Prediction of the in vitro permeability determined in Caco-2 cells by using artificial neural networks.
about
Systems biological approach of molecular descriptors connectivity: optimal descriptors for oral bioavailability predictionDrug-permeability and transporter assays in Caco-2 and MDCK cell lines.Continuous Intestinal Absorption Model Based on the Convection-Diffusion Equation.Multi-functional scaling methodology for translational pharmacokinetic and pharmacodynamic applications using integrated microphysiological systems (MPS).Drug discovery and regulatory considerations for improving in silico and in vitro predictions that use Caco-2 as a surrogate for human intestinal permeability measurements.Drug permeability prediction using PMF method.QSAR Prediction of Passive Permeability in the LLC-PK1 Cell Line: Trends in Molecular Properties and Cross-Prediction of Caco-2 Permeabilities.Predicting binding affinities of diverse pharmaceutical chemicals to human serum plasma proteins using QSPR modelling approaches.Brivaracetam, a selective high-affinity synaptic vesicle protein 2A (SV2A) ligand with preclinical evidence of high brain permeability and fast onset of action.Effect of anionic macromolecules on intestinal permeability of furosemide.Prediction of drug distribution in rat and humans using an artificial neural networks ensemble and a PBPK model.Biopartitioning Micellar Chromatography-Partition Coefficient Micelle/Water as a Potential Descriptor for Hydrophobicity in Prediction of Oral Drug Absorption
P2860
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P2860
Prediction of the in vitro permeability determined in Caco-2 cells by using artificial neural networks.
description
2010 nî lūn-bûn
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2010年の論文
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2010年学术文章
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2010年学术文章
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2010年学术文章
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2010年学术文章
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2010年学术文章
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name
Prediction of the in vitro per ...... ng artificial neural networks.
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Prediction of the in vitro per ...... ng artificial neural networks.
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type
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Prediction of the in vitro per ...... ng artificial neural networks.
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Prediction of the in vitro per ...... ng artificial neural networks.
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Prediction of the in vitro per ...... ng artificial neural networks.
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Prediction of the in vitro per ...... ng artificial neural networks.
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P1476
Prediction of the in vitro per ...... ng artificial neural networks.
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P2093
José A G Morais
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P356
10.1016/J.EJPS.2010.05.014
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P577
2010-06-08T00:00:00Z