Artificial Neural Networks Applied to the In Vitro-In Vivo Correlation of an Extended-Release Formulation: Initial Trials and Experience

1999 ◽  
Vol 88 (1) ◽  
pp. 154-160 ◽  
Author(s):  
James A. Dowell ◽  
Ajaz Hussain ◽  
John Devane ◽  
David Young
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Extended Release ◽  
Release Formulation ◽  
Extended Release Formulation ◽  
Artificial Neural

scholarly journals Development and biopharmaceutical evaluation of extended release formulation of tramadol hydrochloride based on osmotic technology

2009 ◽  
Vol 59 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Pramod Kumar ◽  
Sanjay Singh ◽  
Brahmeshwar Mishra
Keyword(s):  
Drug Release ◽  
Extended Release ◽  
Relative Bioavailability ◽  
Pharmacokinetic Parameters ◽  
Healthy Human ◽  
Tramadol Hydrochloride ◽  
Release Formulation ◽  
Extended Release Formulation

Development and biopharmaceutical evaluation of extended release formulation of tramadol hydrochloride based on osmotic technologyExtended release formulation of tramadol hydrochloride (TRH) based on osmotic technology was developed and evaluated. Target release profile was selected and different variables were optimized to achieve it. Formulation variables such as the level of swellable polymer, plasticizer and the coat thickness of semipermeable membrane (SPM) were found to markedly affect drug release. TRH release was directly proportional to the levels of plasticizer but inversely proportional to the levels of swellable polymer and coat thickness of SPM. Drug release from developed formulations was independent of pH and agitation intensity but dependent on osmotic pressure of the release media.In vivostudy was also performed on six healthy human volunteers and various pharmacokinetic parameters (cmax,tmax,AUC0-24,MRT) and relative bioavailability were calculated. Thein vitroandin vivoresults were compared with the performance of two commercial TRH tablets. The developed formulation provided more prolonged and controlled TRH release compared to the marketed formulation.In vitro-in vivocorrelation (IVIVC) was analyzed according to the Wagner-Nelson method. The optimized formulation (batch IVB) exhibited good IVIV correlation (R= 0.9750). The manufacturing procedure was found to be reproducible and formulations were stable over 6 months of accelerated stability testing.

In vitro and in vivo release of dinalbuphine sebacate extended release formulation: Effect of the oil ratio on drug release

2017 ◽  
Vol 531 (1) ◽  
pp. 306-312 ◽  
Author(s):  
Chan-Jung Li ◽  
Mei-Yun Ku ◽  
Chia-Yin Lu ◽  
Yu-En Tien ◽  
Wendy H. Chern ◽  
...  
Keyword(s):  
Drug Release ◽  
Extended Release ◽  
Release Formulation ◽  
Extended Release Formulation ◽  
In Vivo Release

Development of an Extended-Release Formulation of Capecitabine Making Use of In Vitro–In Vivo Correlation Modelling

2014 ◽  
Vol 103 (2) ◽  
pp. 478-484 ◽  
Author(s):  
Jelte Meulenaar ◽  
Ron J. Keizer ◽  
Jos H. Beijnen ◽  
Jan H.M. Schellens ◽  
Alwin D.R. Huitema ◽  
...  
Keyword(s):  
Extended Release ◽  
Release Formulation ◽  
Extended Release Formulation ◽  
Correlation Modelling

scholarly journals Development of an Extended-Release Formulation for Apremilast and a Level A in Vitro–in Vivo Correlation Study in Beagle Dogs

2016 ◽  
Vol 64 (11) ◽  
pp. 1607-1615 ◽  
Author(s):  
Meiqiong Tang ◽  
Ping Hu ◽  
Shigui Huang ◽  
Qiang Zheng ◽  
Hao Yu ◽  
...  
Keyword(s):  
Extended Release ◽  
Correlation Study ◽  
Beagle Dogs ◽  
Release Formulation ◽  
Extended Release Formulation

Evaluation of an in vitro in vivo correlation for nebulizer delivery using artificial neural networks

2007 ◽  
Vol 96 (12) ◽  
pp. 3293-3303 ◽  
Author(s):  
Marcel de Matas ◽  
Qun Shao ◽  
Victoria Louise Silkstone ◽  
Henry Chrystyn
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural
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