Search results for: drug prediction

Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

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Authors: Tarek Aboueldahab, Amin Mohamed Nassar

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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.

Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction

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Authors: Magdalena Hałupka-Bryl, Magdalena Bednarowicz, Ryszard Krzyminiewski, Yukio Nagasaki

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Due to their unique physical properties, superparamagnetic iron oxide nanoparticles are increasingly used in medical applications. They are very useful carriers for delivering antitumor drugs in targeted cancer treatment. Magnetic nanoparticles (PEG-PIONs/DOX) with chemotherapeutic were synthesized by coprecipitation method followed by coating with biocompatible polymer PEG-derivative (poly(ethylene glycol)-block-poly(4-vinylbenzylphosphonate). Complete physicochemical characterization was carried out (ESR, HRTEM, X-ray diffraction, SQUID analysis) to evaluate the magnetic properties of obtained PEG-PIONs/DOX. Nanoparticles were investigated also in terms of their stability, drug loading efficiency, drug release and antiproliferative effect on cancer cells. PEG-PIONs/DOX have been successfully used for the efficient delivery of an anticancer drug into the tumor region. Fluorescent imaging showed the internalization of PEG-PIONs/DOX in the cytoplasm. Biodistribution studies demonstrated that PEG-PIONs/DOX preferentially accumulate in tumor region via the enhanced permeability and retention effect. The present findings show that synthesized nanosystem is promising tool for potential magnetic drug delivery.

Keywords: targeted drug delivery, magnetic properties, iron oxide nanoparticles, biodistribution

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Authors: Raquel Galante, Marina Braga, Daniela Ghisleni, Terezinha J. A. Pinto, Rogério Colaço, Ana Paula Serro

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The sensitive nature of soft biomaterials, such as hydrogels, renders their sterilization a particularly challenging task for the biomedical industry. Widely used contact lenses are now studied as promising platforms for topical corneal drug delivery. However, to the best of the authors knowledge, the influence of sterilization methods on these systems has yet to be evaluated. The main goal of this study was to understand how different pairs drug-hydrogel would interact under an ozone-based sterilization method in comparison with two conventional processes (steam heat and gamma irradiation). For that, Si-Hy containing hydroxylethyl methacrylate (HEMA) and [tris(trimethylsiloxy)silyl]propyl methacrylate (TRIS) was produced and soaked in different drug solutions, commonly used for the treatment of ocular diseases (levofloxacin, chlorhexidine, diclofenac and timolol maleate). The drug release profiles and main material properties were evaluated before and after the sterilization. Namely, swelling capacity was determined by water uptake studies, transparency was accessed by UV-Vis spectroscopy, surface topography/morphology by scanning electron microscopy (SEM) and mechanical properties by performing tensile tests. The drug released was quantified by high performance liquid chromatography (HPLC). The effectiveness of the sterilization procedures was assured by performing sterility tests. Ozone gas method led to a significant reduction of drug released and to the formation of degradation products specially for diclofenac and levofloxacin. Gamma irradiation led to darkening of the loaded Si-Hys and to the complete degradation of levofloxacin. Steam heat led to smoother surfaces and to a decrease of the amount of drug released, however, with no formation of degradation products. This difference in the total drug released could be the related to drug/polymer interactions promoted by the sterilization conditions in presence of the drug. Our findings offer important insights that, in turn, could be a useful contribution to the safe development of actual products.

Keywords: drug delivery, silicone hydrogels, sterilization, gamma irradiation, steam heat, ozone gas

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Pengwei Qiao, Sucai Yang, Wenxia Wei

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Soil pollution has become an important issue in China. Accurate spatial distribution prediction of pollutants with interpolation methods is the basis for soil remediation in the site. However, a relatively strong variability of pollutants would decrease the prediction accuracy. Theoretically, partition interpolation can result in accurate prediction results. In order to verify the applicability of partition interpolation for a site, benzo (b) fluoranthene (BbF) in four soil layers was adopted as the research object in this paper. IDW (inverse distance weighting)-, RBF (radial basis function)-and OK (ordinary kriging)-based partition interpolation accuracies were evaluated, and their influential factors were analyzed; then, the uncertainty and applicability of partition interpolation were determined. Three conclusions were drawn. (1) The prediction error of partitioned interpolation decreased by 70% compared to unpartitioned interpolation. (2) Partition interpolation reduced the impact of high CV (coefficient of variation) and high concentration value on the prediction accuracy. (3) The prediction accuracy of IDW-based partition interpolation was higher than that of RBF- and OK-based partition interpolation, and it was suitable for the identification of highly polluted areas at a contaminated site. These results provide a useful method to obtain relatively accurate spatial distribution information of pollutants and to identify highly polluted areas, which is important for soil pollution remediation in the site.

Keywords: accuracy, applicability, partition interpolation, site, soil pollution, uncertainty

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Filipa Vasconcelos

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The administration of endoplasmic reticulum amino peptidases (ERAP1 or ERAP2) inhibitors can be used for therapeutic approaches against cancer and auto-immune diseases. However, one of the main shortcomings of drug delivery systems (DDS) is associated with the drug off-target distribution, which can lead to an increase in its side effects on the patient’s body. To overcome such limitations, the encapsulation of four representative compounds of ERAP inhibitors into Polycaprolactone (PCL), Polyvinyl-alcohol (PVA), crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes is proposed as a safe and controlled drug release system. The use of electrospun fibrous meshes as a DDS allows efficient solvent evaporation giving limited time to the encapsulated drug to recrystallize, continuous delivery of the drug while the fibers degrade, prevention of initial burst release (sustained release), tunable dosages, and the encapsulation of other agents. This is possible due to the fibers' small diameters and resemblance to the extracellular matrix (confirmed by scanning electron microscopy results), high specific surface area, and good mechanical strength/stability. Furthermore, release studies conducted on PCL, PVA, crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes with each of the ERAP compounds encapsulated demonstrated that they were capable of releasing >60%, 50%, 40%, and 45% of the total ERAP concentration, respectively. Fibrous meshes with ERAP_E compound encapsulated achieved higher released concentrations (75.65%, 62.41%, 56.05%, and 65.39%, respectively). Toxicity studies of fibrous meshes with encapsulated compounds are currently being accessed in vitro, as well as pharmacokinetics and dynamics studies. The last step includes the implantation of the drug-loaded fibrous meshes in vivo.

Keywords: drug delivery, electrospinning, ERAP inhibitors, liposomes

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Authors: Pingshan Chen, Zhiliang Dong

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In order to estimate the post-construction settlement more objectively, the power-polynomial model is proposed, which can reflect the trend of settlement development based on the observed settlement data. It was demonstrated by an actual case history of an embankment, and during the prediction. Compared with the other three prediction models, the power-polynomial model can estimate the post-construction settlement more accurately with more simple calculation.

Keywords: prediction, model, post-construction settlement, soft ground

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Authors: Ashish Jain, Satish Nayak

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Transdermal iontophoretic drug delivery system is viable drug delivery platform technology and has a strong market worldwide. Transdermal drug delivery system is particularly desirable for therapeutic agents that need prolonged administration at controlled plasma level. This makes appropriateness to antihypertensive and anti-diabetic agents for their transdermal development. Controlled zero order absorption, easily termination of drug delivery and easy to administration also support for popularity of transdermal delivery. In this current research iontophoretic delivery of various anti diabetic agents like glipizide, glibenclamide and glimepiride were carried out. The experiments were carried out at different drug concentrations and different current densities using cathodal iontophoresis. Diffusion cell for iontophoretic permeation study was modified according to Glikfield Design. Pig skin was used for in vitro permeation study and for the in-vivo study New Zealand rabbits were used. At all concentration level iontophoresis showed enhanced permeation rate compared to passive controls. Iontophoretic transports of selected drugs were found to be increased with the current densities. Results showed that target permeation rate for selected drugs could be achieved with the aid of iontophoresis by increasing the area in an appreciable range.

Keywords: transdermal, iontophoresis, pig skin, rabbits, glipizide, glibeclamide

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Authors: Annie Ramanbhai Mecwan

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Cleaning validation in a pharmaceutical manufacturing facility is documented evidence that a cleaning process has effectively removed contaminants, residues from previous drug products and cleaning agents below a pre-defined threshold from the reusable tools and parts of equipment. In shared manufacturing facilities more than one drug product is prepared. After cleaning of reusable tools and parts of equipment after one drug product manufacturing, there are chances that some residues of drug substance from previously manufactured drug products may be retained on the equipment and can carried forward to the next drug product and thus cause cross-contamination. Health-based limits through the derivation of a safe threshold value called permitted daily exposure (PDE) for the residues of drug substances should be employed to identify the risks posed at these manufacturing facilities. The PDE represents a substance-specific dose that is unlikely to cause an adverse effect if an individual is exposed to or below this dose every day for a lifetime. There are different practices to calculate PDE. Data for all APIs in the public domain are considered to calculate PDE value though, company to company may vary the final PDE value based on different toxicologist’s perspective or their subjective evaluation. Hence, Regulatory agencies should take responsibility for publishing PDE values for all APIs as it is done for elemental PDEs. This will harmonize the PDE values all over the world and prevent the unnecessary load on manufacturers for cleaning validation

Keywords: active pharmaceutical ingredient, good manufacturing practice, NOAEL, no observed adverse effect level, permitted daily exposure

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Authors: Qin Wei

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There has been an increased number of immigrants arriving in Canada and a concurrent rise in the number of immigrant youth suffering from drug abuse. Immigrant youths’ drug abuse has become a significant social and public health concern for researchers. This literature review explores the nature of immigrant youths’ drug abuse by examining the factors influencing the onset of substance misuse, the barriers that discourage youth to seek out treatment, and how to resolve addictions amidst immigrant youth. Findings from the literature demonstrate that diminished parental supervision, acculturation challenges, peer conformity, discrimination, and ethnic marginalization are all significant factors influencing youth to use drugs as an outlet for their pain, while culturally competent care and fear of family and culture-based addiction stigma act as barriers discouraging youth from seeking out addiction support. To resolve addiction challenges amidst immigrant youth, future research should focus on promoting and implementing culturally sensitive practices and psychoeducational initiatives into immigrant communities and within public health policies.

Keywords: approaches, barriers, drug abuse, Canada, immigrant youth, reasons

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Ashish Jain, Shivam Tayal

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There has been great interest in the field of Iontophoresis since few years due to its great applications in the field of controlled transdermal drug delivery system. It is an technique which is used to enhance the transdermal permeation of ionized high molecular weight molecules across the skin membrane especially Peptides & Proteins by the application of direct current of 1-4 mA for 20-40 minutes whereas chemical must be placed on electrodes with same charge. Iontophoresis enhanced the delivery of drug into the skin via pores like hair follicles, sweat gland ducts etc. rather than through stratum corneum. It has wide applications in the field of experimental, Therapeutic, Diagnostic, Dentistry etc. Medical science is using it to treat Hyperhidrosis (Excessive sweating) in hands and feet and to treat other ailments like hypertension, Migraine etc. Nowadays commercial transdermal iontophoretic patches are available in the market to treat different ailments. Researchers are keen to research in this field due to its vast applications and advantages.

Keywords: iontophoresis, novel drug delivery, transdermal, permeation enhancer

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Authors: Sophie N. Selby-Pham, Yudie Wang, Louise Bennett

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Consumption of grapes promotes health and reduces the risk of chronic diseases due to the action of grape phytochemicals in regulation of Oxidative Stress and Inflammation (OSI). The bioefficacy of phytochemicals depends on their absorption in the human body. The time required for phytochemicals to achieve maximal plasma concentration (Tₘₐₓ) after oral intake reflects the time window of maximal bioefficacy of phytochemicals, with Tₘₐₓ dependent on physicochemical properties of phytochemicals. This research collated physicochemical properties of grape phytochemicals from white and red grapes to predict their Tₘₐₓ using pharmacokinetic modelling. The predicted values of Tₘₐₓ were then compared to the measured Tₘₐₓ collected from clinical studies to determine the accuracy of prediction. In both liquid and solid intake forms, white grapes exhibit a shorter Tₘₐₓ range (0.5-2.5 h) versus red grapes (1.5-5h). The prediction accuracy of Tₘₐₓ for grape phytochemicals was 33.3% total error of prediction compared to the mean, indicating high prediction accuracy. Pharmacokinetic modelling allows prediction of Tₘₐₓ without costly clinical trials, informing dosing frequency for sustained presence of phytochemicals in the body to optimize the health benefits of phytochemicals.

Keywords: absorption kinetics, phytochemical, phytochemical absorption prediction model, Vitis vinifera

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Authors: Abhishek Kumar Sah, Preeti K. Suresh

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Effective drug delivery to the eye is a massive challenge, due to complicated physiological ocular barriers, rapid washout by tear and nasolachrymal drainage. Thus, most of the conventional ophthalmic formulations face the problem of low ocular bioavailability. Ophthalmic drug therapy can be improved by enhancing the precorneal drug retention along with improved drug penetration. The aim of the present investigation was to develop and evaluate a biodegradable polymer poly (D, L-lactide-co-glycolide) (PLGA) coated nanoparticulate carrier of loteprednol etabonate. PLGA nanoparticles were prepared by modified emulsification/solvent diffusion method using high-speed homogenizer followed by sonication. The nanoparticles were characterized for various parameters such as particle size, zeta potential, polydispersity index, X-ray powder diffraction (XRD), Transmission electron microscopy (TEM), in vitro drug release profile and stability. The prepared nanocarriers displayed mean particle size in the range of 271.7 to 424.4 nm, with zeta potential less than –10 mV. In vitro release in simulated tear fluid (STF) nanocarrier showed an extended release profile of loteprednol etabonate. TEM confirmed the spherical morphology and smooth surface of the particles. All the prepared formulations were found to be stable at varying temperatures.

Keywords: drug delivery, ocular delivery, polymeric nanoparticles, loteprednol etabonate

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Authors: Bushra Nabi, Saleha Rehman, Sanjula Baboota, Javed Ali

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Aim: The objective of research undertaken is analytical method validation (HPLC method) of an anti-HIV drug Elvitegravir (EVG). Additionally carrying out the forced degradation studies of the drug under different stress conditions to determine its stability. It is envisaged in order to determine the suitable technique for drug estimation, which would be employed in further research. Furthermore, comparative pharmacokinetic profile of the drug from lipid architectonics and drug suspension would be obtained post oral administration. Method: Lipid Architectonics (LA) of EVR was formulated using probe sonication technique and optimized using QbD (Box-Behnken design). For the estimation of drug during further analysis HPLC method has been validation on the parameters (Linearity, Precision, Accuracy, Robustness) and Limit of Detection (LOD) and Limit of Quantification (LOQ) has been determined. Furthermore, HPLC quantification of forced degradation studies was carried out under different stress conditions (acid induced, base induced, oxidative, photolytic and thermal). For pharmacokinetic (PK) study, Albino Wistar rats were used weighing between 200-250g. Different formulations were given per oral route, and blood was collected at designated time intervals. A plasma concentration profile over time was plotted from which the following parameters were determined:

Keywords: AIDS, Elvitegravir, HPLC, nanostructured lipid carriers, pharmacokinetics

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Authors: Jolanta Pulit-Prociak, Olga Dlugosz, Marcin Banach

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The toxicity of bare zinc oxide nanoparticles used as drug carriers may be the result of releasing zinc ions. Thus, zinc oxide nanoparticles modified with galactose were obtained. The process of their formation was conducted in the microwave field. The physicochemical properties of the obtained products were studied. The size and electrokinetic potential were defined by using dynamic light scattering technique. The crystalline properties were assessed by X-ray diffractometry. In order to confirm the formation of the desired products, Fourier-transform infrared spectroscopy was used. The releasing of zinc ions from the prepared products when comparing to the bare oxide was analyzed. It was found out that modification of zinc oxide nanoparticles with galactose limits the releasing of zinc ions which are responsible for the toxic effect of the whole carrier-drug conjugate.

Keywords: nanomaterials, zinc oxide, drug delivery system, toxicity

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Authors: Cedric Leong, Parth Desai, Parth Patel

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The purpose of this project was to develop a neural network based on qualitative team data to predict alliance scores to determine winners of matches in the FIRST Robotics Competition (FRC). The game for the competition changes every year with different objectives and game objects, however the idea was to create a prediction system which can be reused year by year using some of the statistics that are constant through different games, making our system adaptable to future games as well. Aerial Assist is the FRC game for 2014, and is played in alliances of 3 teams going against one another, namely the Red and Blue alliances. This application takes any 6 teams paired into 2 alliances of 3 teams and generates the prediction for the final score between them.

Keywords: artifical neural network, prediction system, qualitative team data, FIRST Robotics Competition (FRC)

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Authors: Meltem Koray, Arda Ozgon, Duygu Ofluoglu, Mehmet Yaltirik

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Oral ulcerations can be seen as a side effect of different drugs. These ulcers usually appear within a few weeks following drug treatment. In most of cases, these ulcers resist to conventional treatments, such as anesthetics, antiseptics, anti-inflammatory agents, cauterization, topical tetracycline and corticosteroid treatment. The diagnosis is usually difficult, especially in patients receiving multiple drug therapies. Hyaluronan or hyaluronic acid (HA) is a biomaterial that has been introduced as an alternative approach to enhance wound healing and also used for oral ulcer treatment. The aim of this report is to present the treatment of drug-induced oral ulceration on maxillary mucosa with HA gel. 60-year-old male patient was referred to Department of Oral and Maxillofacial Surgery complaining of oral ulcerations during few weeks. He had received chemotherapy and radiotherapy in 2014 with the diagnosis of nasopharyngeal carcinoma, and he has accompanying systemic diseases such as; cardiological, neurological diseases and gout. He is medicated with Escitalopram (Cipralex® 20mg), Quetiapine (Seroquel® 100mg), Mirtazapine (Zestat® 15mg), Acetylsalicylic acid (Coraspin® 100mg), Ramipril-hydrochlorothiazide (Delix® 2.5mg), Theophylline anhydrous (Teokap Sr® 200mg), Colchicine (Colchicum Dispert® 0.5mg), Spironolactone (Aldactone® 100mg), Levothyroxine sodium (Levotiron® 50mg). He had painful oral ulceration on the right side of maxillary mucosa. The diagnosis was 'drug-induced oral ulceration' and HA oral gel (Aftamed® Oral gel) was prescribed 3 times a day for 2 weeks. Complete healing was achieved within 3 weeks without any side effect and discomfort. We suggest that HA oral gel is a potentially useful local drug which can be an alternative for management of drug-induced oral ulcerations.

Keywords: drug-induced, hyaluronic acid, oral ulceration, maxillary mucosa

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Authors: Nagasamy Venkatesh Dhandapani

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This work aims at investigating the use of β-Cyclodextrin as a cross linker, in an attempt to formulate nanosponges containing ketoconazole. The nanosponges were prepared by cross-linking method. The excipients used in this study did not alter the physicochemical properties of a drug as revealed by FTIR spectroscopy. Studies on various formulation variables revealed that all the variables are inter-related with the formulation. The ideal batch among the formulation was selected based on the higher entrapment efficiency and drug loading. The in vitro release studies of ketoconazole nanosponges in hydrogel exhibited a sustained release over a period of 24 hours. Mathematical analysis of drug release from the formulation followed non-Fickian diffusion obeying first order kinetics. The anti-fungal activity of the formulation exhibited better zone of inhibition when compared to pure drug (ketoconazole) against Tinea corporis.

Keywords: nanosponges, beta-cyclodextrin, ketoconazole, tinea corporis

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Authors: Venkatalakshmi Ranganathan, Ong Hsin Ju, Tan Yinn Ming, Lim Kien Sin, Wong Man Ting, Venkata Srikanth Meka

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The mucoadhesive buccal tablet is an oral drug delivery system which attached to the buccal surface for direct drug absorption into the systemic circulation and the unidirectional drug release is ensured by formulating a hydrophobic backing layer. The objective of present study was to formulate mucoadhesive atenolol bilayer buccal tablets by using sodium alginate, hydroxyethyl cellulose, and xanthan gum as mucoadhesive polymer and the technique applied was direct compression method. Ethyl cellulose was used as backing layer of the tablet. FTIR and DSC analysis were carried out to identify the drug polymer interactions. The prepared tablets were evaluated for physicochemical parameters, ex vivo mucoadhesion time and in-vitro drug release. The formulated tablets showed the average surface pH 6-7 which is favourable for oral mucosa. The formulation containing sodium alginate showed more than 90 % of drug release at the end of the 7 hours in vitro dissolution studies. The formulation containing xanthan gum showed more than 8 hours of mucoadhesion time and all formulation exhibited non fickian release kinetics. The present study indicates enormous potential of erodible mucoadhesive buccal tablet containing atenolol for systemic delivery with an added advantage of circumventing the hepatic first pass metabolism.

Keywords: atenolol, mucoadhesion, in vitro drug release, direct compression, ethyl cellulose

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Authors: Surendra Agrawal, Pravina Gurjar, Supriya Bhide, Ram Gaud

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Levamisole hydrochloride is a prominent anticancer drug in the treatment of colon cancer but resulted in toxic effects due poor bioavailability and poor cellular uptake by tumor cells. Levamisole is an unstable drug. Incorporation of this molecule in solid lipids may minimize their exposure to the aqueous environment and partly immobilize the drug molecules within the lipid matrix-both of which may protect the encapsulated drugs against degradation. The objectives of the study were to enhance bioavailability by sustaining drug release and to reduce the toxicities associated with the therapy. Solubility of the drug was determined in different lipids to select the components of Solid Lipid Nanoparticles (SLN). Pseudoternary phase diagrams were created using aqueous titration method. Formulations were subjected to particle size and stability evaluation to select the final test formulations which were characterized for average particle size, zeta potential, and in-vitro drug release and percentage transmittance to optimize the final formulation. SLN of Levamisole hydrochloride was prepared by Nanoprecipitation method. Glyceryl behenate (Compritol 888 ATO) was used as core comprising of Tween 80 as surfactant and Lecithin as co-surfactant in (1:1) ratio. Entrapment efficiency (EE) was found to be 45.89%. Particle size was found in the range of 100-600 nm. Zeta potential of the formulation was -17.0 mV revealing the stability of the product. In-vitro release study showed that 66 % drug released in 24 hours in pH 7.2 which represent that formulation can give controlled action at the intestinal environment. In pH 5.0 it showed 64% release indicating that it can even release drug in acidic environment of tumor cells. In conclusion, results revealed SLN to be a promising approach to sustain the drug release so as to increase bioavailability and cellular uptake of the drug with reduction in toxic effects as dose has been reduced with controlled delivery.

Keywords: SLN, nanoparticulate delivery of levamisole, pharmacy, pharmaceutical sciences

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Authors: Zohreh Bayat, Dariush Minai-Tehrani

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Pseudomonas aeruginosa is a Gram-negative, rode shape and aerobic bacterium that has shown to be resistance to many antibiotics. This resistance makes the bacterium very harmful in some diseases. It can also generate diseases in any part of the gastrointestinal tract from oropharynx to rectum. P. aeruginosa has become an important cause of infection, especially in patients with compromised host defense mechanisms. One of the most important reasons that make P. aeruginosa an emerging opportunistic pathogen in patients is its ability to use various compounds as carbon sources. Lipase is an enzyme that catalyzes the hydrolysis of lipids. Most lipases act at a specific position on the glycerol backbone of lipid substrate. Some lipases are expressed and secreted by pathogenic organisms during the infection. Muscarinic antagonist used as an antispasmodic and in urinary incontinence. The drug has little effect on glandular secretion or the cardiovascular system. It does have some local anesthetic properties and is used in gastrointestinal, biliary, and urinary tract spasms. Aim: In this study the inhibitory effect of a muscarinic antagonist on lipase of P. aeruginosa was investigated. Methods: P. aeruginosa was cultured in minimal salt medium with 1% olive oil as carbon source. The cells were harvested and the supernatant, which contained lipase, was used for enzyme assay. Results: Our results showed that the drug can inhibit P. aeruginosa lipase by competitive manner. In the presence of different concentrations of the drug, the Vmax (2 mmol/min/mg protein) of enzyme did not change, while the Km raised by increasing the drug concentration. The Ki (inhibition constant) and IC50 (the half maximal inhibitory concentration) value of drug was estimated to be about 30 uM and 60 uM which determined that the drug binds to enzyme with high affinity. Maximum activity of the enzyme was observed at pH 8 in the absence and presence of muscarinic antagonist, respectively. The maximum activity of lipase was observed at 600C and the enzyme became inactive at 900C. Conclusion: The muscarinic antagonist drug could inhibit lipase of P. aeruginosa and changed the kinetic parameters of the enzyme. The drug binded to enzyme with high affinity and did not chang the optimum pH of the enzyme. Temperature did not affect the binding of drug to musmuscarinic antagonist.

Keywords: Pseudomonas aeruginosa, drug, enzyme, inhibition

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Farzad Khajavi, Farzaneh Jalilfar, Faranak Jafari, Leila Shokrani

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Formulation of gliclazide in the form of extended-release tablet in 30 and 60 mg dosage forms was performed using hypromellose (HPMC K4M) as a retarding agent. Drug-release profiles were investigated in comparison with references Diamicron MR 30 and 60 mg tablets. The effect of size of powder particles, the amount of hypromellose in formulation, hardness of tablets, and also the effect of halving the tablets were investigated on drug release profile. A mathematical model which describes hypromellose behavior in initial times of drug release was proposed for the estimation of hypromellose content in modified-release gliclazide 60 mg tablet. This model is based on erosion of hypromellose in dissolution media. The model is applicable to describe release profiles of insoluble drugs. Therefore, by using dissolved amount of drug in initial times of dissolution and the model, the amount of hypromellose in formulation can be predictable. The model was used to predict the HPMC K4M content in modified-release gliclazide 30 mg and extended-release quetiapine 200 mg tablets.

Keywords: Gliclazide, hypromellose, drug release, modified-release tablet, mathematical model

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Authors: Ajayi Olusola Olajide, Alonge Olaide Moses

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Predicting the outcome of soccer matches poses an interesting challenge for which it is realistically impossible to successfully do so for every match. Despite this, there are lots of resources that are being expended on the correct prediction of soccer matches weekly, and all over the world. Soccer Match Result Prediction System Model (SMRPSM) is a system that is proposed whereby the results of matches between two soccer teams are auto-generated, with the added excitement of giving users a chance to test their predictive abilities. Soccer teams from different league football are loaded by the application, with each team’s corresponding manager and other information like team location, team logo and nickname. The user is also allowed to interact with the system by selecting the match to be predicted and viewing of the results of completed matches after registering/logging in.

Keywords: predicting, soccer match, outcome, soccer, matches, result prediction, system, model

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Authors: Ian Walmsley

Abstract:

The aim of this paper is to explore the influence of time and temporality on the experience of coming off heroin in prison. The presentation draws on qualitative data collected during a small-scale pilot study of the role of self-care in the process of coming off drugs in prison. Time and temporality emerged as a key theme in the interview transcripts. Drug dependent prisoners experience of time in prison has not been recognized in the research literature. Instead, the literature on prison time typically views prisoners as a homogenous group or tends to focus on the influence of aging and gender on prison time. Furthermore, there is a tendency in the literature on prison drug treatment and recovery to conceptualize drug dependent prisoners as passive recipients of prison healthcare, rather than active agents. In building on these gaps, this paper argues that drug dependent prisoners experience multiple temporalities which involve an interaction between the body-times of the drug dependent prisoner and the economy of time in prison. One consequence of this interaction is the feeling that they are doing, at this point in their prison sentence, double prison time. The second part of the argument is that time and temporality were a means through which they governed their withdrawing bodies. In addition, this paper will comment on the challenges of prison research in England.

Keywords: heroin withdrawal, time and temporality, prison, body

Procedia PDF Downloads 253

Authors: C. Manjula, Lilly Florence

Abstract:

Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Marcelus U. Ajonina, Deodata B. Ngonga, Kenric B. Ware, Carine K. Nfor

Abstract:

Background: Lack of knowledge of rational use of antimalarial drugs among dispensers is a serious problem, especially in areas of intense transmission, thus increasing the risk of resistance and adverse drug reactions. This study was aimed at assessing the knowledge of malaria as well as perception and dispensing practices of antimalarials among vendors in Buea community. Methods: A community-based cross-sectional survey of a random sample of 140 drug vendors living within the Buea community was conducted between March and June 2017. A questionnaire was designed to obtain information from drug vendors on the general knowledge of malaria as well as dispensing practices. Data were analyzed using SPSS Statistics 20.0 and were considered significant at p ≤ 0.05. Results: Knowledge of malaria symptoms, transmission, and prevention was reasonable among 55.8% (77) of the respondents. Only 33.6% (47) of the respondents could attribute the cause of malaria to protozoan of genus Plasmodium species. Of the 140 vendors, 115 (82.7%) prescribe antimalarial drugs. The knowledge of the national protocol was malaria case management among dispensers was 35.0%. Vendors in hospital/community pharmacies were 2.4 times (OR = 3.14, 95% CI: 4.14 - 8.74, p < 0.001) more knowledgeable about malaria treatment protocol than those of in drugstores. The prevalence of self-prescription of antimalarials was 39.3%. Self-prescription was significantly higher in drugstores than hospital/community pharmacies (p=0.004). In all, 56 (40.6%) of vendors showed good practices regarding antimalarial drug dispensing with the majority (51.7%) from community pharmacies (OR=2.27,95% CI: 1.13-4.56). Conclusion: Findings reveal moderate knowledge of malaria but poor prescription and dispensing practices of antimalarial drugs among vendors, thus indicating a need for routine monitoring and evaluation to prevent the emergence of resistant strains to current efficacious antimalarials.

Keywords: antimalarials, drug retail outlets, dispensing, drug resistance, prescription

Procedia PDF Downloads 102