Literature DB >> 8464826

Feasibility of developing a neural network for prediction of human pharmacokinetic parameters from animal data.

A S Hussain1, R D Johnson, N N Vachharajani, W A Ritschel.   

Abstract

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Year:  1993        PMID： 8464826     DOI： 10.1023/a:1018917128684

Source DB:  PubMed          Journal:  Pharm Res        ISSN： 0724-8741            Impact factor:   4.200


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  12 in total

Review 1.  Prediction of hepatic metabolic clearance: comparison and assessment of prediction models.

Authors:  J Zuegge; G Schneider; P Coassolo; T Lavé
Journal:  Clin Pharmacokinet       Date:  2001       Impact factor: 6.447

2.  The use of artificial neural networks for the selection of the most appropriate formulation and processing variables in order to predict the in vitro dissolution of sustained release minitablets.

Authors:  Michael M Leane; Iain Cumming; Owen I Corrigan
Journal:  AAPS PharmSciTech       Date:  2003       Impact factor: 3.246

Review 3.  Artificial neural network as a novel method to optimize pharmaceutical formulations.

Authors:  K Takayama; M Fujikawa; T Nagai
Journal:  Pharm Res       Date:  1999-01       Impact factor: 4.200

Review 4.  Perspectives in pharmacokinetics. Physiologically based pharmacokinetic modeling as a tool for drug development.

Authors:  S B Charnick; R Kawai; J R Nedelman; M Lemaire; W Niederberger; H Sato
Journal:  J Pharmacokinet Biopharm       Date:  1995-04

5.  Prediction of pharmacokinetic parameters and the assessment of their variability in bioequivalence studies by artificial neural networks.

Authors:  J Opara; S Primozic; P Cvelbar
Journal:  Pharm Res       Date:  1999-06       Impact factor: 4.200

6.  Use of artificial neural networks to predict drug dissolution profiles and evaluation of network performance using similarity factor.

Authors:  K K Peh; C P Lim; S S Quek; K H Khoh
Journal:  Pharm Res       Date:  2000-11       Impact factor: 4.200

7.  Empirical versus mechanistic modelling: comparison of an artificial neural network to a mechanistically based model for quantitative structure pharmacokinetic relationships of a homologous series of barbiturates.

Authors:  I S Nestorov; S T Hadjitodorov; I Petrov; M Rowland
Journal:  AAPS PharmSci       Date:  1999

Review 8.  The backpropagation neural network--a Bayesian classifier. Introduction and applicability to pharmacokinetics.

Authors:  R J Erb
Journal:  Clin Pharmacokinet       Date:  1995-08       Impact factor: 6.447

9.  Formulation optimization of paclitaxel carried by PEGylated emulsions based on artificial neural network.

Authors:  Tianyuan Fan; Kozo Takayama; Yoshiyuki Hattori; Yoshie Maitani
Journal:  Pharm Res       Date:  2004-09       Impact factor: 4.200

10.  Neural network predicted peak and trough gentamicin concentrations.

Authors:  M E Brier; J M Zurada; G R Aronoff
Journal:  Pharm Res       Date:  1995-03       Impact factor: 4.200
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