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Journal ArticleDOI

Modeling and comparison of dissolution profiles.

01 May 2001-European Journal of Pharmaceutical Sciences (Elsevier)-Vol. 13, Iss: 2, pp 123-133
TL;DR: Drug dissolution from solid dosage forms has been described by kinetic models in which the dissolved amount of drug (Q) is a function of the test time, t or Q=f(t).
About: This article is published in European Journal of Pharmaceutical Sciences.The article was published on 2001-05-01. It has received 4794 citations till now. The article focuses on the topics: Dissolution testing & Dosage form.
Citations
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Journal ArticleDOI
TL;DR: In each case, the very slow and complete delivery of Ibuprofen was achieved under physiological conditions after 3 weeks with a predictable zero-order kinetics, which highlights the unique properties of flexible hybrid solids for adapting their pore opening to optimize the drug-matrix interactions.
Abstract: Flexible nanoporous chromium or iron terephtalates (BDC) MIL-53(Cr, Fe) or M(OH)[BDC] have been used as matrices for the adsorption and in vitro drug delivery of Ibuprofen (or alpha- p-isobutylphenylpropionic acid). Both MIL-53(Cr) and MIL-53(Fe) solids adsorb around 20 wt % of Ibuprofen (Ibuprofen/dehydrated MIL-53 molar ratio = 0.22(1)), indicating that the amount of inserted drug does not depend on the metal (Cr, Fe) constitutive of the hybrid framework. Structural and spectroscopic characterizations are provided for the solid filled with Ibuprofen. In each case, the very slow and complete delivery of Ibuprofen was achieved under physiological conditions after 3 weeks with a predictable zero-order kinetics, which highlights the unique properties of flexible hybrid solids for adapting their pore opening to optimize the drug-matrix interactions.

1,514 citations

Journal ArticleDOI
TL;DR: The development of a software program, called DDSolver, for facilitating the assessment of similarity between drug dissolution data and to establish a model library for fitting dissolution data using a nonlinear optimization method is described.
Abstract: In recent years, several mathematical models have been developed for analysis of drug dissolution data, and many different mathematical approaches have been proposed to assess the similarity between two drug dissolution profiles. However, until now, no computer program has been reported for simplifying the calculations involved in the modeling and comparison of dissolution profiles. The purposes of this article are: (1) to describe the development of a software program, called DDSolver, for facilitating the assessment of similarity between drug dissolution data; (2) to establish a model library for fitting dissolution data using a nonlinear optimization method; and (3) to provide a brief review of available approaches for comparing drug dissolution profiles. DDSolver is a freely available program which is capable of performing most existing techniques for comparing drug release data, including exploratory data analysis, univariate ANOVA, ratio test procedures, the difference factor f 1, the similarity factor f 2, the Rescigno indices, the 90% confidence interval (CI) of difference method, the multivariate statistical distance method, the model-dependent method, the bootstrap f 2 method, and Chow and Ki’s time series method. Sample runs of the program demonstrated that the results were satisfactory, and DDSolver could be served as a useful tool for dissolution data analysis.

1,045 citations


Cites background from "Modeling and comparison of dissolut..."

  • ...f1 0 1⁄4 Pn t1⁄41 Rt Tt j j= Pn t1⁄41 Rt þ Tt ð Þ=2 100 DD_f1cp (13)...

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  • ...# 326 Quadratic F 1⁄4 100 k1 t2 þ k2 t k1, k2 (8,13)...

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  • ...Parameters for Assessing the Difference Between Dissolution Profiles Abbreviation, description Equation Function in DDSolver Reference(s) f1, difference factora f1 ¼ Pn t¼1 Rt Ttj j= Pn t¼1 Rt 100 DD_f1 (6) f2, similarity factor a f2 ¼ 50 log 1þ 1n Pn t¼1 Rt Ttð Þ2 0:5 100 )( DD_f2 (6) f1’, difference factor modified by Costa P.a f1 0 ¼ Pn t¼1 Rt Ttj j= Pn t¼1 Rt þ Ttð Þ=2 100 DD_f1cp (13) ξ1, first-order Rescigno index a, b xj ¼ R t 0 Ri Tij jjdt = R t 0 Ri þ Tij j j dt h i1=j ; j ¼ 1 DD_res1 (7) ξ2, second-order Rescigno indexa, b xj ¼ R t 0 Ri Tij jjdt = R t 0 Ri þ Tij jjdt h i1=j ; j ¼ 2 DD_res2 (7) Sd, difference in similarity c Sd ¼ Pn 1 t¼1 log AUCRt AUCTt n 1 DD_Sd (53) D, sum of squared mean differencesd D ¼ Pp i¼1 yTi yRið Þ2 DD_D (44,54) D1, mean distance d D1 ¼ Pp i¼1 yTi yRij j=p DD_D1 (55,56) D2, mean squared distance d D2 ¼ Pp i¼1 yTi yRið Þ2=p 1=2 DD_D2 (56) DAUC, difference of area under the profilesd,e DAUC ¼ Pp i¼1 yTi þ yT i 1ð Þ yRi þ yR i 1ð Þ h i ti ti 1ð Þ=2 n o DD_DAUC (56) DABC, area between the profiles d,e DABC ¼ Pp i¼1 yTi yRij j tiþ1 þ tið Þ=2 ti þ ti 1ð Þ=2½ f g DD_DABC (56) a Rt, Tt are the percentage dissolved of the reference and test profile, respectively, at time point t; n is the number of sampling points b j is 1 and 2 for the first- (ξ1) and second-order (ξ2) Rescigno indexes, respectively c n is the number of sampling points; AUCRt and AUCTt are the areas under the dissolution curves of the reference and test formulations, respectively, at time t d p is the number of sampling points; yTi and yRi are the mean dissolution values of the test and reference profiles respectively at the ith time point e ti is the ith sampling time point The MSC provided by MicroMath Corporation (38) is another statistical criterion for model selection which is attracting increasing attention in the field of dissolution data modeling (32,39); it is defined as: ¼ ln Pn i¼1 wi yi obs y obsð Þ2 Pn i¼1 wi yi obs yi pre 2 0 BB@ 1 CCA 2pn where wi is the weighting factor, which is usually equal to 1 for fitting dissolution data, yi_obs is the ith observed y value, yi_pre is the ith predicted y value, y obs is the mean of all observed y-data points, p is the number of parameters in the model, and n is the number of data points....

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  • ...# 301 Zero-order F 1⁄4 k0 t k0 (15) # 302 c Zero-order with Tlag F 1⁄4 k0 t Tlag k0, Tlag (16) # 303 d Zero-order with F0 F 1⁄4 F0 þ k0 t k0, F0 (13) # 304 First-order F 1⁄4 100 1 e k1 t k1 (8)...

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  • ...This work was not performed to assess any particular model or to discuss the statistical or mechanical meaning of each model parameter, because these topics have been well reviewed previously (13,14)....

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Journal ArticleDOI
TL;DR: A review of solid particle technologies available for improving solubility, dissolution, and bioavailability of drugs with poor aqueous solubilities is presented in this article, where the authors highlight the solid particle technology available to improve the bioavailability.

773 citations


Cites background from "Modeling and comparison of dissolut..."

  • ...ble drugs and enhancing their bioavailability is an important challenge to pharmaceutical scientists [5,6]....

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Journal ArticleDOI
TL;DR: The entire drug release kinetics of various published data and experimental data from commercial or prepared controlled release formulations of diltiazem and diclofenac are analyzed using the Weibull function to determine the mechanism of transport of a drug through the polymer matrix.

608 citations

References
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Book
01 Jan 1956
TL;DR: Though it incorporates much new material, this new edition preserves the general character of the book in providing a collection of solutions of the equations of diffusion and describing how these solutions may be obtained.
Abstract: Though it incorporates much new material, this new edition preserves the general character of the book in providing a collection of solutions of the equations of diffusion and describing how these solutions may be obtained

20,495 citations

Book
01 Jan 1985
TL;DR: In this paper, a scaling solution for the Bethe lattice is proposed for cluster numbers and a scaling assumption for cluster number scaling assumptions for cluster radius and fractal dimension is proposed.
Abstract: Preface to the Second Edition Preface to the First Edition Introduction: Forest Fires, Fractal Oil Fields, and Diffusion What is percolation? Forest fires Oil fields and fractals Diffusion in disordered media Coming attractions Further reading Cluster Numbers The truth about percolation Exact solution in one dimension Small clusters and animals in d dimensions Exact solution for the Bethe lattice Towards a scaling solution for cluster numbers Scaling assumptions for cluster numbers Numerical tests Cluster numbers away from Pc Further reading Cluster Structure Is the cluster perimeter a real perimeter? Cluster radius and fractal dimension Another view on scaling The infinite cluster at the threshold Further reading Finite-size Scaling and the Renormalization Group Finite-size scaling Small cell renormalization Scaling revisited Large cell and Monte Carlo renormalization Connection to geometry Further reading Conductivity and Related Properties Conductivity of random resistor networks Internal structure of the infinite cluster Multitude of fractal dimensions on the incipient infinite cluster Multifractals Fractal models Renormalization group for internal cluster structure Continuum percolation, Swiss-cheese models and broad distributions Elastic networks Further reading Walks, Dynamics and Quantum Effects Ants in the labyrinth Probability distributions Fractons and superlocalization Hulls and external accessible perimeters Diffusion fronts Invasion percolation Further reading Application to Thermal Phase Transitions Statistical physics and the Ising model Dilute magnets at low temperatures History of droplet descriptions for fluids Droplet definition for the Ising model in zero field The trouble with Kertesz Applications Dilute magnets at finite temperatures Spin glasses Further reading Summary Numerical Techniques

9,830 citations

Book
01 Jan 1992
TL;DR: In this article, a scaling solution for the Bethe lattice is proposed for cluster numbers and a scaling assumption for cluster number scaling assumptions for cluster radius and fractal dimension is proposed.
Abstract: Preface to the Second Edition Preface to the First Edition Introduction: Forest Fires, Fractal Oil Fields, and Diffusion What is percolation? Forest fires Oil fields and fractals Diffusion in disordered media Coming attractions Further reading Cluster Numbers The truth about percolation Exact solution in one dimension Small clusters and animals in d dimensions Exact solution for the Bethe lattice Towards a scaling solution for cluster numbers Scaling assumptions for cluster numbers Numerical tests Cluster numbers away from Pc Further reading Cluster Structure Is the cluster perimeter a real perimeter? Cluster radius and fractal dimension Another view on scaling The infinite cluster at the threshold Further reading Finite-size Scaling and the Renormalization Group Finite-size scaling Small cell renormalization Scaling revisited Large cell and Monte Carlo renormalization Connection to geometry Further reading Conductivity and Related Properties Conductivity of random resistor networks Internal structure of the infinite cluster Multitude of fractal dimensions on the incipient infinite cluster Multifractals Fractal models Renormalization group for internal cluster structure Continuum percolation, Swiss-cheese models and broad distributions Elastic networks Further reading Walks, Dynamics and Quantum Effects Ants in the labyrinth Probability distributions Fractons and superlocalization Hulls and external accessible perimeters Diffusion fronts Invasion percolation Further reading Application to Thermal Phase Transitions Statistical physics and the Ising model Dilute magnets at low temperatures History of droplet descriptions for fluids Droplet definition for the Ising model in zero field The trouble with Kertesz Applications Dilute magnets at finite temperatures Spin glasses Further reading Summary Numerical Techniques

7,349 citations

Journal ArticleDOI
TL;DR: In this article, the role of dynamic swelling and the dissolution of the polymer matrix on the release mechanism was discussed, as well as the effect of the tracer/excipient ratio on the poly(vinyl alcohol) release profile.

4,397 citations


"Modeling and comparison of dissolut..." refers background in this paper

  • ...(29) can only be used in systems with a drug diffusion Korsmeyer et al. (1983) developed a simple, semi- coefficient fairly concentration independent....

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Journal ArticleDOI
TL;DR: The analyses suggest that for the latter system the time required to release 50% of the drug would normally be expected to be approximately 10 per cent of that required to dissolve the last trace of the solid drug phase in the center of the pellet.

4,383 citations


"Modeling and comparison of dissolut..." refers methods in this paper

  • ...Higuchi model Higuchi (1961, 1963) developed several theoretical contact with a perfect sink release media....

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