quantitative models, both mathematical and computational, provide a powerful tool for elucidating this relationship, as well as for understanding the mechanisms governing the intertwined processes of interaction and internalisation. Here we review the different types of mathematical and computational models that have been used to examine particle-cell interactions and particle internalisation. We detail the mathematical methodology for each type of model, the benefits and limitations associated with the different types of models, and highlight the advances in understanding gleaned from the application of these models to experimental observations of particle internalisation. We discuss the recent proposal and ongoing community adoption of standardised experimental reporting, and how this adoption is an important step toward unlocking the full potential of modelling approaches. Finally, we consider future directions in quantitative models of particle-cell interactions and highlight the need for hybrid experimental and theoretical investigations to address hitherto unanswered questions.

Computational and experimental approaches for chitosan-based nano PECs design: Insights on a deeper comprehension of nanostructure formation

Nanostructured polyelectrolyte complexes (nano PECs) based on biopolymers are an important technological strategy to target drugs to the action and/or absorption site in a more effective way. In this work, computational studies were performed to predict the ionization, spatial arrangement and interaction energies of chitosan (CS), hyaluronic acid (HA), and hypromellose phthalate (HP), for the design of nano PEC carriers for methotrexate (MTX). The optimal pH range (5.0-5.5) for preparing nano PECs was selected by experimental and computational methodologies, favoring the polymers interactions. CS, HA, HP and MTX addition order was also rationalized, maximizing their interactions and MTX entrapment. Spherical nano-sized particles (256-575 nm, by dynamic light scattering measurement) with positive surface charge (+25.5 to +29.2 mV) were successfully prepared. The MTX association efficiency ranged from 20 to 32 %. XRD analyses evidenced the formation of a new material with an organized structure, in relation to raw polymers.

Mixed-monolayer functionalized gold nanoparticles for cancer treatment: Atomistic molecular dynamics simulations study

Gold nanoparticles (AuNPs) are employed as drug carriers due to their inertness, non-toxicity, and ease of synthesis. An experimental search for the optimal AuNP design would require a systematic variation of physico-chemical properties which is time-consuming and expensive. Computational methods provide quicker and cheaper approach to complement experiments and provide useful guidelines. In this paper, we performed atomistic molecular dynamics simulations to study how the size, hydrophobicity, and concentration of the drug affect the structure of functionalized AuNPs in the aqueous environment. We simulated two groups of nano-systems functionalized with a zwitterionic background ligand, and a ligand carrying a drug (Quinolinol or Panobinostat). Results indicate that in the case of a hydrophobic drug (Quinolinol), the hydrophobicity drives the conformation changes of the coating layer. The tendency of the hydrophobic drug to reduce its solvent-accessible surface results in a decrease of the coating thickness and the overall NP size. Although the amount of accessible drug can be increased by increasing its initial concentration, it will compromise the solubility of the system. In the case of a hydrophilic drug (Panobinostat), the ligand in excess has a dominant influence on the final structure of the coating conformations. The percentage of accessible drug is significantly higher than in the hydrophobic systems for any given ratio. It implies that for hydrophilic systems we can generally expect higher biological efficiency. Our results highlight the importance of taking into account physico-chemical properties of drugs and ligands when developing gold-based nanosystems, especially in the case of hydrophobic drugs.

Computational and Experimental Approaches to Investigate Lipid Nanoparticles as Drug and Gene Delivery Systems

Lipid nanoparticles (LNPs) have been widely applied in drug and gene delivery. More than twenty years ago, DoxilTM was the first LNPs-based drug approved by the US Food and Drug Administration (FDA). Since then, with decades of research and development, more and more LNP-based therapeutics have been used to treat diverse diseases, which often offer the benefits of reduced toxicity and/or enhanced efficacy compared to the active ingredients alone. Here, we provide a review of recent advances in the development of efficient and robust LNPs for drug/gene delivery. We emphasize the importance of rationally combining experimental and computational approaches, especially those providing multiscale structural and functional information of LNPs, to the design of novel and powerful LNP-based delivery systems.

Acidity constant and DFT-based modelling of pH-responsive alendronate loading and releasing on propylamine-modified silica surface

A computational methodology that couples the acidity (K_a) and density functional theory (DFT) calculations has been developed to explain the pH-dependent drug loading on and releasing from mesoporous silica nanoparticles.

On the magnetic aggregation of Fe3O4 nanoparticles

Background and objective In-vivo MRI-guided drug delivery concept is a personalized technique towards cancer treatment. A major bottleneck of this method, is the weak magnetic response of nanoparticles. A crucial improvement is the usage of paramagnetic nanoparticles aggregates since they can easier manipulated in human arteries than isolated particles. However its significance, not a comprehensive study to estimate the mean length and time to aggregate exists. Methods The present detailed numerical study includes all major discrete and continues forces and moments of the nanoscale in a global model. The effort is given in summarizing the effects of particle diameter and concentration, and magnetic field magnitude to comprehensive relations. Therefore, several cases with nanoparticles having various diameters and concentrations are simulated as magnetic field increases. Results It is found that aggregations with maximum length equal to 2000nm can be formed. In addition, the increase of the concentration leads to a decrease in the amount of the isolated particles. Consequently, 33% of the particles are isolated for the concentration of 2.25mg/ml while 13% for the concentration of 10mg/ml. Moreover, the increase of the permanent magnetic field and diameter of particles gives rise to an asymptotic behavior in the number of isolated particles. Furthermore, the mean length of aggregates scales linear with diameter and magnetic field, however, concentration increase results in a weaker effect. The larger aggregation that is formed is composed by 21 particles. Smaller time is needed for the completion of the aggregation process with larger particles. Additionally, the increase of the magnitude of the magnetic field leads to a decrease in the aggregation time process. Therefore, 8.5ms are needed for the completion of the aggregation process for particles of 100nm at B₀=0.1T while 7ms at B₀=0.9T. Surprisedly, the mean time to aggregate is of the same order as in microparticles, although, with an opposite trend. Conclusions In this study, the evolution of the mean length of aggregations as well as the completion time of the aggregation process in the nano and micro range is evaluated. The present results could be useful to improve the magnetic nanoparticles assisted drug delivery method in order to minimize the side effects from the convectional cancer treatments like radiation and chemotherapy.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Comparing cefotaxime and ceftriaxone in combating meningitis through nose-to-brain delivery using bio/chemoinformatics tools

Bio/chemoinformatics tools can be deployed to compare antimicrobial agents aiming to select an efficient nose-to-brain formulation targeting the meningitis disease by utilizing the differences in the main structural, topological and electronic descriptors of the drugs. Cefotaxime and ceftriaxone were compared at the formulation level (by comparing the loading in gelatin and tripalmitin matrices as bases for the formation of nanoparticulate systems), at the biopharmaceutical level (through the interaction with mucin and the P-gp efflux pumps) and at the therapeutic level (through studying the interaction with S. pneumoniae bacterial receptors). GROMACS v4.6.5 software package was used to carry-out all-atom molecular dynamics simulations. Higher affinity of ceftriaxone was observed compared to cefotaxime on the investigated biopharmaceutical and therapeutic macromolecules. Both drugs showed successful docking on mucin, P-gp efflux pump and S. pneumoniae PBP1a and 2b; but ceftriaxone showed higher affinity to the P-gp efflux pump proteins and higher docking on mucin. Ceftriaxone showed less out-of-matrix diffusion and higher entrapment on the gelatin and the tripalmitin matrices. Accordingly, Ceftriaxone gelatin nanospheres or tripalmitin solid lipid nanoparticles may pose a more feasible and efficient nose-to-brain formulation targeting the meningitis disease compared to the cefotaxime counterparts.

Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery

In this review, we outline the growing role that molecular dynamics simulation is able to play as a design tool in drug delivery. We cover both the pharmaceutical and computational backgrounds, in a pedagogical fashion, as this review is designed to be equally accessible to pharmaceutical researchers interested in what this new computational tool is capable of and experts in molecular modeling who wish to pursue pharmaceutical applications as a context for their research. The field has become too broad for us to concisely describe all work that has been carried out; many comprehensive reviews on subtopics of this area are cited. We discuss the insight molecular dynamics modeling has provided in dissolution and solubility, however, the majority of the discussion is focused on nanomedicine: the development of nanoscale drug delivery vehicles. Here we focus on three areas where molecular dynamics modeling has had a particularly strong impact: (1) behavior in the bloodstream and protective polymer corona, (2) Drug loading and controlled release, and (3) Nanoparticle interaction with both model and biological membranes. We conclude with some thoughts on the role that molecular dynamics simulation can grow to play in the development of new drug delivery systems.

Drug-loading capacity of polylactide-based micro- and nanoparticles - Experimental and molecular modeling study

Micro- and nanostructures prepared from biodegradable homopolymers and amphiphilic block copolymers (AmBCs) have found application as drug-delivery systems (DDSs). The ability to accumulate a drug is a very important parameter characterizing a given DDS. This work focuses on the impact of DDS size, the packing of polymer chains in the DDS, and drug - polymer matrix compatibility on the hydrophobic drug - loading capacity (DLC) of nano/microcarriers prepared from a biodegradable polymer or its copolymer. Using experimental measurements in combination with atomistic molecular dynamics simulations, an analysis of curcumin encapsulation in microspheres (MSs) from polylactide (PLA) homopolymer and nanoparticles (NPs) from PLA-block-poly(2-methacryloyloxyethylphosphorylcholine) AmBC was performed. The results show that curcumin has good affinity for the PLA matrix due to its hydrophobic nature. However, the DLC value is limited by the fact that curcumin only accumulates in the peripheral part of these structures. Such uneven drug distribution in the PLA matrix results from the non-homogeneous density of MSs (non-uniform packing of the polymer chains in the coil). The results also indicate that the MSs can retain a greater amount of hydrophobic drug compared to the NPs, which is associated with the formation of drug aggregates inside the PLA microparticles.