Search results for: drug property prediction

Authors: Ravi Sheshala, Annie Lee, Ai Lin Ong, Ling Ling Cheu, Thiagarajan Madheswaran, Thankur R. R. Singh

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The objectives of the present research work were to develop and characterize biodegradable controlled release photo cross-linked implants of Triamcinolone Acetonide (TA) for the treatment of chronic ocular diseases. The photo cross-linked implants were prepared using film casting technique by mixing TA (2.5%) polyethylene glycol diacrylate (PEGDA 700), pore formers (mannitol, maltose, and gelatin) and the photoinitiator (Irgacure 2959). The resulting mixture was injected into moulds using 21 G and subjected to photocrosslinking at 365 nm. Scanning electron microscopy results demonstrated that more pores were formed in the films with the increase in the concentration of pore formers from 2%-10%. The maximum force required to break the films containing 2-10% of pore formers were determined in both dry and wet conditions using texture analyzer and found that films in a dry condition required a higher force to break compared to wet condition and blank films. In vitro drug release from photo cross-linked films were determined by incubating samples in 50 ml PBS pH 7.4 at 37 C and the samples were analyzed for drug release by HPLC. The films demonstrated a biphasic release profile i.e. an initial burst release (<20%) on the first day followed by a constant and continuous drug release in a controlled manner for 42 days. The drug release from all formulations followed the first-order release pattern and the combination of diffusion and erosion release mechanism. In conclusion, the developed formulations were able to provide controlled drug delivery to treat the chronic ocular diseases.

Keywords: controlled release, ophthalmic, PEGDA, photocrosslinking, pore formers

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Authors: Linda Ana Maria Ungureanu

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This article details the manner in which European law establishes the protection and ownership rights over works created in off-world environments or in relation to space exploration. In this sense, the analysis is focused on identifying the legal treatment applicable to creative works based on the provisions regulated under the International Space Treaties, on one side, and the International IP Treaties and subsequent EU legislation, on the other side, with a special interest on ESA Rules and Regulations. Furthermore, the article analyses the manner in which ESA regulates the ownership regime applicable for creative works, taking into account the relationship existing between the inventor/creator and ESA and the environment in which the creative work was developed. Moreover, the article sets a series of de lege ferenda proposals for the regulation of intellectual property matters in the context of space exploration, the main purpose being to identify legal measures and steps that need to be taken in order to ensure that creative activities are fostered and understood as a significant catalyst for encouraging space exploration.

Keywords: intellectual property law, ESA guidelines, international IP treaties, EU legislation

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Amanda C. Q. M. Vieira, Cybelly M. Melo, Camila B. M. Figueirêdo, Giovanna C. R. M. Schver, Salvana P. M. Costa, Magaly A. M. de Lyra, Ping I. Lee, José L. Soares-Sobrinho, Pedro J. Rolim-Neto, Mônica F. R. Soares

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Epiisopiloturine (EPI) is a drug candidate that is extracted from Pilocarpus microphyllus and isolated from the waste of Pilocarpine. EPI has demonstrated promising schistosomicidal, leishmanicide, anti-inflammatory and antinociceptive activities, according to in vitro studies that have been carried out since 2009. However, this molecule shows poor aqueous solubility, which represents a problem for the release of the drug candidate and its absorption by the organism. The purpose of the present study is to investigate the extent of enhancement of kinetic solubility of a solid solution (SS) of EPI in hipromellose phthalate HP-55 (HPMCP), an enteric polymer carrier. SS was obtained by the solvent evaporation methodology, using acetone/methanol (60:40) as solvent system. Both EPI and polymer (drug loading 10%) were dissolved in this solvent until a clear solution was obtained, and then dried in oven at 60ºC during 12 hours, followed by drying in a vacuum oven for 4 h. The results show a considerable modification in the crystalline structure of the drug candidate. For instance, X-ray diffraction (XRD) shows a crystalline behavior for the EPI, which becomes amorphous for the SS. Polarized light microscopy, a more sensitive technique than XRD, also shows completely absence of crystals in SS sample. Differential Scanning Calorimetric (DSC) curves show no signal of EPI melting point in SS curve, indicating, once more, no presence of crystal in this system. Interaction between the drug candidate and the polymer were found in Infrared microscopy, which shows a carbonyl 43.3 cm-1 band shift, indicating a moderate-strong interaction between them, probably one of the reasons to the SS formation. Under sink conditions (pH 6.8), EPI SS had its dissolution performance increased in 2.8 times when compared with the isolated drug candidate. EPI SS sample provided a release of more than 95% of the drug candidate in 15 min, whereas only 45% of EPI (alone) could be dissolved in 15 min and 70% in 90 min. Thus, HPMCP demonstrates to have a good potential to enhance the kinetic solubility profile of EPI. Future studies to evaluate the stability of SS are required to conclude the benefits of this system.

Keywords: epiisopiloturine, hipromellose phthalate HP-55, pharmaceuticaltechnology, solubility

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Authors: Tadesse Melaku Abegaz

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Background: there was paucity of data on the self-reported adverse drug reactions (ADRs), level of adherence and clinical outcomes with antidepressants among major depressive disorder (MDD) patients in Ethiopia. Hence, the present study sought to determine the level of adherence for and clinical outcome with antidepressants and the magnitude of ADRs. Methods: A prospective cross-sectional study was employed on MDD patients from September 2016 to January 2017 at Gondar university hospital psychiatry clinic. All patients who were available during the study period were included under the study population. The Naranjo adverse drug reaction probability scale was employed to assess the adverse drug reaction. The rate of medication adherence was determined using morisky medication adherence measurement scale eight. Clinical Outcome of patients was measured by using patient health questionnaire. Multivariable logistic carried out to determine factors for adherence and patient outcome. Results: two hundred seventy patients were participated in the study. More than half of the respondents were males 122(56.2%). The mean age of the participants was 30.94 ± 8.853. More than one-half of the subjects had low adherence to their medications 124(57.1%). About 186(85.7%) of patients encountered ADR. The most common ADR was weight gain 29(13.2). Around 198(92.2%) ADRs were probable and 19(8.8%) were possible. Patients with long standing MDD had high risk of non-adherence COR: 2.458[4.413-4.227], AOR: 2.424[1.185-4.961]. More than one-half 125(57.6) of respondents showed improved outcome. Optimal level of medication adherence was found to be associated with reduced risk of progression of the diseases COR: 0.37[0.110-5.379] and AOR: 0.432[0.201-0.909]. Conclusion: Patient reported adverse drug reactions were more prevalent in major depressive disorder patients. Adherence to medications was very poor in the setup. However, the clinical outcome was relatively higher. Long standing depression was associated with non-adherence. In addition, clinical outcome of patients were affected by non-adherence. Therefore, adherence enhancing interventions should be provided to improve medication adherence and patient outcome.

Keywords: adverse drug reactions, clinical outcomes, Ethiopia, prospective study, medication adherence

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

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Authors: Jinfeng Zhang, Chun-Sing Lee

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Pure nanodrugs (PNDs) – nanoparticles consisting entirely of drug molecules, have been considered as promising candidates for the next-generation nanodrugs. However, the traditional preparation method via reprecipitation faces critical challenges including low production rates, relatively large particle sizes and batch-to-batch variations. Here, for the first time, we successfully developed a novel, versatile and controllable strategy for preparing PNDs via an anodized aluminium oxide (AAO) template-assisted method. With this approach, we prepared PNDs of an anti-cancer drug (VM-26) with precisely controlled sizes reaching the sub-20 nm range. This template-assisted approach has much higher feasibility for mass production comparing to the conventional reprecipitation method and is beneficial for future clinical translation. The present method is further demonstrated to be easily applicable for a wide range of hydrophobic biomolecules without the need of custom molecular modifications and can be extended for preparing all-in-one nanostructures with different functional agents.

Keywords: drug delivery, pure nanodrugs, size control, template

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Authors: Lubna Azmi, Ila Shukla, Shyam Sundar Gupta, Padam Kant, C. V. Rao

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Elvitegravir is the mainstay of anti-HIV combination therapy in most endemic countries presently. However, it cannot be used alone owing to its long onset time of action. 2-(3,4-dihydroxyphenyl)-3,5,7-trihydroxychromen-4-one (Quercetin: QU) is a polyphenolic compound obtained from Argeria speciosa Linn (Family: Convolvulaceae), an anti-HIV candidate. In the present study, a sensitive, simple and rapid high-performance liquid chromatography coupled with positive ion electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) method was developed for the simultaneous determination elvitegravir and Quercetin, in rat plasma. The method was linear over a range of 0.2–500 ng/ml. All validation parameters met the acceptance criteria according to regulatory guidelines. LC–MS/MS method for determination of Elvitegravir and Quercetin was developed and validated. Results show the potential of drug–drug interaction upon co-administration this marketed drugs and plant derived secondary metabolite.

Keywords: anti-HIV resistance, extraction, HPLC-ESI-MS-MS, validation

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Authors: Gou-Moon Choi, Woo-Young Jung, Chan-Young Yune

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Recently, the natural disaster has increased worldwide. In Korea, the damage to life and property caused by a typhoon, heavy rain, heavy snow, and an extreme wind also increases every year. Among natural disasters, the frequency and the strength of wind have increased because sea surface temperature has risen due to the increase of the average temperature of the Earth. In the case of extreme wind disaster, it is impossible to control or reduce the occurrence, and the recovery cost always exceeds the damage cost. Therefore, quantitative estimation of the damage cost for extreme wind needs to be established beforehand to install proactive countermeasures. In this study, the damage cost for private properties was analyzed based on the data for the past 10 years in Korea. The damage cost curve was also suggested for the metropolitan cities and provinces. The result shows the possibility for the regional application of the damage cost curve because the damage cost of the regional area is estimated based on the cost of cities and provinces.

Keywords: damage cost, extreme wind, natural disaster, private property

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Authors: Min Wu, Shuming Shen, Xuhong Yang, Rencheng Tang

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Every year, numerous organic wastes from fiber byproducts of the wool textile industry, poor quality raw wools not fit for spinning, horns, nails and feathers from butchery are disposed. These wastes are abundant in keratin which is a renewable material. Wool fiber/keratin/PVA composites with different proportions were prepared in this study, and the influence of the proportions on their structure and properties were studied, aiming to understand the potential application of keratin in the field of biomedicine, degradable wrapper, and cosmetics film, and provide a new way to reuse keratin wastes. The urea / sodium sulfide / sodium dodecyl sulfate (SDS) method was used to dissolve the wool. After filtration and dialysis, the wool keratin solution was achieved. Then the keratin solution and polyvinal (PVA) solution were blended in different proportions, and the wool fibers cut into a certain length were cast into the blended solution. Thereby, various wool fiber/keratin/PVA composite films with different proportions were formed through pouring the solution into a flat box and drying at room temperature. The surface morphology, molecular structure, and mechanical property of the composite films were studied. The results showed that, there are α-helix structure, β-sheet and random coil conformations in the pure keratin film, as well as in the wool fiber. Compared with wool fiber, the crystallinity of keratin decreased. PVA can obviously improve the mechanical property of the blended film. When the blended ratio of keratin and PVA is 20:80, the mechanical property of the blended film is greatly improved. The composite films with 8%-16% of wool fibers have better flexibility than those without wool fibers.

Keywords: composite film, keratin, mechanical property, morphological structure, PVA, wool fiber

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Authors: Shouji Yujiro, Memei Dukovic, Mist Yakubu

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Fields are important objects of study in algebra since they provide a useful generalization of many number systems, such as the rational numbers, real numbers, and complex numbers. In particular, the usual rules of associativity, commutativity and distributivity hold. Fields also appear in many other areas of mathematics; see the examples below. When abstract algebra was first being developed, the definition of a field usually did not include commutativity of multiplication, and what we today call a field would have been called either a commutative field or a rational domain. In contemporary usage, a field is always commutative. A structure which satisfies all the properties of a field except possibly for commutativity, is today called a division ring ordivision algebra or sometimes a skew field. Also non-commutative field is still widely used. In French, fields are called corps (literally, body), generally regardless of their commutativity. When necessary, a (commutative) field is called corps commutative and a skew field-corps gauche. The German word for body is Körper and this word is used to denote fields; hence the use of the blackboard bold to denote a field. The concept of fields was first (implicitly) used to prove that there is no general formula expressing in terms of radicals the roots of a polynomial with rational coefficients of degree 5 or higher. An extension of a field k is just a field K containing k as a subfield. One distinguishes between extensions having various qualities. For example, an extension K of a field k is called algebraic, if every element of K is a root of some polynomial with coefficients in k. Otherwise, the extension is called transcendental. The aim of Galois Theory is the study of algebraic extensions of a field. Given a field k, various kinds of closures of k may be introduced. For example, the algebraic closure, the separable closure, the cyclic closure et cetera. The idea is always the same: If P is a property of fields, then a P-closure of k is a field K containing k, having property, and which is minimal in the sense that no proper subfield of K that contains k has property P. For example if we take P (K) to be the property ‘every non-constant polynomial f in K[t] has a root in K’, then a P-closure of k is just an algebraic closure of k. In general, if P-closures exist for some property P and field k, they are all isomorphic. However, there is in general no preferable isomorphism between two closures.

Keywords: field theory, mechanic maths, supertech, rolltech

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Authors: Xiaoci Li, Yonghua Huang, Hui Lin

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Optimization of the concentration of components in mixed refrigerants leads to potential improvement of either thermodynamic cycle performance or safety performance of heat pumps and refrigerators. R32+R1234yf and R125+R290 are two promising binary mixed refrigerants for the application of heat pumps working in the cold areas. The p-ρ-T data of these mixtures are one of the fundamental and necessary properties for design and evaluation of the performance of the heat pumps. Although the property data of mixtures can be predicted by the mixing models based on the pure substances incorporated in programs such as the NIST database Refprop, direct property measurement will still be helpful to reveal the true state behaviors and verify the models. Densities of the mixtures of R32+R1234yf an d R125+R290 are measured by an Anton Paar U shape oscillating tube digital densimeter DMA-4500 in the range of temperatures from 0°C to 100 °C and pressures up to 10 MPa. The accuracy of the measurement reaches 0.00005 g/cm³. The experimental data are compared with the predictions by Refprop in the corresponding range of pressure and temperature.

Keywords: mixed refrigerant, density measurement, densimeter, thermodynamic property

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

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Authors: Caroline Mendes, Mary McNamara, Orla Howe

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Drug delivery systems are proposed for use in cancer treatment to specifically target cancer cells and deliver a therapeutic dose without affecting normal cells. For that purpose, the use of folate receptors (FR) can be considered a key strategy, since they are commonly over-expressed in cancer cells. In this study, cyclodextrins (CD) have being used as vehicles to target FR and deliver the chemotherapeutic drug, methotrexate (MTX). CDs have the ability to form inclusion complexes, in which molecules of suitable dimensions are included within their cavities. Here, β-CD has been modified using folic acid so as to specifically target the FR. Thus, this drug delivery system consists of β-CD, folic acid and MTX (CDEnFA:MTX). Cellular uptake of folic acid is mediated with high affinity by folate receptors while the cellular uptake of antifolates, such as MTX, is mediated with high affinity by the reduced folate carriers (RFCs). This study addresses the gene (mRNA) and protein expression levels of FRs and RFCs in the cancer cell lines CaCo-2, SKOV-3, HeLa, MCF-7, A549 and the normal cell line BEAS-2B, quantified by real-time polymerase chain reaction (real-time PCR) and flow cytometry, respectively. From that, four cell lines with different levels of FRs, were chosen for cytotoxicity assays of MTX and CDEnFA:MTX using the MTT assay. Real-time PCR and flow cytometry data demonstrated that all cell lines ubiquitously express moderate levels of RFC. These experiments have also shown that levels of FR protein in CaCo-2 cells are high, while levels in SKOV-3, HeLa and MCF-7 cells are moderate. A549 and BEAS-2B cells express low levels of FR protein. FRs are highly expressed in all the cancer cell lines analysed when compared to the normal cell line BEAS-2B. The cell lines CaCo-2, MCF-7, A549 and BEAS-2B were used in the cell viability assays. 48 hours treatment with the free drug and the complex resulted in IC50 values of 93.9 µM ± 15.2 and 56.0 µM ± 4.0 for CaCo-2 for free MTX and CDEnFA:MTX respectively, 118.2 µM ± 16.8 and 97.8 µM ± 12.3 for MCF-7, 36.4 µM ± 6.9 and 75.0 µM ± 10.5 for A549 and 132.6 µM ± 16.1 and 288.1 µM ± 26.3 for BEAS-2B. These results demonstrate that free MTX is more toxic towards cell lines expressing low levels of FR, such as the BEAS-2B. More importantly, these results demonstrate that the inclusion complex CDEnFA:MTX showed greater cytotoxicity than the free drug towards the high FR expressing CaCo-2 cells, indicating that it has potential to target this receptor, enhancing the specificity and the efficiency of the drug. The use of cell imaging by confocal microscopy has allowed visualisation of FR targeting in cancer cells, as well as the identification of the interlisation pathway of the drug. Hence, the cellular uptake and internalisation process of this drug delivery system is being addressed.

Keywords: cancer treatment, cyclodextrins, drug delivery, folate receptors, reduced folate carriers

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Authors: K. Rawojć, J. Miszczyk, A. Możdżeń, A. Panek, J. Swakoń, M. Rydygier

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Due to the mitotic delay, poor mitotic index and disappearance of lymphocytes from peripheral blood circulation, assessing the DNA damage after high dose exposure is less effective. Conventional chromosome aberration analysis or cytokinesis-blocked micronucleus assay do not provide an accurate dose estimation or radiosensitivity prediction in doses higher than 6.0 Gy. For this reason, there is a need to establish reliable methods allowing analysis of biological effects after exposure in high dose range i.e., during particle radiotherapy. Lately, Premature Chromosome Condensation (PCC) has become an important method in high dose biodosimetry and a promising treatment modality to cancer patients. The aim of the study was to evaluate the usefulness of drug-induced PCC scoring procedure in an experimental mode, where 100 G2/M cells were analyzed in different dose ranges. To test the consistency of obtained results, scoring was performed by 3 independent persons in the same mode and following identical scoring criteria. Whole-body exposure was simulated in an in vitro experiment by irradiating whole blood collected from healthy donors with 60 MeV protons and 250 keV X-rays, in the range of 4.0 – 20.0 Gy. Drug-induced PCC assay was performed on human peripheral blood lymphocytes (HPBL) isolated after in vitro exposure. Cells were cultured for 48 hours with PHA. Then to achieve premature condensation, calyculin A was added. After Giemsa staining, chromosome spreads were photographed and manually analyzed by scorers. The dose-effect curves were derived by counting the excess chromosome fragments. The results indicated adequate dose estimates for the whole-body exposure scenario in the high dose range for both studied types of radiation. Moreover, compared results revealed no significant differences between scores, which has an important meaning in reducing the analysis time. These investigations were conducted as a part of an extended examination of 60 MeV protons from AIC-144 isochronous cyclotron, at the Institute of Nuclear Physics in Kraków, Poland (IFJ PAN) by cytogenetic and molecular methods and were partially supported by grant DEC-2013/09/D/NZ7/00324 from the National Science Centre, Poland.

Keywords: cell response to radiation exposure, drug induced premature chromosome condensation, premature chromosome condensation procedure, proton therapy

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Authors: Huafeng Wei

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Failures of developing new drugs primarily based on the amyloid pathology hypothesis after decades of efforts internationally lead to changes of focus targeting alternative pathways of pathology in Alzheimer’s disease (AD). Disruption of intracellular Ca2+ homeostasis, especially the pathological and excessive Ca2+ release from the endoplasmic reticulum (ER) via ryanodine receptor (RyRs) Ca2+ channels, has been considered an upstream pathology resulting in major AD pathologies, such as amyloid and Tau pathology, mitochondria damage and inflammation, etc. Therefore, dantrolene, an inhibitor of RyRs that reduces the pathological Ca2+ release from ER and a clinically available drug for the treatment of malignant hyperthermia and muscle spasm, is expected to ameliorate AD multiple pathologies synapse and cognitive dysfunction. Our own studies indicated that dantrolene ameliorated impairment of neurogenesis and synaptogenesis in neurons developed from induced pluripotent stem cells (iPSCs) originated from skin fibroblasts of either familiar (FAD) or sporadic (SAD) AD by restoring intracellular Ca2+ homeostasis. Intranasal administration of dantrolene significantly increased its passage across the blood-brain barrier (BBB) and, therefore its brain concentrations and durations. This can render dantrolene a more effective therapeutic drug with fewer side effects for chronic AD treatment. This review summarizes the potential therapeutic and side effects of dantrolene and repurposes intranasal dantrolene as a disease-modifying drug for future AD treatment.

Keywords: Alzheimer's disease, calcium, drug development, dementia, neurodegeneration, neurogenesis

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Authors: Pawas Suren

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The conflict between livelihood and forest protection has been a perpetual phenomenon in India. In the era of climate change, the problem is expected to aggravate the declining trend of dense forest in the country, creating impediments in the climate change adaptation by the forest dependent communities. In order to access the complexity of the problem, Hazarinagh and Chatra districts of Jharkhand were selected as a case study. To identify norms practiced by the communities to manage community forestry, the ethnographic study was designed to understand the values, traditions, and cultures of forest dependent communities, most of whom were tribal. It was observed that internalization of efficient forest norms is reflected in the pride and honor of such behavior while violators are sanctioned through guilt and shame. The study analyzes the effect of norms being practiced in the management and ecology of community forestry as common property resource. The light of the findings led towards the gaps in the prevalent forest laws to address efficient allocation of property rights. The conclusion embarks on reconsidering accepted factors of forest degradation in India.

Keywords: climate change, common property resource, community forestry, norms

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Harneet Walia, Morteza Zihayat

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Customer acquisition has become one of the critical issues of any business in the 21st century; having a healthy customer base is the essential asset of the bank business. Term deposits act as a major source of cheap funds for the banks to invest and benefit from interest rate arbitrage. To attract customers, the marketing campaigns at most financial institutions consist of multiple outbound telephonic calls with more than one contact to a customer which is a very time-consuming process. Therefore, customized direct marketing has become more critical than ever for attracting new clients. As customer acquisition is becoming more difficult to archive, having an intelligent and redefined list is necessary to sell a product smartly. Our aim of this research is to increase the effectiveness of campaigns by predicting customers who will most likely subscribe to the fixed deposit and suggest the most suitable month to reach out to customers. We design a Time Aware Upsell Prediction Framework (TAUPF) using two different approaches, with an aim to find the best approach and technique to build the prediction model. TAUPF is implemented using Upsell Prediction Approach (UPA) and Clustered Upsell Prediction Approach (CUPA). We also address the data imbalance problem by examining and comparing different methods of sampling (Up-sampling and down-sampling). Our results have shown building such a model is quite feasible and profitable for the financial institutions. The Time Aware Upsell Prediction Framework (TAUPF) can be easily used in any industry such as telecom, automobile, tourism, etc. where the TAUPF (Clustered Upsell Prediction Approach (CUPA) or Upsell Prediction Approach (UPA)) holds valid. In our case, CUPA books more reliable. As proven in our research, one of the most important challenges is to define measures which have enough predictive power as the subscription to a fixed deposit depends on highly ambiguous situations and cannot be easily isolated. While we have shown the practicality of time-aware upsell prediction model where financial institutions can benefit from contacting the customers at the specified month, further research needs to be done to understand the specific time of the day. In addition, a further empirical/pilot study on real live customer needs to be conducted to prove the effectiveness of the model in the real world.

Keywords: customer acquisition, predictive analysis, targeted marketing, time-aware analysis

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Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: N. Yachou, R. Aboulaich

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Home is a basic necessity for human life, that why home financing takes a large chunk of people’s income. Therefore, Islamic and Conventional Banks try to offer new product in order to respond to customer needs related to home financing. Basing on this fact, we propose a Modified Diminishing Partnership model based on profit and loss sharing to reduce the duration of getting the full shares in the house property. Our proposition will be represented by the rental that customer has to give every month to the bank with redemption to increase his shares on the property of the house.

Keywords: home financing, interest rate, rental rate, modified diminishing partnership

Procedia PDF Downloads 321

Authors: X. King, E. Nazarzadeh, J. Reboud, J. Cooper

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Pulmonary diseases, such as asthma, are generally treated by the inhalation of aerosols that has the advantage of reducing the off-target (e.g., toxicity) effects associated with systemic delivery in blood. Effective respiratory drug delivery requires a droplet size distribution between 1 and 5 µm. Inhalation of aerosols with wide droplet size distribution, out of this range, results in deposition of drug in not-targeted area of the respiratory tract, introducing undesired side effects on the patient. In order to solely deliver the drug in the lower branches of the lungs and release it in a targeted manner, a control mechanism to produce the aerosolized droplets is required. To regulate the drug release and to facilitate the uptake from cells, drugs are often encapsulated into protective liposomes. However, a multistep process is required for their formation, often performed at the formulation step, therefore limiting the range of available drugs or their shelf life. Using surface acoustic waves (SAWs), a pulmonary drug delivery platform was produced, which enabled the formation of defined size aerosols and the formation of liposomes in situ. SAWs are mechanical waves, propagating along the surface of a piezoelectric substrate. They were generated using an interdigital transducer on lithium niobate with an excitation frequency of 9.6 MHz at a power of 1W. Disposable silicon superstrates were etched using photolithography and dry etch processes to create an array of cylindrical through-holes with different diameters and pitches. Superstrates were coupled with the SAW substrate through water-based gel. As the SAW propagates on the superstrate, it enables nebulisation of a lipid solution deposited onto it. The cylindrical cavities restricted the formation of large drops in the aerosol, while at the same time unilamellar liposomes were created. SAW formed liposomes showed a higher monodispersity compared to the control sample, as well as displayed, a faster production rate. To test the aerosol’s size, dynamic light scattering and laser diffraction methods were used, both showing the size control of the aerosolised particles. The use of silicon superstate with cavity size of 100-200 µm, produced an aerosol with a mean droplet size within the optimum range for pulmonary drug delivery, containing the liposomes in which the medicine could be loaded. Additionally, analysis of liposomes with Cryo-TEM showed formation of vesicles with narrow size distribution between 80-100 nm and optimal morphology in order to be used for drug delivery. Encapsulation of nucleic acids in liposomes through the developed SAW platform was also investigated. In vitro delivery of siRNA and DNA Luciferase were achieved using A549 cell line, lung carcinoma from human. In conclusion, SAW pulmonary drug delivery platform was engineered, in order to combine multiple time consuming steps (formation of liposomes, drug loading, nebulisation) into a unique platform with the aim of specifically delivering the medicament in a targeted area, reducing the drug’s side effects.

Keywords: acoustics, drug delivery, liposomes, surface acoustic waves

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Authors: Minh-Phuong Ngoc Bui, Abdennour Abbas

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Microbial spoilage of food/drug has been a constant nuisance and an unavoidable problem throughout history that affects food/drug quality and safety in a variety of ways. A simple and rapid test of fungi and bacteria in food/drugs and environmental clinical samples is essential for proper management of contamination. A number of different techniques have been developed for detection and enumeration of foodborne microorganism including plate counting, enzyme-linked immunosorbent assay (ELISA), polymer chain reaction (PCR), nucleic acid sensor, electrical and microscopy methods. However, the significant drawbacks of these techniques are highly demand of operation skills and the time and cost involved. In this report, we introduce a rapid method for detection of bacteria and fungi in food/drug products using a specific interaction between a reducing agent (tris(2-carboxylethyl)phosphine (TCEP)) and the microbial surface proteins. The chemical reaction was transferred to a transduction system using gold nanoplates-enhanced chemiluminescence. We have optimized our nanoplates synthetic conditions, characterized the chemiluminescence parameters and optimized conditions for the microbial assay. The new detection method was applied for rapid detection of bacteria (E.coli sp. and Lactobacillus sp.) and fungi (Mucor sp.), with limit of detection as low as single digit cells per mL within 10 min using a portable luminometer. We expect our simple and rapid detection method to be a powerful alternative to the conventional plate counting and immunoassay methods for rapid screening of microorganisms in food/drug products.

Keywords: microorganism testing, gold nanoplates, chemiluminescence, reducing agents, luminol

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Authors: Hamida Hamed Said Al Harthi

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Background: Illegal drug use is a rising problem that affects Omani youth. This research aimed to study a group of young Omani men who were imprisoned more than once for illegal drug use, focusing on exploring their lifestyle experiences inside and outside the prison and whether these contributed to their early relapse and re-imprisonment. This is the first study of its kind from Oman conducted in a prison setting. Methods: 19 Omani males aged 18–35 years imprisoned in Oman Central Prison were recruited using purposive sampling. Focused ethnography was conducted over 8 months to explore the drug-related experiences outside the prison and during imprisonment. Face-to-face semi-structured interviews with the participants yielded detailed transcripts and field notes. These were thematically analyzed, and the results were compared with the existing literature. Results: The participants’ voices yielded new insights into the lives of young Omani men imprisoned for illegal drug use, including their sufferings and challenges in prison. These included: entry shock, timing and boredom, drug trafficking in prison, as well as physical and psychological health issues. Overall, imprisonment was reported to have negatively impacted the participants’ health, personality, self-concept, emotions, attitudes, behavior and life expectations. The participants reported how their efforts to reintegrate into the Omani community after release from prison were rebuffed due to stigmatization and rejection from society and family. They also experienced frequent unemployment, police surveillance, accommodation problems and a lack of rehabilitation facilities. The immensity of the accumulated psychophysiological trauma contributed to their early relapse and re-imprisonment. Conclusion: This thesis concludes that imprisonment is largely ineffective in controlling drug use in Oman. Urgent action is required across multiple sectors to improve the lives and prospects of users of illegal drugs within and outside the prison to minimize factors contributing to early relapse. Key Words: illegal drugs, drug users, Oman, addiction, Omani culture, prisoners, relapse, re-imprisonment, qualitative research, ethnography.

Keywords: illigal drugs, Prison, Omani culture lifestyle, post prison life

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Authors: Shivahari Revathi Venkateswaran

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Segmenting customers plays a significant role in churn prediction. It helps the marketing team with proactive and reactive customer retention. For the reactive retention, the retention team reaches out to customers who already showed intent to disconnect by giving some special offers. When coming to proactive retention, the marketing team uses churn prediction model, which ranks each customer from rank 1 to 100, where 1 being more risk to churn/disconnect (high ranks have high propensity to churn). The churn prediction model is built by using XGBoost model. However, with the churn rank, the marketing team can only reach out to the customers based on their individual ranks. To profile different groups of customers and to frame different marketing strategies for targeted groups of customers are not possible with the churn ranks. For this, the customers must be grouped in different segments based on their profiles, like demographics and other non-controllable attributes. This helps the marketing team to frame different offer groups for the targeted audience and prevent them from disconnecting (proactive retention). For segmentation, machine learning approaches like k-mean clustering will not form unique customer segments that have customers with same attributes. This paper finds an alternate approach to find all the combination of unique segments that can be formed from the user attributes and then finds the segments who have uplift (churn rate higher than the baseline churn rate). For this, search algorithms like fast search and recursive search are used. Further, for each segment, all customers can be targeted using individual churn ranks from the churn prediction model. Finally, a UI (User Interface) is developed for the marketing team to interactively search for the meaningful segments that are formed and target the right set of audience for future marketing campaigns and prevent them from disconnecting.

Keywords: churn prediction modeling, XGBoost model, uplift segments, proactive marketing, search algorithms, retention, k-mean clustering

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Authors: Abhay Asthana, Gyati Shilakari Asthana

Abstract:

It’s the patient compliance and stability in combination with controlled drug delivery and biocompatibility that forms the core feature in present research and development of sustained biodegradable patch formulation intended for wound healing. The aim was to impart sustained degradation, sterile formulation, significant folding endurance, elasticity, biodegradability, bio-acceptability and strength. The optimized formulation was developed using component including polymers including Hydroxypropyl methyl cellulose, Ethylcellulose, and Gelatin, and Citric Acid PEG Citric acid (CPEGC) triblock dendrimers and active Curcumin. Polymeric mixture dissolved in geometric order in suitable medium through continuous stirring under ambient conditions. With continued stirring Curcumin was added with aid of DCM and Methanol in optimized ratio to get homogenous dispersion. The dispersion was sonicated with optimum frequency and for given time and later casted to form a patch form. All steps were carried out under under strict aseptic conditions. The formulations obtained in the acceptable working range were decided based on thickness, uniformity of drug content, smooth texture and flexibility and brittleness. The patch kept on stability using butter paper in sterile pack displayed folding endurance in range of 20 to 23 times without any evidence of crack in an optimized formulation at room temperature (RT) (24 ± 2°C). The patch displayed acceptable parameters after stability study conducted in refrigerated conditions (8±0.2°C) and at RT (24 ± 2°C) upto 90 days. Further, no significant changes were observed in critical parameters such as elasticity, biodegradability, drug release and drug content during stability study conducted at RT 24±2°C for 45 and 90 days. The drug content was in range 95 to 102%, moisture content didn’t exceeded 19.2% and patch passed the content uniformity test. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as drug release with correlation factor R2>0.9. The biodegradable patch based formulation developed shows promising results in terms of stability and release profiles.

Keywords: sustained biodegradation, wound healing, polymers, stability

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Authors: Yuvraj Singh Dangi, Kamta Prasad Namdeo, Surendra Bodhake

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The purpose of this research was to develop and evaluate mucoadhesive films for buccal administration of itraconazole using film-forming and mucoashesive polymers. Buccal films of chitosan bearing Itraconazole were prepared by solvent casting technique. The films have been evaluated in terms of film weight, thickness, density, surface pH, FTIR, X-ray diffraction analysis, bioadhesion, swelling properties, and in vitro drug release studies. It was found that film formulations of 2 cm2 size having weight in the range of 204 ± 0.76 to 223 ± 2.09 mg and film thickness were in the range of 0.44 ± 0.11 to 0.57 ± 0.19 mm. Density of the films was found to be 0.102 to 0.126 g/ml. Drug content was found to be uniform in the range of 8.23 ± 0.07 to 8.73 ± 0.09 mg/cm2 for formulation A1 to A4. Maximum bioadhesion force was recorded for HPMC buccal films (A2) i.e. 0.57 ± 0.47 as compared to other films. In vitro residence time was in range of 1.7 ± 0.12 to 7.65 ± 0.15 h. The drug release studies show that formulations follow non-fickian diffusion. These mucoadhesive formulations could offer many advantages in comparison to traditional treatments.

Keywords: biovariability, buccal patches, itraconazole, Mucoadhesion

Procedia PDF Downloads 489