Besides the methods mentioned above, DDSolver also allows the user to specify an initial value for each parameter manually. References Publications referenced by this paper. Use of artificial neural networks to predict drug dissolution profiles and evaluation of network performance using similarity factor. However, in cases where linear transformation of the model equation produces multiple line segments, the multiple linear regression method should be used. Interface of the DDSolver program.

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Most of in vitro kinetics of drugs released from nanoparticles under various conditions can be described by the K-P model. Click here to see the associated Ddsolvver record.

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

References Publications referenced by this paper. Skip to ddsklver form Skip to main content. The software is free to all. Ddwolver the past decade, several approaches have been proposed for assessing the similarity between dissolution profiles. When comparing different models, the most appropriate model will be that with the largest MSC.

The comparisons among three different products obtained similarity factors of In brief, the drug release from gelatin nanoparticles was determined in the presence of trypsin named as group 1, whereas in the second case, drug release from gelatin nanoparticles was measured in the absence of trypsin regarded as group 2, as shown Figure 3.

Sustainable release of propranolol hydrochloride tablet using chitin as press-coating material. But Ddsolveer have some two problem with using of it. Toshiaki KoizumiGarnpimol C.

BioMed Research International

The use of statistical moment analysis to elucidate the mechanism of release of a model drug from pellets produced by extrusion and spheronization. Sample runs of the program demonstrated that the results were satisfactory, and DDSolver could be served as a useful tool for dissolution data analysis.

Hopfenberg, Controlled Release Polymeric Formulationsvol. An investigation of the mechanism of release of the amphoteric drug amoxycillin from poly dl -lactide- co -glycolide matrices.

In addition, a detailed disscusion of the approaches for estimating similarity between dissolution profiles was supplied as Supplementary File. All of the other conditions were held constant; it was expected to see different drug release from these nanoparticles because trypsin will cause a forced degradation of the nanoparticles.

Since most of the dissolution equations only have no more than four parameters and do not suffer severely from this problem, it appears to be suited for application in this situation. Use of artificial neural networks to predict drug dissolution profiles and evaluation of network performance using similarity factor.

Performing routine quantitative analysis proved to be much easier using the DDSolver program than an Excel spreadsheet. Microwave-assisted microemulsion technique for production of miconazole nitrate- and econazole nitrate-loaded solid lipid nanoparticles.

When using Excel to calculate the value, the number of time points used in the equation must be carefully accounted for, because can vary among comparison groups and may not equal the number of time points collected during the experiment.

A simple equation for the description of solute release III. This is an open access article distributed ddxolver the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Comets E, Mentre F. For group 2, in the absence of trypsin, polymer swelling ddsolved play an important role in the control of drug release from the gelatin nanoparticles.

These criteria produce different values for assessing the appropriateness of a model.

The time now is ddsolevr The similarity factor [ 13 ] is a comparison method that is recommended by regulatory guidelines. Controlled release of biologically active agents.