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      Mini-Tablets versus Nanoparticles for Controlling the Release of Amoxicillin: In vitro/In vivo Study

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          Controlling the drug release from the dosage form at a definite rate is the main challenge for a successful oral controlled-release drug delivery system. In this study, mini-tablets (MTs) and lipid/polymer nanoparticles (LPNs) of lipid polymer and chitosan in different ratios were designed to encapsulate and control the release time of Amoxicillin (AMX).


          Physical characteristics and in vitro release profiles of both MT and LPN formulations were studied. Antimicrobial activity and oral pharmacokinetics of the optimum MT and LPN formulations in comparison to market tablet were studied in rats.


          All designed formulations of AMX as MTs and LPNs showed accepted characteristics. MT-6 (Compritol/Chitosan 1:1) showed the greatest retardation among all prepared minitablet preparations, releasing about 79.5% of AMX over 8 h. In contrast, LPN-11 (AMX: Cr 1:3/Chitosan 1 mg/mL) had the slowest drug release, revealing the sustained release of 80.9% within 8 h. The MIC of both optimized tablet formula (MT-6) and LPNs formula (LPN-11) was around two-fold lower than the control against H. pylori. The C max of MT-6 and LPN11 were non significantly different compared with the marketed AMX product. While the bioavailability experiment proved that the relative bioavailability of the AMX was 1.85 and 1.8 after the oral use of LPN11 and MT-6, respectively, compared to the market tablet.


          The results verified that both controlled-release mini-tablets and lipid/polymer nanoparticles can be used for sustaining the release and hence improve the bioavailability of amoxicillin.

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          Most cited references 57

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          DDSolver: an add-in program for modeling and comparison of drug dissolution profiles.

          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.
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            Modeling and comparison of dissolution profiles.

            Over recent years, drug release/dissolution from solid pharmaceutical dosage forms has been the subject of intense and profitable scientific developments. Whenever a new solid dosage form is developed or produced, it is necessary to ensure that drug dissolution occurs in an appropriate manner. The pharmaceutical industry and the registration authorities do focus, nowadays, on drug dissolution studies. The quantitative analysis of the values obtained in dissolution/release tests is easier when mathematical formulas that express the dissolution results as a function of some of the dosage forms characteristics are used. In some cases, these mathematic models are derived from the theoretical analysis of the occurring process. In most of the cases the theoretical concept does not exist and some empirical equations have proved to be more appropriate. 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). Some analytical definitions of the Q(t) function are commonly used, such as zero order, first order, Hixson-Crowell, Weibull, Higuchi, Baker-Lonsdale, Korsmeyer-Peppas and Hopfenberg models. Other release parameters, such as dissolution time (tx%), assay time (tx min), dissolution efficacy (ED), difference factor (f1), similarity factor (f2) and Rescigno index (xi1 and xi2) can be used to characterize drug dissolution/release profiles.
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              Degradable Controlled-Release Polymers and Polymeric Nanoparticles: Mechanisms of Controlling Drug Release.


                Author and article information

                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                07 December 2020
                : 14
                : 5405-5418
                [1 ]Department of Pharmaceutics, College of Pharmacy, Qassim University , Buraidah, kingdom of saudi arabia
                [2 ]Department of Quality Control & Quality Assurance, Holding Company for Biological Products and Vaccines , Cairo, Egypt
                [3 ]College of Pharmacy, Qassim University , Buraidah, kingdom of saudi arabia
                [4 ]National Medicine Quality Control Laboratory, National Medicine and Poisons Board , Sudan
                [5 ]King Faisal Specialist Hospital and Research Center , Riyadh, kingdom of saudi arabia
                Author notes
                Correspondence: Dalia A Gaber Department of Pharmaceutics, College of pharmacy, Qassim university , Buridah, Saudi arabiaTel +20 1001523222 Email dr_daliaahmed@hotmail.com
                © 2020 Gaber et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 8, Tables: 9, References: 57, Pages: 14
                Original Research


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