<b>Influence of technological variables on release of drugs from hydrophilic matrices</b>

Vázquez, M. J.; Pérez-Marcos, B.; Gómez-Amoza, J.L.; Pacheco, R. iAnez; Souto, C.; Concheiro, Angel

doi:10.3109/03639049209046332

Cited by 119 publications

(47 citation statements)

References 48 publications

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“…Rate of drug release (until 8 hrs) tended to decrease with increase in the content of either HPMC or PVP K 30. This is in agreement with literatureˆndings 27,28) that the viscosity of the gel layer around the tablet increases with increase in the hydrogel concentration, thus limiting the release of active ingredient. The gel formed during the penetration of dissolution media into the matrix structure, consists of closely packed swollen particles.…”

Section: Drug Content and Physical Evaluationsupporting

confidence: 82%

Formulation and Optimization of Sustained Release Matrix Tablet of Metformin HCl 500 mg Using Response Surface Methodology

et al. 2007

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The aim of the current study was to design an oral sustained release matrix tablet of metformin HCl and to optimize the drug release proˆle using response surface methodology. Tablets were prepared by non-aqueous wet granulation method using HPMC K 15M as matrix forming polymer. A central composite design for 2 factors at 3 levels each was employed to systematically optimize drug release proˆle. HPMC K 15M (X 1 ) and PVP K 30 (X 2 ) were taken as the independent variables. The dependent variables selected were ％ of drug released in 1 hr (rel 1 hr ), ％ of drug released in 8 hrs (rel 8 hrs ) and time to 50％ drug release (t 50％ ). Contour plots were drawn, and optimum formulations were selected by feasibility and grid searches. The formulated tablets followed Higuchi drug release kinetics and diŠusion was the dominant mechanism of drug release, resulting in regulated and complete release within 8 hrs. The polymer (HPMC K 15M) and binder (PVP K 30) had signiˆcant eŠect on the drug release from the tablets ( p＜0.05). Polynomial mathematical models, generated for various response variables using multiple linear regression analysis, were found to be statistically signiˆcant ( p＜0.05). Validation of optimization study, performed using 8 conˆrmatory runs, indicated very high degree of prognostic ability of response surface methodology, with mean percentage error (±S.D.) 0.0437± 0.3285. Besides unraveling the eŠect of the 2 factors on the in vitro drug release, the study helped inˆnding the optimum formulation with sustained drug release.

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Section: Drug Content and Physical Evaluationsupporting

confidence: 82%

Formulation and Optimization of Sustained Release Matrix Tablet of Metformin HCl 500 mg Using Response Surface Methodology

et al. 2007

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“…Rate of drug release (until 8 h) tended to decrease with increase in the content of either HPMC or PVP K30. This is in agreement with literature findings 39,40) that the viscosity of the gel layer around the tablet increases with increase in the hydrogel concentration, thus limiting the release of active ingredient. The gel formed during the penetration of dissolution media into the matrix structure, consists of closely packed swollen particles.…”

Section: Resultssupporting

confidence: 83%

Optimization of Metformin HCl 500 mg Sustained Release Matrix Tablets Using Artificial Neural Network (ANN) Based on Multilayer Perceptrons (MLP) Model

et al. 2008

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The aim of the present study was to apply the simultaneous optimization method incorporating Artificial Neural Network (ANN) using Multi-layer Perceptron (MLP) model to the development of a metformin HCl 500 mg sustained release matrix tablets with an optimized in vitro release profile. The amounts of HPMC K15M and PVP K30 at three levels (؊1, 0, ؉1) for each were selected as casual factors. In vitro dissolution time profiles at four different sampling times (1 h, 2 h, 4 h and 8 h) were chosen as output variables. 13 kinds of metformin matrix tablets were prepared according to a 2 3 factorial design (central composite) with five extra center points, and their dissolution tests were performed. Commercially available STATISTICA Neural Network software (Stat Soft, Inc., Tulsa, OK, U.S.A.) was used throughout the study. The training process of MLP was completed until a satisfactory value of root square mean (RSM) for the test data was obtained using feed forward back propagation method. The root mean square value for the trained network was 0.000097, which indicated that the optimal MLP model was reached. The optimal tablet formulation based on some predetermined release criteria predicted by MLP was 336 mg of HPMC K15M and 130 mg of PVP K30. Calculated difference ( f 1 2.19) and similarity ( f 2 89.79) factors indicated that there was no difference between predicted and experimentally observed drug release profiles for the optimal formulation. This work illustrates the potential for an artificial neural network with MLP, to assist in development of sustained release dosage forms.Key words artificial neural network; multilayer perceptron; metformin HCl; sustained release; matrix tablet Chem. Pharm. Bull. 56(2) 150-155 (2008)

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“…19,20 Polymer dissolution plays an important role in regulating the drug release in the case of lower viscosity grades of HPMC and for relatively water-insoluble drugs. 21 Several kinetic models have been proposed to describe the release characteristics of a drug from a CR polymer matrix. The following 3 equations are commonly used, because of their simplicity and applicability 22,23 : Equation 1, the zero-order model equation; Equation 2, Higuchi's square-root equation; and Equation 3, the Ritger-Peppas empirical equation.…”

Section: Introductionmentioning

confidence: 99%

Design and study of lamivudine oral controlled release tablets

2007

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The objective of this study was to design oral controlled release matrix tablets of lamivudine using hydroxypropyl methylcellulose (HPMC) as the retardant polymer and to study the effect of various formulation factors such as polymer proportion, polymer viscosity, and compression force on the in vitro release of drug. In vitro release studies were performed using US Pharmacopeia type 1 apparatus (basket method) in 900 mL of pH 6.8 phosphate buffer at 100 rpm. The release kinetics were analyzed using the zero-order model equation, Higuchi's square-root equation, and the RitgerPeppas empirical equation. Compatibility of the drug with various excipients was studied. In vitro release studies revealed that the release rate decreased with increase in polymer proportion and viscosity grade. Increase in compression force was found to decrease the rate of drug release. Matrix tablets containing 60% HPMC 4000 cps were found to show good initial release (26% in first hour) and extended the release up to 16 hours. Matrix tablets containing 80% HPMC 4000 cps and 60% HPMC 15 000 cps showed a first-hour release of 22% but extended the release up to 20 hours. Mathematical analysis of the release kinetics indicated that the nature of drug release from the matrix tablets was dependent on drug diffusion and polymer relaxation and therefore followed non-Fickian or anomalous release. No incompatibility was observed between the drug and excipients used in the formulation of matrix tablets. The developed controlled release matrix tablets of lamivudine, with good initial release (20%-25% in first hour) and extension of release up to 16 to 20 hours, can overcome the disadvantages of conventional tablets of lamivudine.

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Influence of technological variables on release of drugs from hydrophilic matrices

Cited by 119 publications

References 48 publications

Formulation and Optimization of Sustained Release Matrix Tablet of Metformin HCl 500 mg Using Response Surface Methodology

Formulation and Optimization of Sustained Release Matrix Tablet of Metformin HCl 500 mg Using Response Surface Methodology

Optimization of Metformin HCl 500 mg Sustained Release Matrix Tablets Using Artificial Neural Network (ANN) Based on Multilayer Perceptrons (MLP) Model

Design and study of lamivudine oral controlled release tablets

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