Browsing by Subject "Drug delivery systems."

Now showing 1 - 8 of 8

Open Access
Analysis of the in-vitro nanoparticle-cell interactions via smoothing splines mixed effects model
(2013) Doğruöz, Elifnur
A mixed effects statistical model is developed to understand the nanoparticle(NP)- cell interactions and predict the cellular uptake rate of NPs. NP-cell interactions are crucial for targeted drug delivery systems, cell-level diagnosis, and cancer treatment. The NP cellular uptake depends on the size, charge, chemical structure, concentration of NPs, and incubation time. The vast number of combinations of those variable values disallows a comprehensive experimental study of NP-cell interactions. A mathematical model can, however, generalize the findings from some limited number of carefully designed experiments and can be used for the simulation of NP uptake rates for the alternative treatment design, planning, and comparisons. We propose a mathematical model based on the data obtained from in-vitro NPhealthy cell experiments conducted by the Nanomedicine and Advanced Technologies Research Center in Turkey. The proposed model predicts the cellular uptake rate of Silica, polymethyl methacrylate, and polylactic acid NPs given the incubation time, size, charge and concentration of NPs. This study implements the mixed model methodology in nanomedicine area for the first time and is the first mathematical model that predicts NP cellular uptake rate based on sound statistical principles. Our model provides a cost effective tool for researchers developing targeted drug delivery systems.
Open Access
Analysis of the in-vitro nanoparticle-cell interactions via support vector regression model
(2013) Akbulut, Nur Muhammed
In this research a Support Vector Regression model is developed to understand the nanoparticle (NP)-cell interactions and to predict the cellular uptake rate of the nanoparticles, which is the rate of NPs adhered to the cell surface or entered into the cell. Examination of nanoparticle-cell interaction is important for developing targeted drug delivery systems and cell-level detection and treatment of diseases. Cellular uptake rate of NPs depends on NP type, size, shape, surface charge, concentration and incubation time. Conducting numerous experiments on the combinations of those variables to understand NP-cell interaction is impractical. Hence, a mathematical model of the cellular uptake rate will therefore be useful. The data for this study are obtained from in-vitro NP-healthy cell experiments conducted by a Nano-Medicine Research Center in Turkey. The proposed support vector regression model predicts the cellular uptake rate of nanoparticles with respect to incubation time given the size, charge and concentration properties of NPs.
Open Access
Artificial neural networks modeling and simulation of the in-vitro nanoparticles - cell interactions
(2012) Cenk, Neslihan
In this research a prediction model for cellular uptake efficiency of nanoparticles (NPs), which is the rate of NPs adhered to the cell surface or entered into the cell, is investigated via Artificial Neural Network (ANN) method. Prediction of cellular uptake rate of NPs is an important study considering the technical limitations of volatile environment of organism and the time limitation of conducting numerous experiments for thousands of possible variations of different variables that have an impact on NP uptake rate. Moreover, this study constitutes a basis for the targeted drug delivery and cell-level detection, treatment and diagnoses of existing pathologies through simulating experimental procedure of NP-Cell interactions. Accordingly, this study will accelerate nano-medicine researches. The research focuses on constructing a proper ANN model based on multilayered feed-forward back-propagation algorithm for prediction of cellular uptake efficiency which depends on NP type, NP size, NP surface charge, concentration and time. NP types for in-vitro NP-healthy cell interaction analysis are polymethyl methacrylate (PMMA), silica and polylactic acid (PLA) all of whose shapes are spheres. The proposed ANN model has been developed on MATLAB Programming Language by optimizing number of hidden layers, node numbers and training functions. The data sets for training and testing of the network are provided through in-vitro NP-cell interaction experiments conducted by a Nano-Medicine Research Center in Turkey. The dispersion characteristics and cell interactions of the different nanoparticles in organisms are explored through constructing and implementing an optimal prediction model using ANNs. Simulating the possible interactions of targeted nanoparticles with cells via ANN model could lead to a more rapid, more convenient and less expensive approach in comparison to numerous experimental variations.
Open Access
Cell penetrating peptide amphiphile integrated liposomal systems for enhanced delivery of cargo to tumor cells
(2013) Kılınç, Murat
Liposomes have been extensively utilized as effective nanocarriers due to their enhanced solubility, higher stability and greater ability to facilitate the slow release of encapsulated drugs compared to free drug administrations. Liposomes are also preferred as drug vectors due to their non-toxic nature, biodegradability and structural resemblance to the cell membrane. However, their low internalization efficiencies pose an important challenge for their use in drug delivery applications. Internalization issues inherent in many liposomal systems can be circumvented by the use of cell penetrating peptides, which non-covalently attach on the liposome surface and greatly enhance liposomal uptake in a receptor- and charge-dependent manner. In this study, we examined the liposomal dynamics effected through the integration of an amphiphilic cell penetrating peptide into a simple liposome system. Peptide amphiphiles with a cell penetrating arginine-rich domain were incorporated into liposomal membranes formed by negatively charged dioleoylphosphoglycerol (DOPG) phospholipids in the presence of cholesterol. Throughout the present study, we sought to analyze the effect of peptide incorporation on (a) the physical characteristics, such as size, surface potential and membrane polarity, of the liposomal membrane, (b) the alterations in the encapsulation and delivery mechanisms of hydrophilic (Rhodamine B) and hydrophobic (Nile Red) drug models and (c) the enhancement of therapeutic capability in liposomes loaded with the drugs Doxorubicin-HCl and Paclitaxel. Our results revealed that the modification of liposomes by cell penetrating peptide amphiphiles results in the improvement of cargo delivery and the enhancement of the therapeutic effects of the anticancer drugs Doxurubicin and Paclitaxel.
Open Access
Conjugated polymer nanoparticles for biomedical applications including bioimaging and drug delivery
(2013) Ünal, Özlem
Open Access
Generalized linear models for in-vitro nanoparticle-cell interactions
(2013) Çuhacı, Z. Gülce
Nanomedicine techniques are quite promising in terms of treatment and detection of cancerous cells. Targeted drug delivery plays an important role in this field of cancer nanotechnology. A lot of studies have been conducted so far concerning nanoparticle (NP)-cell interaction. Most of them fail to propose a mathematical model for a quantitative prediction of cellular uptake rate with measurable accuracy. In this thesis, we investigate cell-NP interactions and propose statistical models to predict cellular uptake rate. Size, surface charge, chemical structure (type), concentration of NPs and incubation time are known to affect the cellular uptake rate. Generalized linear models are employed to explain the change in uptake rate with the consideration of those effects and their interactions. The data set was obtained from in-vitro NP-healthy cell experiments conducted by the Nanomedicine & Advanced Technologies Research Center in Turkey. Statistical models predicting cellular uptake rate are proposed for sphere-shaped Silica, polymethyl methacrylate (PMMA), and polylactic acid (PLA) NPs.
Open Access
Slow release and delivery of antisense oligonucleotide drug by self-assembled peptide amphiphile nanofibers
(2012) Bulut, Selma
Antisense oligonucleotides are short single stranded DNA sequences and they are suggested to be used for treatment of several disorders including cancer. They could enter the cell and specifically inhibit the target gene, however chemical stability, controlled release and intracellular delivery are areas that has to be focused on to increase their efficacy. Gels composed of nanofibrous peptide network have been previously suggested as carriers for controlled delivery of drugs to improve stability and to provide controlled release, but have not been used for oligonucleotide delivery. In this work, a self-assembled peptide nanofibrous system is formed by mixing a cationic peptide amphiphile (PA) with Bcl-2 antisense oligodeoxynucleotide (ODN), G3139, through electrostatic interactions. The self-assembly of PA-ODN gel was characterized by circular dichroism, rheology, atomic force microscopy (AFM) and scanning electron microscopy (SEM). AFM and SEM images revealed establishment of the nanofibrous PA-ODN network. Due to the electrostatic interactions between PA and ODN, ODN release can be controlled by changing PA and ODN concentrations in the PA-ODN gel. Cellular delivery of the ODN by PA-ODN nanofiber complex was observed by fluorescently labeled ODN molecule. Cells incubated with PA-ODN complex had enhanced cellular uptake compared to cells incubated with naked ODN. Furthermore, Bcl-2 mRNA amounts were lower in MCF-7 human breast cancer cells in the presence of PA-ODN complex compared to naked ODN and mismatch ODN evidenced by quantitative RT-PCR studies. These results suggest that PA molecules can control ODN release, enhance cellular uptake and present a novel efficient approach for gene therapy studies and oligonucleotide based drug delivery. In follow-up studies, increase in the internalization efficacy of ODN by incorporation of bioactive sequences, RGDS, to peptide sequence was also shown.
Open Access
Stimuli-responsive conjugated polymer nanoparticles as simple theranostic platforms = Basit teranostik platformlar olarak uyaranlara hassas konjuge polimer nanoparçacıklar
(2014) Özgün, Alp
In this study, green and near-infrared emitting stimuli responsive conjugated polymer nanoparticles that can be utilized simultaneously for chemotherapeutic drug delivery and bioimaging were synthesized. The nanoparticles are sensitive to low pH values of tumor microenvironment or elevated redox potential of some tumor types. These theranostic platforms could be used for in-vivo imaging and perform controlled-drug release triggered by an appropriate stimulus. For this purpose, green emitting polymer with fluorene and benzothiadiazole alternating units in the backbone and a conjugated polymer emitting in the red-NIR region based on thiophene and benzothiadiazole alternating units in the backbone were synthesized and characterized. Nanoparticles of these polymers (CPNs) were prepared by a simple method called nanoprecipitation where hydrophobic polymer chains collapse onto each other in aqueous media, trapping any other hydrophobic drug molecules (anticancer agent camptothecin in our case) in the environment inside the polymer matrix. Nanoprecipitation process was optimized for each polymer to obtain maximum drug encapsulation rate and a narrow nanoparticle size distribution under 100 nm. Resulting CPNs were stable for a long time in PBS buffer, water, bovine serum albumin and human plasma. SEM images showed spherical particles with a narrow diameter distribution. In vitro drug release studies, pH responsive CPNs showed faster drug release in more acidic media. Redox sensitive red polymer on the other hand showed a cleavage of disulfide bond in its structure in the presence of stimulus. To evaluate the cytotoxicity of drug loaded and blank CPNs RT-CES (real-time cell electronic sensing) assays with HuH-7 cell line have been carried out. While blank CPNs show an insignificant temporary cytotoxicity, camptothecin loaded nanoparticles match or outperform the growth inhibition effect of free camptothecin. Fluorescence microscopy images of HuH-7 cells incubated with CPNs clearly show CPNs that are internalized by cells. In conclusion, it was demonstrated that conjugated polymers could be used to fabricate theranostic platforms without the need for an additional imaging agent and their structures can be engineered to obtain stimuli responsive smart drug delivery systems. These results promise simple and easily fabricated smart systems that can selectively carry anticancer agents to tumors while enabling monitoring of drug distribution and inexpensive tumor imaging without using any harmful rays on the highly energetic side of the electromagnetic spectrum.