Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Systematic development of pH-independent controlled release tablets of carvedilol using central composite design and artificial neural networks
Date
2013-08-01
Author
Aktas, Elcin
EROĞLU, HAKAN
Kockan, Umit
ÖNER, LEVENT
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
152
views
0
downloads
Cite This
The purpose of this study was to apply the optimization method incorporating artificial neural network (ANN) using pH-independent release of weakly basic drug, carvedilol from HPMC-based matrix formulation. Because of weakly basic nature of carvedilol, drug shows pH-dependent solubility. The enteric polymer EUDRAGIT L100 was added formulations to overcome pH-dependent solubility of carvedilol. Effects of the Hydroxypropylmethyl cellulose (HPMC) K4M and EUDRAGIT L100 amount on drug release were investigated. For this purpose 13 kinds of formulations were prepared at three different levels of each variables. The optimization of the formulation was evaluated by using ANN method. Two formulation parameters, the amounts of HPMC K4M and Eudragit L100 at three levels (-1, 0, 1) were selected as independent/input variables. In-vitro dissolution sampling times at twelve different time points were selected as dependent/output variables. By using experimental dissolution results and amount of HPMC K4M and EUDRAGIT L100, percentage of dissolved carvedilol was predicted by ANN. Similarity factor (f(2)) between predicted and experimentally observed profile was calculated and f(2) value was found 76.33. This value showed that there was no difference between predicted and experimentally observed drug release profile. As a result of these experiments, it was found that ANNs can be successfully used to optimize controlled release drug delivery systems.
Subject Keywords
Carvedilol
,
pH-dependent solubility
,
pH-independent release
,
Artificial neural network
,
HPMC K4M
,
Eudragit L100
URI
https://hdl.handle.net/11511/67541
Journal
DRUG DEVELOPMENT AND INDUSTRIAL PHARMACY
DOI
https://doi.org/10.3109/03639045.2012.705291
Collections
Graduate School of Natural and Applied Sciences, Article
Suggestions
OpenMETU
Core
Exponential stability of periodic solutions of recurrent neural networks with functional dependence on piecewise constant argument
Akhmet, Marat; Cengiz, Nur (The Scientific and Technological Research Council of Turkey, 2018-01-01)
In this study, we develop a model of recurrent neural networks with functional dependence on piecewise constant argument of generalized type. Using the theoretical results obtained for functional differential equations with piecewise constant argument, we investigate conditions for existence and uniqueness of solutions, bounded solutions, and exponential stability of periodic solutions. We provide conditions based on the parameters of the model.
Multi-time-scale input approaches for hourly-scale rainfall-runoff modeling based on recurrent neural networks
Ishida, Kei; Kiyama, Masato; Ercan, Ali; Amagasaki, Motoki; Tu, Tongbi (2021-11-01)
This study proposes two effective approaches to reduce the required computational time of the training process for time-series modeling through a recurrent neural network (RNN) using multi-time-scale time-series data as input. One approach provides coarse and fine temporal resolutions of the input time-series data to RNN in parallel. The other concatenates the coarse and fine temporal resolutions of the input time-series data over time before considering them as the input to RNN. In both approaches, first, ...
An experimental study on Power Amplifier linearisation by artificial neural networks Yapay Sinir Aǧlari ile Güç Yükselteç Doǧrusalląstirma Amaçli Deneysel Bir Çalisma
Yesil, Soner; Kolagasioglu, Ahmet Ertugrul; Yılmaz, Ali Özgür (2018-07-05)
This paper represents an experimental study on the linearisation of Power Amplifiers especially on high output power regions by utilizing an artificial neural network structure and open-loop training method. For the same in-band output power, 9dB EVM and 6dB ACLR improvement has been observed on hardware by feeding the proposed digital predistortion signal (DPD) to the PA under test.
IMPULSIVE SICNNS WITH CHAOTIC POSTSYNAPTIC CURRENTS
Fen, Mehmet Onur; Akhmet, Marat (2016-06-01)
In the present study, we investigate the dynamics of shunting inhibitory cellular neural networks (SICNNs) with impulsive effects. We give a mathematical description of the chaos for the multidimensional dynamics of impulsive SICNNs, and prove its existence rigorously by taking advantage of the external inputs. The Li-Yorke definition of chaos is used in our theoretical discussions. In the considered model, the impacts satisfy the cell and shunting principles. This enriches the applications of SICNNs and ma...
Sampling Performance of Multiple Independent Molecular Dynamics Simulations of an RNA Aptamer
Yan, Shuting; Peck, Jason M.; İlgü, Müslüm; Nilsen-Hamilton, Marit; Lamm, Monica H. (2020-08-01)
Using multiple independent simulations instead of one long simulation has been shown to improve the sampling performance attained with the molecular dynamics (MD) simulation method. However, it is generally not known how long each independent simulation should be, how many independent simulations should be used, or to what extent either of these factors affects the overall sampling performance achieved for a given system. The goal of the present study was to assess the sampling performance of multiple indep...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. Aktas, H. EROĞLU, U. Kockan, and L. ÖNER, “Systematic development of pH-independent controlled release tablets of carvedilol using central composite design and artificial neural networks,”
DRUG DEVELOPMENT AND INDUSTRIAL PHARMACY
, pp. 1207–1216, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67541.