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Christopher E Keefer

Showing results (1-10 of 9) with videos related to

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Medchemcomm|August 16, 2018
The use of matched molecular series networks for cross target structure activity relationship translation and potency predictionChristopher E Keefer, George Chang
Journal of Chemical Information and Modeling|December 1, 2018
In-Silico Extraction of Design Ideas Using MMPA-by-QSAR and its Application on ADME EndpointsAlexios Koutsoukas, George Chang, Christopher E Keefer
Drug Metabolism Letters|September 16, 2011
Systematic and pairwise analysis of the effects of aromatic halogenation and trifluoromethyl substitution on human liver microsomal clearanceHao Sun, Christopher E Keefer, Dennis O Scott
Bioorganic & Medicinal Chemistry|May 28, 2011
Extraction of tacit knowledge from large ADME data sets via pairwise analysisChristopher E Keefer, George Chang, Gregory W Kauffman
Journal of Chemical Information and Modeling|January 25, 2013
Interpretable, probability-based confidence metric for continuous quantitative structure-activity relationship modelsChristopher E Keefer, Gregory W Kauffman, Rishi Raj Gupta
Bioorganic & Medicinal Chemistry|November 15, 2016
A multi-endpoint matched molecular pair (MMP) analysis of 6-membered heterocyclesGeorge Chang, Kim Huard, Gregory W Kauffman, et al.
Journal of Medicinal Chemistry|July 27, 2013
Evaluating the differences in cycloalkyl ether metabolism using the design parameter "lipophilic metabolism efficiency" (LipMetE) and a matched molecular pairs analysisAntonia F Stepan, Gregory W Kauffman, Christopher E Keefer, et al.
Journal of Medicinal Chemistry|June 14, 2017
In Silico Absorption, Distribution, Metabolism, Excretion, and Pharmacokinetics (ADME-PK): Utility and Best Practices. An Industry Perspective from the International Consortium for Innovation through Quality in Pharmaceutical DevelopmentFranco Lombardo, Prashant V Desai, Rieko Arimoto, et al.
Molecular Pharmaceutics|October 9, 2023
The Comparison of Machine Learning and Mechanistic In Vitro-In Vivo Extrapolation Models for the Prediction of Human Intrinsic ClearanceChristopher E Keefer, George Chang, Li Di, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Medchemcomm|August 16, 2018
The use of matched molecular series networks for cross target structure activity relationship translation and potency predictionChristopher E Keefer, George Chang
Journal of Chemical Information and Modeling|December 1, 2018
In-Silico Extraction of Design Ideas Using MMPA-by-QSAR and its Application on ADME EndpointsAlexios Koutsoukas, George Chang, Christopher E Keefer
Drug Metabolism Letters|September 16, 2011
Systematic and pairwise analysis of the effects of aromatic halogenation and trifluoromethyl substitution on human liver microsomal clearanceHao Sun, Christopher E Keefer, Dennis O Scott
Bioorganic & Medicinal Chemistry|May 28, 2011
Extraction of tacit knowledge from large ADME data sets via pairwise analysisChristopher E Keefer, George Chang, Gregory W Kauffman
Journal of Chemical Information and Modeling|January 25, 2013
Interpretable, probability-based confidence metric for continuous quantitative structure-activity relationship modelsChristopher E Keefer, Gregory W Kauffman, Rishi Raj Gupta
Bioorganic & Medicinal Chemistry|November 15, 2016
A multi-endpoint matched molecular pair (MMP) analysis of 6-membered heterocyclesGeorge Chang, Kim Huard, Gregory W Kauffman, et al.
Journal of Medicinal Chemistry|July 27, 2013
Evaluating the differences in cycloalkyl ether metabolism using the design parameter "lipophilic metabolism efficiency" (LipMetE) and a matched molecular pairs analysisAntonia F Stepan, Gregory W Kauffman, Christopher E Keefer, et al.
Journal of Medicinal Chemistry|June 14, 2017
In Silico Absorption, Distribution, Metabolism, Excretion, and Pharmacokinetics (ADME-PK): Utility and Best Practices. An Industry Perspective from the International Consortium for Innovation through Quality in Pharmaceutical DevelopmentFranco Lombardo, Prashant V Desai, Rieko Arimoto, et al.
Molecular Pharmaceutics|October 9, 2023
The Comparison of Machine Learning and Mechanistic In Vitro-In Vivo Extrapolation Models for the Prediction of Human Intrinsic ClearanceChristopher E Keefer, George Chang, Li Di, et al.
Pageof 1