Dissolution Profiles Of Tablets Research Articles

Curcumin- β-Cyclodextrin Molecular Inclusion Complex: A Water-Soluble Complex in Fast-dissolving Tablets for the Treatment ofNeurodegenerative Disorders.

Orally disintegrating tablets (ODTs) have become an excellent choice for delivering drugs as their palatability is greatly improved. In this work, β-cyclodextrin has been used to improve the solubility of curcumin by encapsulating it into the hydrophobic cavity for the treatment of neurodegenerative disorders. The current study aimed to present the design, formulation, and optimisation of fastdissolving oral tablets of curcumin- β-cyclodextrin molecular inclusion complex using a 32-factorial design. The drug-excipient compatibility was studied by FTIR spectroscopy. The inclusion complex of curcumin-β-cyclodextrin was prepared using solvent casting and confirmed using XRD studies. Powder blends were evaluated for flow properties. Tablets prepared by direct compression were evaluated for post-compression parameters. Further, the effect of formulation variables, such as sodium starch glycolate (X1) and Neusilin® ULF2 (X2), on various responses, including disintegration time and dissolution at 2 hours, was studied using statistical models. Post-compression parameters, i.e., hardness (4.4-5 kg/cm2), thickness (3.82-3.93 mm), weight variation (±7.5%), friability (< 1%), wetting time (51-85 seconds) and drug content (96.28- 99.32%) were all found to be within the permissible limits and the disintegration time of tablets with super-disintegrants ranged between 45-58 seconds. The in-vitro dissolution profile of tablets showed that higher SSG and Neuslin® ULF2 levels promoted drug release. For statistical analysis, the 2FI model was chosen. Optimised variables for formulation have been determined and validated with the experimental findings based on the significant desirability factor. The current study reveals the validated curcumin-β-cyclodextrin inclusion complex fastdissolving tablets with SSG and Neusilin® ULF2 to be an ideal choice for effectively treating neurodegenerative disorders.

İZOSORBİD DİNİTRATIN MODİFİYE SALIM YAPAN ÇOK BİRİMLİ BİLEŞİMİNİN TABLET ŞEKLİNDE BASILMASI VE DEĞERLENDİRİLMESİ

Objective: This study was aimed to create a multiple-unit dosage form of isosorbide dinitrate by pressing spherical matrix granules into tablets, selecting the optimal technology parameters and evaluating the obtained tablets. Material and Method: The tablet cores were prepared from mixtures of active matrix granules and shock-absorbing auxiliary granules in various ratios using diverse tabletting forces. The dissolution profiles of the obtained tablet compositions were evaluated in comparison with the reference preparation. Result and Discussion: An optimal ratio of spheroids with the active component with auxiliary granules along with optimal compression parameters were determined. The resulting as multiple-unit tablets exhibited a release profile similar to that of Cardicket Retard. Used technological approach makes it possible to regulate the dissolution profile of tablets by changing the ratio of active granules with different kinetics of the active substance release.

Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks.

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.

Impact of Raman mapping area and intra-tablet homogeneity on the accuracy of sustained-release tablet dissolution prediction

This exploratory study investigated the minimum required Raman mapping area for predicting sustained-release tablet dissolution profiles based on intra-tablet homogeneity. The aim was to minimize scanning time while achieving reliable dissolution profile predictions. To construct the sample set, we controlled the blending time to introduce variability in the homogeneity of the tablets. The dissolution prediction models were established using the partial least squares regression under different Raman mapping area. The accuracies of the prediction results were evaluated according to the difference factor f1 and Intersection–Union two one-sided t-tests (IU TOST) methods, and the implications conveyed by the results were discussed. The results showed that the homogeneity of sustained-release tablet affects the minimum required mapping area, and the tablets with higher homogeneity show higher prediction accuracy when using the same mapping area to model the dissolution profiles of tablets.

Development of a Discriminative Dissolution Method, Using In-Silico Tool for Hydrochlorothiazide and Valsartan Tablets.

Hydrochlorothiazide (HTZ) and Valsartan (VAL) are poorly soluble drugs in BCS classes IV and II. This study aimed to develop a method to assess the dissolution profile of tablets containing HTZ (12.5 mg) and VAL (160 mg) as a fixed-dose combination, using in silico tools to evaluate products marketed in Brazil and Peru. Firstly, in vitro dissolution tests were performed using a fractional factorial design 33-1. Then, DDDPlus™ was used to carry out experimental design assays of a complete factorial design 33. Data from the first stage were used to obtain calibration constants for in silico simulations. The factors used in both designs were formulation, sinker use, and rotation speed. Finally, effects and factor interaction assessment was evaluated based on a statistical analysis of the dissolution efficiency (DE) obtained from simulations. Thus, the established final conditions of the dissolution method were 900 mL of phosphate buffer pH 6.8, 75 rpm of rotation speed, and sinker use to prevent formulation floating. The reference product stood out because of its higher DE than other formulations. It was concluded that the proposed method, in addition to ensuring total HTZ and VAL release from formulations, has adequate discriminative power.

Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles

In this work, the capabilities of a state-of-the-art fast Raman imaging apparatus are exploited to gain information about the concentration and particle size of hydroxypropyl methylcellulose (HPMC) in sustained release tablets. The extracted information is utilized to predict the in vitro dissolution profile of the tablets. For the first time, convolutional neural networks (CNNs) are used for the processing of the chemical images of HPMC distribution and to directly predict the dissolution profile based on the image. This new method is compared to wavelet analysis, which gives a quantification of the texture of HPMC distribution, carrying information regarding both concentration and particle size. A total of 112 training and 32 validation tablets were used, when a CNN was used to characterize the particle size of HPMC, the dissolution profile of the validation tablets was predicted with an average f2 similarity value of 62.95. Direct prediction based on the image had an f2 value of 54.2, this demonstrates that the CNN is capable of recognizing the patterns in the data on its own. The presented methods can facilitate a better understanding of the manufacturing processes, as detailed information becomes available with fast measurements.

Formulation design and optimization of sustained release tablet dosage form of Diacerein

Diacerein is both an anti-inflammatory drug and an anti-arthritic agent. At present, no sustained release dosage form of Diacerein is commercially available. The aim of the study was to develop an optimized formulation of sustained release tablet dosage form of Diacerein that will be highly patient compliant. A three-level full factorial design was employed to develop nine different formulations of matrix tablets using a combination of Methocel K100M CR and Methocel K4M CR polymer at different ratios. The physical evaluation of both the drug-excipient powder mixtures and tablets of the nine formulations were performed and results were found to be within acceptable ranges for all tests. Dissolution profiles of tablets were obtained and the kinetics of drug release from the matrix tablets were determined by employing various mathematical models. The release data were simulated in Design Expert Software to carry out statistical analysis and the effect of both polymers on release patterns were observed after 1, 4 and 8 h in terms of contour plots and 3D surface plots, which were found to be statistically significant (p < 0.05). Finally, the overlay plot was obtained from which the optimized formulation of Diacerein was determined.

A Simple One-Parameter Percent Dissolved Versus Time Dissolution Equation that Accommodates Sink and Non-sink Conditions via Drug Solubility and Dissolution Volume

In vitro dissolution generally involves sink conditions, so dissolution equations generally do not need to accommodate non-sink conditions. Greater use of biorelevant media, which are typically less able to provide sink conditions than pharmaceutical surfactants, necessitates equations that accommodate non-sink conditions. One objective was to derive an integrated, one-parameter dissolution equation for percent dissolved versus time that accommodates non-sink effects via drug solubility and dissolution volume parameters, including incomplete solubility. A second objective was to characterize the novel equation by fitting it to biorelevant dissolution profiles of tablets of two poorly water-soluble drugs, as well as by conducting simulations of the effect of dose on dissolution profile. The Polli dissolution equation was derived, % ;dissolved=100%left[1-frac{left({{M}_{0}-c}_{s}Vright)}{{M}_{0}-{{c}_{s}Ve}^{{-k}_{d}left(frac{{{M}_{0}-c}_{s}V}{V}right)t}}right], where M0 is the drug dose (mg), cs is drug solubility (mg/ml), V is dissolution volume (ml), and kd is dissolution rate coefficient (ml/mg per min). Maximum allowable percent dissolved was determined by drug solubility and not a fitted extent of dissolution parameter. The equation fit tablet profiles in the presence and absence of sink conditions, using a single fitted parameter, kd, and where solubility ranged over a 1000-fold range. kd was generally smaller when cs was larger. FeSSGF provided relatively small kd values, reflecting FeSSGF colloids are large and slowly diffusing. Simulations showed impact of non-sink conditions, as well as plausible kd values for various cs scenarios, in agreement with observed kd values. The equation has advantages over first-order and z-factor dissolution rate equations. An Excel file for regression is provided.Graphical

The effect of partially pregelatinized cassava starch as disintegrant for paracetamol tablet

The use of partially pregelatinized starch in tablet formulations is entirely various; one of them is disintegrant. Present pregelatinized starch is imported from another country, which is relatively expensive. In contrast, many plants can be used as starch sources, including cassava which is relatively abundant in Indonesia. This study aimed to determine the effect of using partially pregelatinized starch from cassava as a disintegrant in paracetamol tablets. In this study, seven formulas were used with different disintegrants, three formulas using partially pregelatinized starch from cassava with concentrations of F1 5%, F2 10%, and F3 15%, three formulas using Starch 1500 with the same concentration as partially pregelatinized starch from cassava and one control formula without disintegrant. The tablet was made using the wet granulation method. The tablets produced were tested for physical properties (hardness, disintegration, and dissolution). In addition, compact ability of partially pregelatinized starch from cassava was compared with Avicel, Starch 1500, and cassava starch. Based on the results of the study showed that partially pregelatinized starch from cassava produced tablets that tended to be capping with less hardness than tablets with Starch 1500 and control tablets. The compact ability test results showed that the compact ability of partially pregelatinized starch from cassava was better than Starch 1500 and cassava starch. The disintegration test results showed that tablets with partially pregelatinized starch from cassava had faster disintegration than tablets with Starch 1500 and control tablets. The dissolution profile of tablets with partially pregelatinized starch from cassava is also better than other formulas.

Production, physicochemical investigations, antioxidant effect, and cellular uptake in Caco-2 cells of the supersaturable astaxanthin self-microemulsifying tablets

The purpose of this study was to develop astaxanthin (AST)-loaded self-microemulsifying drug delivery system (SMEDDS) tablets and evaluate their physicochemical and biological properties. The optimized liquid (L)-AST SMEDDS formulation was composed of rice bran oil (33.67%), Kolliphor® RH 40 (34.70%), and Span® 20 (31.63%). Two types of hydrophilic polymers (hydroxypropyl methylcellulose, HPMC, and polyvinyl alcohol, PVA) solutions were selected as a precipitation inhibitor for AST and incorporated into L-AST SMEDDS to obtain supersaturation and enhance dissolution of AST. The formulation was then mixed with microcrystalline cellulose and subsequently transformed to solid S-AST SMEDDS particles using a spray dryer prior to direct compression into tablets. The HPMC AST SMEDDS tablet and PVA AST SMEDDS tablet were characterized for their physicochemical properties, dissolution, AST release, and stabilities. Moreover, the cellular uptake and antioxidant effect of AST SMEDDS tablets were evaluated in Caco-2 cells. With good tablet characters, both HPMC AST SMEDDS tablet and PVA AST SMEDDS tablet dissolution profiles were improved compared to that of raw AST. While initially less than 50% of AST released from HPMC AST SMEDDS tablet and PVA AST SMEDDS tablet in pH 1.2 medium, after 6 h more than 98% of AST releases in pH 6.8 were achieved which was similar to L-AST SMEDDS profile. Cellular antioxidant activities of L-AST SMEDDS and HPMC AST SMEDDS tablet & PVA AST SMEDDS tablet were significantly greater than pure AST powder. HPMC AST SMEDDS tablet showed better uptake and deeper penetration through Caco-2 cells than that in PVA AST SMEDDS tablet and pure powder. Our successfully developed AST SMEDDS tablets were demonstrated to be a potential platform to deliver highly lipophilic AST and improve permeation and bioavailability.

Self‐supervised cross validation using data generation structure

AbstractModern statistics and machine learning typically involve large amounts of data coupled with computationally intensive methods. In a predictive modeling context, one seeks models that achieve high predictive accuracy on new datasets. This is typically implemented by partitioning the data into training and hold‐out data sets. The allocation is often conducted randomly, at the row level of the data matrix. In this work, we discuss an overlooked gap in machine learning and predictive modeling, the role of data structure and data generation process in the partitioning of observational data into training and hold‐out datasets. Ignoring such structures can lead to deficiencies in model generalizability and operationalization. We highlight that explicitly embracing the data generation structure to partition the data for validating predictive model is essential to the success of data science projects. The proposed approach is called befitting cross validation (BCV). It relies on an information quality perspective of analytics. This requires an assessment with inputs from domain experts, in contrast to automated approaches that are purely data driven. BCV is motivated by the objective of generating information quality with data and modeling. Two case studies are illustrating the proposed approach. One is based on a 96‐h burn‐in process applied to electro‐mechanical devices, implemented in order to reduce early failures at the customer site. The goal was to shorten the burn‐in process with a predictive model applied at 20 h. The other case study is combining tablet dissolution profiles and designed mixture experiments. The goal there was to match the tablet under test dissolution profiles with a brand tablet reference profile. These case studies demonstrate the methodological points made with BCV, which are generic in nature. We suggest that BCV principles should be always considered in the development of data‐driven predictive models.

Comparative dissolution profiles of two anti-emetic delayed release dosage forms of doxylamine and pyridoxine: Xonvea® tablets vs. Cariban® capsules.

Nausea and vomiting of pregnancy is a common disease that affects many women suffering from mild to severe symptoms. Amongst the different treatments, a fixed dose combination of doxylamine and pyridoxine has been proven safe and effective although the mechanism of action is not well established. There are different pharmaceutical dosage forms in the European market. The objective of this study was to compare the characteristics of a capsule formulation, Cariban® and a tablet formulation, Xonvea® to evaluate the potential impact of their release profiles on their onset of action. 10 mg/10 mg of doxylamine succinate/pyridoxine hydrochloride capsules (Cariban®) and tablets (Xonvea®) were used as reference materials. Appearance, mass, composition, and in vitro dissolution profiles were compared. Bibliographic data from 4 pharmacokinetic studies of Xonvea® and 1 pharmacokinetic study of Cariban® was reviewed. In vitro dissolution studies showed significant differences in dissolution profiles of tablets and capsules. The later exhibiting some release of both drug substances in acid conditions followed by a non-complete release after a total of 3 hours while the tablets demonstrated gastro-resistant properties and rapid API release in about 20-30 minutes after the acid stage. Comparison of PK data showed greater Cmax for pyridoxine. At pH 6.8, complete and faster release of the fixed dose combination for Xonvea® gastro-resistant tablets compared to Cariban® capsules could possibly explain the greater Cmax observed in vivo for the tablet's formulation. This could translate into faster onset of action and relief of nausea for pregnant women taking the tablets vs. the capsules.

Raman mapping-based non-destructive dissolution prediction of sustained-release tablets

In this paper, the applicability of Raman chemical imaging for the non-destructive prediction of the in vitro dissolution profile of sustained-release tablets is demonstrated for the first time. Raman chemical maps contain a plethora of information about the spatial distribution and the particle size of the components, compression force and even polymorphism. With proper data analysis techniques, this can be converted into simple numerical information which can be used as input in a machine learning model. In our work, sustained-release tablets using hydroxypropyl methylcellulose (HPMC) as matrix polymer are prepared, the concentration and particle size of this component varied between samples. Chemical maps of HPMC are converted into histograms with two different methods, an approach based on discretizing concentration values and a wavelet analysis technique. These histograms are then subjected to Principal Component Analysis, the score value of the first two principal components was found to represent HPMC content and particle size. These values are used as input in Artificial Neural Networks which are trained to predict the dissolution profile of the tablets. As a result, accurate predictions were obtained for the test tablets (the average f2 similarity value is higher than 59 with both methods). The presented methodology lays the foundations of the analysis of far more extensive datasets acquired with the emerging fast Raman imaging technology.

Amelioration of physicochemical, pharmaceutical, and pharmacokinetic properties of lornoxicam by cocrystallization with a novel coformer

Objective The present study was aimed to prepare and characterize new cocrystals of lornoxicam (LORX), a BCS class II drug employing 1,3-dimethyl urea (DMU) as a coformer to improve physicochemical, pharmaceutical, and pharmacokinetic performance. Methods A screening study was conducted by employing three techniques viz. neat grinding, liquid-assisted grinding (LAG), and solvent evaporation (SE) using different drug–coformer molar ratios (1:1, 1:2, and 1:3). Samples were characterized by DSC, PXRD, ATR-FTIR, SEM, intrinsic dissolution rate (IDR) studies, compressional studies, and pharmacokinetic studies. In vitro dissolution and stability studies (25 °C/60%RH and 40 °C/75%RH for three months) were carried out for cocrystal tablets. Results LAG and SE were found successful in ratio 1:3 and IDR showed approximately 28- and 19-fold increase, respectively in 0.1 N HCl (pH 1.2) and buffer (pH 7.4) as compared to pure LORX. The cocrystal exhibited good tabletability and was ∼2.5 times that of LORX at 6000 Psi. Dissolution profiles of tablets of cocrystal increased (56% and 100% at pH 1.2 and 7.4, respectively in contrast to those of physical mixture (PhyMix) (∼35% and ∼10%) and pure LORX (∼17% and ∼7%) within 60 min. The Cmax and AUC0–∞ for the selected cocrystal were significantly increased (p < 0.05) which was 2.4 and 2.5 times, respectively, that of LORX in a single dose oral pharmacokinetic study executed in rabbits. Tablets of cocrystal were found stable at both conditions. Conclusion The study indicates that cocrystallization with DMU can concomitantly improve tabletability, dissolution rate, and in vivo performance of dissolution limited drug LORX.

Розробка та валідація ВЕРХ-МС методики визначення мемантину гідрохлориду для вивчення профілів розчинення

A method for quantitative determination of memantine hydrochloride by HPLC with mass spectrometric detection (HPLC-MS), suitable for the study of dissolution profiles of tablets "Mematon IС" was developed. Chromatographic determination was performed using a mobile phase of methanol - 0.1% (v/v) aqueous solution of formic acid (55:45) on a column of Zorbax Eclipse Plus C18 size 10 cm Ч 4.6 mm (3.5 μm) at a flow rate of 1 ml/min. The linearity interval in the appropriate dissolution media is 35 - 150 % of the normalized content of memantine hydrochloride in the tablet. The method is validated on the parameters of specificity, accuracy, correctness, linearity in the studied range of concentrations, robustness. The stability of the tested solutions and reference solutions in the case of their storage at room temperature for 24 hours was confirmed. It is established that in the case of the study of solutions prepared in a dissolution medium of 0.1 M hydrochloric acid solution pH 1.2, there is a need to preneutralize hydrochloric acid before analysis, because it, as stronger than formic acid, almost completely ionizes all dissolved molecules, which leads to a significant deviation of the linear dependence of the analytical signal on the concentration of the analyte. Neutralization is performed with 0.1 M sodium hydroxide solution, which is added to the sample of the test solution. The release of more than 85 % of memantine hydrochloride in 15 min in all dissolution media indicates the similarity of the dissolution profiles and does not require the calculation of the similarity factor f2.

An Open Microfluidic Chip for Continuous Sampling of Solute from a Turbulent Particle Suspension

AbstractHigh solids content complicates in situ analysis of chemical processing, biological suspensions, and environmental streams. In most cases, analytical methods require at least one pre‐treatment step of a small volume of sample before a particle‐free fluid can be analyzed. We have developed a continuous in situ sampler that can “sip” particle‐free solution from a turbulent high solids content stream (a slurry). An open microfluidic chip with an extended slit opening shields the internal laminar flow from the turbulence outside. Unlike other open chips, our chip does not require close proximity to a solid surface and operates in turbulent environments for hours without maintenance. Two applications are demonstrated: monitoring FeIII in a stirred slurry of mixed ore particles at high solids loading (4 %wt) and paracetamol tablet dissolution profiles for two different formulations.

An Open Microfluidic Chip for Continuous Sampling of Solute from a Turbulent Particle Suspension.

High solids content complicates in situ analysis of chemical processing, biological suspensions, and environmental streams. In most cases, analytical methods require at least one pre-treatment step of a small volume of sample before a particle-free fluid can be analyzed. We have developed a continuous in situ sampler that can "sip" particle-free solution from a turbulent high solids content stream (a slurry). An open microfluidic chip with an extended slit opening shields the internal laminar flow from the turbulence outside. Unlike other open chips, our chip does not require close proximity to a solid surface and operates in turbulent environments for hours without maintenance. Two applications are demonstrated: monitoring FeIII in a stirred slurry of mixed ore particles at high solids loading (4 %wt) and paracetamol tablet dissolution profiles for two different formulations.

Analysis of available surface area can predict the long-term dissolution profile of tablets using short-term stability studies.

Generally, since at least 6months are usually needed for accelerated testing of tablet at 40°C/75% relative humidity (RH), it would be crucial important to predict the dissolution profiles during long-term storage period by using samples stored with shorter periods such as 3months. In this study, we developed a new method for predicting changes in dissolution from tablets during long-term storage-based changes in the available surface area [S (t)]. In addition, we discussed the dissolution behavior and mechanisms using S (t). The results revealed drastic delays in dissolution in samples stored at 40°C/75% RH for 7weeks. Considering changes of S (t) patterns, this delay was derived from changes of the tablet surface. New parameters, namely T22.1 and T63.2, calculated from the S (t) profile tended to increase with an increased duration of testing. Concerning the long-term prediction model using short-term data, a nonlinear model was deemed appropriate because good agreement was observed between the value predicted using the model and the measured value for samples stored at 40°C/75% RH for 6months. Therefore, using the new evaluation method based on S (t), we can predict changes in dissolution during long-term storage using short-term methods.

Efficient Validated HPLC/UV Method for Determination of Valsartan and Atenolol in Dosage Form And In Vitro Dissolution Studies

The main purpose of this study was to develop and validate an efficient HPLC/UV method for determination of valsartan and atenolol and to introduce the dissolution profiles of tablets; The resolution of peaks was best achieved with Zorbax C8 (4.6 mm i.d. X 150 mm, 5 μm) column. Samples were chromatographed in a isocratic mode (methanol and 25 mM solution potassium dihydrogen phosphate pH 7.3 (55:45, V/V)), pumped with 1.0 mL/min at 40 °C set temperature of column oven, with UV detector set to 225 nm wavelength; The total chromatographic run time was 6 minutes. The retention time of valsartan is 1.753 min, atenolol – 3.064 min. Linearity was examined and proven at different concentration levels in the range of working concentration of valsartan ( 0.16-0.96 mg/mL) and atenolol (0.2–1.2 mg/mL). The high value of recoveries obtained for valsartan and atenolol indicates that the proposed method was found to be accurate. In all three dissolution media the releases of valsartan and atenolol are more than 85% in 15 min A rapid, simple, accurate, selective, and sensitive method was developed for the determination of valsartan and atenolol in dosage forms. The method was strictly validated according to the ICH guidelines. Acquired results demonstrate that proposed strategy can be effortlessly and advantageously applied for routine quality control of drugs and in vitro dissolution study.

Optimization of Floating Tablet Containing Glibenclamide Using Simplex Lattice Design

Glibenclamide is a second generation sulfonyl ureas drug that are widely used in diabetes type 2 therapy. Glibenclamide in floating tablet formulations is used to improve the bioavailability. The aim of this study was to determine the optimum composition of floating tablets of glibenclamide by simplex lattice design. The tablets were prepared by wet granulation technique, using HPMC K100LV and Carbopol 940 as polimers. The optimum formula was determined based on numeric method with physical properties, floating characters, and dissolution profile of tablets. the results of the study show that glibenclamide floating tablets have good physicochemical properties. The combination of HPMC K100LV and Carbopol 940 decreases floating lag time and dissolution rate of floating glibenclamide tablets. The optimum composition of glibenclamide floating tablet was HPMC K100LV 44.29 mg and Carbopol 940 15.71 mg with desirability value 0.989.