Remote Loading Research Articles

Failure of 3D-printed composite continuous carbon fibre hexagonal frames

This study presents an approach to enhancing and expanding the structural performance of composite materials by tailoring their geometry. We explored the potential of continuous carbon fibre composite additive printing to create complaint frames based on hexagonal cell design with the aim to better understand and control their mechanical performance. Our investigation examines the failure behaviour of these frames under remote tensile loading. By experimenting with various geometries and aspect ratios at the frame sites, we gained insight into different failure loads and modes. To predict these results, we developed a computational model based on multiscale homogenisation and the Hashin damage criterion, which showed a high degree of precision compared to our experimental results. The findings validate the effectiveness of our computational model, but also highlight the practical applications of additive manufacturing of composites. This research aims to contribute to the advancement of structural design and material optimisation by engineering of composite materials for specific applications, emphasising the integration of their intrinsic strength and lightweight properties with material efficiency and compliance achieved through geometric design considerations.

Remote loading in liposome: a review of current strategies and recent developments

Remote loading in liposome: a review of current strategies and recent developments

3D stress concentration around circular hole under remote biaxial loading

In this study, a theoretical model is proposed to analyze the stress concentration in a plate of finite thickness containing a circular hole under remote biaxial loading. The stresses in a plate with a circular hole under remote biaxial loading is a superposition of the stresses in the unperforated plate and the released stresses induced by opening the hole. For the latter, the stresses at the edge of the hole can be further decomposed into a spherical component and a deviatoric component. The solution due to a spherical component can be readily obtained but the solution due to a deviatoric component is hard to find. According to the literature, the solution of three-dimensional stress distributions in a plate of finite thickness containing a circular hole can be found by four potential functions. The available fundamental solutions of the potential functions satisfying the boundary conditions on the surfaces of the plate contain numerous complicated integrals, which limits their application to the current problem. Nevertheless, these fundamental solutions can be found explicitly by constructing the orthogonal function, which is composed of the Bessel functions. A system of linear equations is established to satisfy the boundary conditions at the edge of the hole. Therefore, the stresses due to a deviatoric component are obtained by solving the linear simultaneous equations. The stress concentration factor calculated by the proposed model is validated with the available numerical and theoretical solutions. It is concluded that the stress ratio, the thickness of the plate, and Poisson's ratio have an important influence on the distribution of the stress concentration factor along the thickness of the plate, especially on the distribution near the surface. Moreover, the proposed model can be extended to analyze the stress concentration at the edge of a circular hole in a plate of finite thickness under remote bending. The model is efficient and reliable, and it can provide a powerful analytical method to analyze three-dimensional stress concentrations around holes under various remote loading in engineering.

A multiple-objective capacity allocation optimisation method for cogeneration integrated energy systems considering life cycle carbon emission

ABSTRACT With the increasing penetration of renewable sources, the cogeneration integrated energy system (CIES) is much more efficient and flexible to achieve various types of energy supply for remote loads. Due to uncertainties in both sources and loads, the CIES should be carefully planned and optimised to keep it working at the suitable operation condition. Therefore, this paper proposes a multi-objective capacity allocation optimisation method for the islanded CIES, which is composed of renewable energy generation unit, electric-thermal conversion unit, electric storage, thermal storage and various loads. Firstly, three optimisation objectives are selected as typical indexes, including economic cost, solar energy utilisation, and life cycle carbon emission. An improved radar chart evaluation (RCE) solution is subsequently utilised for calculating a fitness function and building the multi-objective optimisation model. Besides, several compulsory constraints are supplemented to ensure the overall CIES performance satisfy energy supply requirement. As a mature and widely accepted algorithm, a genetic algorithm is chosen as an example to obtain the optimal capacity allocation scheme. Case study of an islanded CIES is provided on the basis of real data from the remote region of northwestern China, which successfully verifies the effectiveness of the proposed optimal capacity allocation method.

I+II mixed mode fatigue crack propagation under combination of tensile loading and corrosion in a HSS specimen

Both fatigue and corrosion are two phenomena that can be very often found in metallic components. Thus, it is necessary to study their mutual effect. In this paper, a high strength steel specimen was modelled via finite element method in order to investigate the interaction of a fatigue crack and a corrosion pit. Particularly, a rectangular specimen with a corrosion pit and a nearby angled crack under remote tensile loading was modelled and the crack deflection angle was investigated via MTS and SED criteria for various crack lengths and various crack inclination angles. The results obtained clearly show how the crack behavior is affected by the presence of the corrosion pit.

Corrosion vs. fatigue in a high-strength steel specimen investigated via FEM

The work is devoted to investigations of the stress distribution/concentration in a corroded specimen loaded via remote tensile loading. Existence of corrosion pits of various size and various mutual distance affects stress distribution in a specimen which can have influence on its lifetime. Thus, numerical simulations via finite element method were performed in order to assess the stress field near corrosion pits in specimens made of high-strength steel. The geometry of the numerical model was suggested based on the dimensions of the real specimens produced for fatigue experiments. The results obtained are discussed and mutual comparison with experimental data is intended in oncoming months.

Effect of Shape and Distribution of Secondary Voids on Ductile Crack Path

Ductile fracture in structural metals and alloys comprises of three distinct stages: namely nucleation, growth, and coalescence of voids. In this failure mode voids, either pre-existing in the material or nucleated during deformation grow until they coalesce to form a continuous fracture path. The larger voids nucleating early in the deformation history are often referred to as the primary voids whereas the smaller ones (typically around 0.1 to 0.01 times the size of the primary voids) nucleate much later and are described as the secondary voids. As the imposed deformation increases, voids grow, and the ductile crack path is influenced by the interaction and coalescence of the two-scale voids. The present work numerically models the interaction between the two populations of pre-existing voids lying ahead of the crack tip. The influence of secondary voids attributes, in particular, the shape and distribution of secondary voids on ductile crack propagation is analysed. A plane-strain modified boundary layer (MBL) model, under small-scale yielding condition, subjected to remote mode-I loading is analysed. Both primary and secondary voids lying near the crack tip are modelled explicitly. In the absence of secondary voids, as expected, the crack path is controlled by the distribution of primary voids. The presence of small secondary voids, however, influences the crack growth and, hence, the crack driving force. Various initial configurations of secondary voids are modelled and some details of crack propagation and the numerically computed driving force versus crack extension (J-Δa) curves are presented.

Aqueous remote loading of model cationic peptides in uncapped poly(lactide-co-glycolide) microspheres for long-term controlled release.

Remote loading microencapsulation of peptides into polymer microspheres without organic solvent represents a promising alternative to develop long-acting release depots relative to conventional encapsulation methods. Here, we formulated drug-free microspheres from two kinds of uncapped poly(lactide-co-glycolides) (PLGAs), i.e., ring-opening polymerized Expansorb® DLG 50-2A (50/50, 11.2kDa) and Expansorb® DLG 75-2A (75/25, 9.0kDa), and evaluated their potential capacity to remote-load and control the release of two model peptides, leuprolide and octreotide. Degradation and erosion kinetics, release mechanism, and storage stability was also assessed. As control formulations, peptide was loaded in the same PLGA 75/25 polymer by the conventional double emulsion-solvent evaporation method (W/O/W) and remote loaded in polycondensation poly(lactic-co-glycolic acid) 75/25 (Wako 7515, 14.3kDa). Loading content of 6.7%-8.9% w/w (~ 67%-89% encapsulation efficiency (EE)) was attained for octreotide, and that of 9.5% w/w loading (~ 95% EE) was observed for leuprolide, by the remote loading paradigm. Octreotide and leuprolide were both slowly and continuously released in vitro from the remote-loaded Expansorb® DLG 75-2A MPs for over 56days, which was highly similar to that observed from traditionally-loaded formulations by W/O/W (8.8% loading, 52.8% EE). The faster release kinetics was observed for the faster degrading PLGA 50/50 remote-loaded Expansorb® DLG 50-2A MPs relative to microspheres from the PLGA 75/25 Expansorb® DLG 75-2A. Despite slight differences in degradation kinetics, the release mechanism of octreotide from the Expansorb® microspheres, whether remote loaded or by W/O/W, was identical as determined by release vs. mass loss curves. Octreotide acylation was also minimal (< ~ 10%) for this polymer. Finally, drug-free Expansorb® DLG 75-2A MPs displayed excellent storage stability over 3months. Overall, this work offers support for the use of ring-opening Expansorb® PLGA-based microspheres to remote load peptides to create simple and effective long-acting release depots.

Techno-economic optimization of hydrogen generation through hybrid energy system: A step towards sustainable development

The present study aims to design and optimize a Hybrid Renewable Energy System (HRES) to facilitate a remote community's electricity and hydrogen load demand at Dungri, Uttarakhand, India. The methodology includes an assessment of energy demand, local resource availability, and the nature of the inhabitant. The findings shows techno-economically an optimal HRES, consisting of 90 kW PV, 25 kW Bio-generator, 30 kW electrolyser, 15 kW hydrogen tank, 10 kWh storage and a 30 kW converter with Net present value (NPV) of Rs. 78.4 lakhs, cost of energy (COE) as Rs. 7.61/kWh and cost of hydrogen (COH) Rs. 330/kg. Annual electricity generation is of 250641 kWh/year and yearly average hydrogen generation of 1838 kg through electricity consumption of 80462 kWh/year and can be utilized for 26280 km/year of operation of hydrogen fuelled buses. Furthermore, sensitivity analysis reveals that, rise in the hydrogen load, boost up the system's NPV and COE, whereas,the COH reduces. Amount of annual CO2 emission and avoided are 53.9 kg, 209.12 t, respectively. Moreover, it infers that the proposed system serves isolated rural communities with high-quality energy and satisfies local hydrogen fuel demand in the transportation sector in economically viable manner and achieves the SDG 7 & 8.

Fatigue crack propagation near a corrosion pit in a HSS specimen

Corrosion and fatigue are very common forms of metal degradation, and thus an aspect of the complex issues involved is analysed within this work. A rectangular specimen with a surface fatigue crack and a surface corrosion pit subjected to remote tensile loading was modelled via the finite element method in order to assess the crack behaviour for various configurations of both the crack and the pit. A perpendicular crack was considered along with an angled crack, and the basic fracture parameters have been determined and discussed regarding the influence of the corrosion pit on further crack propagation. Additionally, selected fracture criteria have been applied in their classical one-parameter as well as generalised multi-parameter form to estimate the angle of further crack propagation. The results obtained are discussed thoroughly, and it is proved that the larger the corrosion pit, and the closer it is to the crack, the higher its effect on the fatigue crack behaviour is.

Rapid liposomal formulation for nucleolin targeting to rhabdomyosarcoma cells

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma. More effective and less toxic therapies are urgently needed for high-risk patients. Peptide-guided targeted drug delivery can increase the therapeutic index of encapsulated drugs and improve patients’ well-being. To apply this strategy to RMS, we identified the peptide F3 in a screening for peptides binding to RMS cells surface. F3 binds to nucleolin, which is present on the surface of RMS cells and is abundantly expressed at the mRNA level in RMS patients’ biopsies compared to healthy tissues. We developed a rapid microfluidic formulation of F3-decorated PEGylated liposomes and remote loading of the chemotherapeutic drug vincristine. Size, surface charge, drug loading and retention of targeted and control liposomes were studied. Enhanced cellular binding and uptake were observed in three different nucleolin-positive RMS cell lines. Importantly, F3-functionalized liposomes loaded with vincristine were up to 11 times more cytotoxic than non-targeted liposomes for RMS cell lines. These results demonstrate that F3-functionalized liposomes are promising for targeted drug delivery to RMS and warrant further in vivo investigations.

Influence of nearby fiber on fiber–matrix debonding: Coupled Criterion prediction and debonding shape determination

Fiber–matrix interface debonding in two-fiber specimens under remote tensile loading is studied both experimentally and numerically by means of a coupled stress and energy criterion. Depending on its relative position, the neighboring fiber induces a perturbation of both stress and energy fields at the reference fiber interface which results in asymmetrical debonding initiation and propagation. The determination of the debonding initiation and propagation shape is addressed based on either (i) stress isocontours, (ii) energy isocontours or (iii) the Coupled Criterion (CC). It was found that the debonding initiation configuration can be determined based on stress (respectively energy) isocontours for small (respectively large) enough interface brittleness number. For intermediate brittleness number, the debonding initiation configuration cannot be obtained using neither the stress nor the energy isocontours, but requires a coupling of both aspects. Despite different initiation debonding configurations, the corresponding initiation remote stresses do not differ much, which results in similar debonding configurations after unstable crack propagation following initiation.

Aqueous remote loading of setmelanotide in poly(lactic-co-glycolic acid) microspheres for long-term obesity treatment

Setmelanotide (Imcivree™) was developed as a daily injectable therapeutic peptide for the treatment of rare forms of syndromic obesity, such as POMC deficiency and leptin receptor deficiency. The important option of poly(lactic-co-glycolic acid) (PLGA) controlled release microspheres has become more attractive for this class of drugs upon the discovery that net positively charged peptides can be remote-loaded rapidly from aqueous peptide solution into blank microspheres at high loading and encapsulation efficiency. Here we sought to remote-load setmelanotide in PLGA microspheres and examine its potential for long-term controlled release and body weight control. The influence of PLGA microsphere porosity was investigated with respect to morphology, drug loading, and in vitro release profiles. Increased density of the microspheres inhibited the progress of encapsulation of the dicationic peptide. A diet-induced obese murine model was then used to determine the pharmacokinetic profile and to evaluate long-term efficacy of an optimal formulation. Remote loaded PLGA formulations encapsulated setmelanotide as high as ∼63% (∼6.3% w/w loading) and exhibited slow and continuous peptide release over ∼6 weeks in vitro largely independent of microsphere porosity. The obtained in vivo release pattern from deconvolution of the pharmacokinetics after subcutaneous microsphere injection was consistent with the in vitro release profile but with a lower initial burst release and overall slightly faster release rate. After a single injection of remote-loaded setmelanotide, continuous long-term inhibition of food intake and body weight control was observed over 17 and 30 days, respectively. The improvement in body weight control over drug-free microsphere vehicle-treated control groups matched the observed PK profile. This study provides the first report of long-acting release formulation for 1-month controlled release of setmelanotide and body weight control in a diet induced obese murine model, and supports the further development of long-acting treatment options for obese patients.

Reprogramming the pancreatic cancer stroma and immune landscape by a silicasome nanocarrier delivering nintedanib, a protein tyrosine kinase inhibitor

The prevailing desmoplastic stroma and immunosuppressive microenvironment within pancreatic ductal adenocarcinoma (PDAC) pose substantial challenges to therapeutic intervention. Despite the potential of protein tyrosine kinase (PTK) inhibitors in mitigating the desmoplastic stromal response and enhancing the immune milieu, their efficacy is curtailed by suboptimal pharmacokinetics (PK) and insufficient tumor penetration. To surmount these hurdles, we have pioneered a novel strategy, employing lipid bilayer-coated mesoporous silica nanoparticles (termed "silicasomes") as a carrier for the delivery of Nintedanib. Nintedanib, a triple PTK inhibitor that targets vascular endothelial growth factor, platelet-derived growth factor and fibroblast growth factor receptors, was encapsulated in the pores of silicasomes via a remote loading mechanism for weak bases. This innovative approach not only enhanced pharmacokinetics and intratumor drug concentrations but also orchestrated a transformative shift in the desmoplastic and immune landscape in a robust orthotopic KRAS-mediated pancreatic carcinoma (KPC) model. Our results demonstrate attenuation of vascular density and collagen content through encapsulated Nintedanib treatment, concomitant with significant augmentation of the CD8+/FoxP3+ T-cell ratio. This remodeling was notably correlated with tumor regression in the KPC model. Strikingly, the synergy between encapsulated Nintedanib and anti-PD-1 immunotherapy further potentiated the antitumor effect. Both free and encapsulated Nintedanib induced a transcriptional upregulation of PD-L1 via the extracellular signal-regulated kinase (ERK) pathway. In summary, our pioneering approach involving the silicasome carrier not only improved antitumor angiogenesis but also profoundly reshaped the desmoplastic stromal and immune landscape within PDAC. These insights hold excellent promise for the development of innovative combinatorial strategies in PDAC therapy.

Harnessing Nanomedicine to Potentiate the Chemo-Immunotherapeutic Effects of Doxorubicin and Alendronate Co-Encapsulated in Pegylated Liposomes.

Encapsulation of Doxorubicin (Dox), a potent cytotoxic agent and immunogenic cell death inducer, in pegylated (Stealth) liposomes, is well known to have major pharmacologic advantages over treatment with free Dox. Reformulation of alendronate (Ald), a potent amino-bisphosphonate, by encapsulation in pegylated liposomes, results in significant immune modulatory effects through interaction with tumor-associated macrophages and activation of a subset of gamma-delta T lymphocytes. We present here recent findings of our research work with a formulation of Dox and Ald co-encapsulated in pegylated liposomes (PLAD) and discuss its pharmacological properties vis-à-vis free Dox and the current clinical formulation of pegylated liposomal Dox. PLAD is a robust formulation with high and reproducible remote loading of Dox and high stability in plasma. Results of biodistribution studies, imaging with radionuclide-labeled liposomes, and therapeutic studies as a single agent and in combination with immune checkpoint inhibitors or gamma-delta T lymphocytes suggest that PLAD is a unique product with distinct tumor microenvironmental interactions and distinct pharmacologic properties when compared with free Dox and the clinical formulation of pegylated liposomal Dox. These results underscore the potential added value of PLAD for chemo-immunotherapy of cancer and the relevance of the co-encapsulation approach in nanomedicine.

Remote Loading: The Missing Piece for Achieving High Drug Payload and Rapid Release in Polymeric Microbubbles.

The use of drug-loaded microbubbles for targeted drug delivery, particularly in cancer treatment, has been extensively studied in recent years. However, the loading capacity of microbubbles has been limited due to their surface area. Typically, drug molecules are loaded on or within the shell, or drug-loaded nanoparticles are coated on the surfaces of microbubbles. To address this significant limitation, we have introduced a novel approach. For the first time, we employed a transmembrane ammonium sulfate and pH gradient to load doxorubicin in a crystallized form in the core of polymeric microcapsules. Subsequently, we created remotely loaded microbubbles (RLMBs) through the sublimation of the liquid core of the microcapsules. Remotely loaded microcapsules exhibited an 18-fold increase in drug payload compared with physically loaded microcapsules. Furthermore, we investigated the drug release of RLMBs when exposed to an ultrasound field. After 120 s, an impressive 82.4 ± 5.5% of the loaded doxorubicin was released, demonstrating the remarkable capability of remotely loaded microbubbles for on-demand drug release. This study is the first to report such microbubbles that enable rapid drug release from the core. This innovative technique holds great promise in enhancing drug loading capacity and advancing targeted drug delivery.

Application of ensemble machine learning approach to assess the factors affecting size and polydispersity index of liposomal nanoparticles

Liposome nanoparticles have emerged as promising drug delivery systems due to their unique properties. Assessing particle size and polydispersity index (PDI) is critical for evaluating the quality of these liposomal nanoparticles. However, optimizing these parameters in a laboratory setting is both costly and time-consuming. This study aimed to apply a machine learning technique to assess the impact of specific factors, including sonication time, extrusion temperature, and compositions, on the size and PDI of liposomal nanoparticles. Liposomal solutions were prepared and subjected to sonication with varying values for these parameters. Two compositions: (A) HSPC:DPPG:Chol:DSPE-mPEG2000 at 55:5:35:5 molar ratio and (B) HSPC:Chol:DSPE-mPEG2000 at 55:40:5 molar ratio, were made using remote loading method. Ensemble learning (EL), a machine learning technique, was employed using the Least-squares boosting (LSBoost) algorithm to accurately model the data. The dataset was randomly split into training and testing sets, with 70% allocated for training. The LSBoost algorithm achieved mean absolute errors of 1.652 and 0.0105 for modeling the size and PDI, respectively. Under conditions where the temperature was set at approximately 60 °C, our EL model predicted a minimum particle size of 116.53 nm for composition (A) with a sonication time of approximately 30 min. Similarly, for composition (B), the model predicted a minimum particle size of 129.97 nm with sonication times of approximately 30 or 55 min. In most instances, a PDI of less than 0.2 was achieved. These results highlight the significant impact of optimizing independent factors on the characteristics of liposomal nanoparticles and demonstrate the potential of EL as a decision support system for identifying the best liposomal formulation. We recommend further studies to explore the effects of other independent factors, such as lipid composition and surfactants, on liposomal nanoparticle characteristics.

Use of Stromal Intervention and Exogenous Neoantigen Vaccination to Boost Pancreatic Cancer Chemo-Immunotherapy by Nanocarriers.

Despite the formidable treatment challenges of pancreatic ductal adenocarcinoma (PDAC), considerable progress has been made in improving drug delivery via pioneering nanocarriers. These innovations are geared towards overcoming the obstacles presented by dysplastic stroma and fostering anti-PDAC immune reactions. We are currently conducting research aimed at enhancing chemotherapy to stimulate anti-tumor immunity by inducing immunogenic cell death (ICD). This is accomplished using lipid bilayer-coated nanocarriers, which enable the attainment of synergistic results. Noteworthy examples include liposomes and lipid-coated mesoporous silica nanoparticles known as "silicasomes". These nanocarriers facilitate remote chemotherapy loading, as well as the seamless integration of immunomodulators into the lipid bilayer. In this communication, we elucidate innovative ways for further improving chemo-immunotherapy. The first is the development of a liposome platform engineered by the remote loading of irinotecan while incorporating a pro-resolving lipoxin in the lipid bilayer. This carrier interfered in stromal collagen deposition, as well as boosting the irinotecan-induced ICD response. The second approach was to synthesize polymer nanoparticles for the delivery of mutated KRAS peptides in conjunction with a TLR7/8 agonist. The dual delivery vaccine particle boosted the generation of antigen-specific cytotoxic T-cells that are recruited to lymphoid structures at the cancer site, with a view to strengthening the endogenous vaccination response achieved by chemo-immunotherapy.

Harmonic And Neutral Spherical Elastic Inhomogeneities with A Functionally Graded Interphase Layer

Summary We study the elastic field in a three-phase composite composed of an internal spherical homogeneous elastic inhomogeneity, an intermediate functionally graded interphase layer and an outer unbounded homogeneous elastic matrix subjected to an arbitrary uniform remote loading. The shear modulus of the interphase layer obeys a power law distribution along the radial direction. We accomplish the design of harmonic and neutral spherical elastic inhomogeneities. Specifically, the shear modulus of the matrix can be judiciously chosen in such a way that the insertion of the harmonic spherical inhomogeneity does not disturb the original constant mean stress in the surrounding matrix. The shear modulus of the matrix and relative thickness of the interphase can also be suitably chosen such that the insertion of the neutral spherical inhomogeneity does not disturb the original uniform deviatoric stresses in the surrounding matrix.

Optimizing nanoliposomal formulations: Assessing factors affecting entrapment efficiency of curcumin-loaded liposomes using machine learning

BackgroundCurcumin faces challenges in clinical applications due to its low bioavailability and poor water solubility. Liposomes have emerged as a promising delivery system for curcumin. This study aims to apply ensemble learning, a machine learning technique, to determine the most effective experimental conditions for formulating stable curcumin-loaded liposomes with a high entrapment efficiency (EE). MethodsTwo liposomal formulations composed of HSPC:DPPG:Chol:DSPE-mPEG2000 and HSPC:Chol:DSPE-mPEG2000 at 55:5:35:5 and 55:40:5 M ratios, respectively, were prepared using the remote loading method, and their particle size and polydispersity index (PDI) were determined using Dynamic Light Scattering. To model the impact of five factors (molar ratios, particle size, sonication time, pH, and PDI) on EE%, the Least-squares boosting (LSBoost) ensemble learning algorithm was employed due to its capability to effectively handle nonlinear and non-stationary problems. The implementation and optimization of LSBoost were performed using MATLAB R2020a. The dataset was randomly split into training and testing sets, with 70% allocated for training. The mean absolute error (MAE) was used as the cost function to evaluate model performance. Additionally, a novel approach was employed to visualize the results using 3D plots, facilitating practical interpretation. ResultsThe optimal model exhibited an MAE of 3.61, indicating its robust predictive capability. The study identified several optimal conditions for achieving the highest EE value of 100%. However, to ensure both the highest EE value and a suitable particle size, it is recommended to set the following conditions: a molar ratio of 55:5:35:5, a PDI within the range of 0.09–0.13, a particle size of approximately 130 nm, a sonication time of 30 min, and a pH within the range of 7.2–8. It is worth mentioning that adjusting the molar ratio to 55:40:5 resulted in a maximum EE of 88.38%. ConclusionThese findings underscore the high performance of ensemble learning in accurately predicting and optimizing the EE of the curcumin-loaded liposomes. The application of this technique provides valuable insights and holds promise for the development of efficient drug delivery systems.