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Analysis of Pfizer Compounds in EPA’s ToxCast Chemicals-Assay Space

Chemical research in toxicology, 2014-01, Vol.27 (1), p.86-98

2014

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The development of structure-activity relationships for mitochondrial dysfunction: uncoupling of oxidative phosphorylation

Toxicological sciences, 2013-01, Vol.131 (1), p.271-278

2013

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Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database

Regulatory toxicology and pharmacology, 2023-02, Vol.138, p.105309, Article 105309

2023

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Developing Structure−Activity Relationships for the Prediction of Hepatotoxicity

Chemical research in toxicology, 2010-07, Vol.23 (7), p.1215-1222

2010

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It's difficult, but important, to make negative predictions

Regulatory toxicology and pharmacology, 2016-04, Vol.76, p.79-86

2016

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Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtained

Regulatory toxicology and pharmacology, 2016-04, Vol.76, p.7-20

2016

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Industry-scale application and evaluation of deep learning for drug target prediction

Journal of cheminformatics, 2020-04, Vol.12 (1), p.26-26, Article 26

2020

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The Impact of Novel Assessment Methodologies in Toxicology on Green Chemistry and Chemical Alternatives

Toxicological sciences, 2018-02, Vol.161 (2), p.276-284

2018

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Evaluation of a Published in Silico Model and Construction of a Novel Bayesian Model for Predicting Phospholipidosis Inducing Potential

Journal of chemical information and modeling, 2007-05, Vol.47 (3), p.1196-1205

2007

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The computational prediction of genotoxicity

Expert opinion on drug metabolism & toxicology, 2010-07, Vol.6 (7), p.797-807

2010

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Computer systems for the prediction of toxicity: an update

Advanced drug delivery reviews, 2002-03, Vol.54 (3), p.417-431

Greene, Nigel

2002

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Modeling the mechanism of action of a DGAT1 inhibitor using a causal reasoning platform

PloS one, 2011-11, Vol.6 (11), p.e27009-e27009

2011

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Accelerating Drug Product Development and Approval: Early Development and Evaluation

Pharmaceutical research, 2024, Vol.41 (1), p.1-6

2024

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Machine Learning Models for Human In Vivo Pharmacokinetic Parameters with In-House Validation

Molecular pharmaceutics, 2021-12, Vol.18 (12), p.4520-4530

2021

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Computational toxicology, friend or foe?

Toxicology research (Cambridge), 2015-01, Vol.4 (5), p.1159-1172

2015

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Comparing Measures of Promiscuity and Exploring Their Relationship to Toxicity

Molecular informatics, 2012-02, Vol.31 (2), p.145-159

2012

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Chemotypes sensitivity and predictivity of in vivo outcomes for cytotoxic assays in THLE and HepG2 cell lines

Bioorganic & medicinal chemistry letters, 2014-06, Vol.24 (12), p.2753-2757

2014

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Setting Clinical Exposure Levels of Concern for Drug-Induced Liver Injury (DILI) Using Mechanistic in vitro Assays

Toxicological sciences, 2015-10, Vol.147 (2), p.500-514

2015

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Perspectives on the use of machine learning for ADME prediction at AstraZeneca

Xenobiotica, 2024-08, Vol.54 (7), p.368

2024

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Prediction of In Vivo Pharmacokinetic Parameters and Time–Exposure Curves in Rats Using Machine Learning from the Chemical Structure

Molecular pharmaceutics, 2022-05, Vol.19 (5), p.1488-1504

2022

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Deriving acceptable limits for non-mutagenic impurities in medicinal products – Durational adjustments

Regulatory toxicology and pharmacology, 2024-06, Vol.150, p.105644-105644, Article 105644

2024

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Physiochemical drug properties associated with in vivo toxicological outcomes

Bioorganic & medicinal chemistry, 2008-09, Vol.18 (17), p.4872-4875

2008

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Mechanisms of Nitrosamine Mutagenicity and Their Relationship to Rodent Carcinogenic Potency

Chemical research in toxicology, 2024-02, Vol.37 (2), p.181-198

2024

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Physicochemical drug properties associated with in vivo toxicological outcomes: a review

Expert opinion on drug metabolism & toxicology, 2009-08, Vol.5 (8), p.921-931

2009

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Finding the rules for successful drug optimisation

Drug discovery today, 2014-05, Vol.19 (5), p.680-687

2014

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Analysis of Pfizer Compounds in EPA’s ToxCast Chemicals-Assay Space

The development of structure-activity relationships for mitochondrial dysfunction: uncoupling of oxidative phosphorylation

Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database

Developing Structure−Activity Relationships for the Prediction of Hepatotoxicity

It's difficult, but important, to make negative predictions

Evaluation of a statistics-based Ames mutagenicity QSAR model and interpretation of the results obtained

Industry-scale application and evaluation of deep learning for drug target prediction

The Impact of Novel Assessment Methodologies in Toxicology on Green Chemistry and Chemical Alternatives

Evaluation of a Published in Silico Model and Construction of a Novel Bayesian Model for Predicting Phospholipidosis Inducing Potential

The computational prediction of genotoxicity

Computer systems for the prediction of toxicity: an update

Modeling the mechanism of action of a DGAT1 inhibitor using a causal reasoning platform

Accelerating Drug Product Development and Approval: Early Development and Evaluation

Machine Learning Models for Human In Vivo Pharmacokinetic Parameters with In-House Validation

Computational toxicology, friend or foe?

Comparing Measures of Promiscuity and Exploring Their Relationship to Toxicity

Chemotypes sensitivity and predictivity of in vivo outcomes for cytotoxic assays in THLE and HepG2 cell lines

Setting Clinical Exposure Levels of Concern for Drug-Induced Liver Injury (DILI) Using Mechanistic in vitro Assays

Perspectives on the use of machine learning for ADME prediction at AstraZeneca

Prediction of In Vivo Pharmacokinetic Parameters and Time–Exposure Curves in Rats Using Machine Learning from the Chemical Structure

Deriving acceptable limits for non-mutagenic impurities in medicinal products – Durational adjustments

Physiochemical drug properties associated with in vivo toxicological outcomes

Mechanisms of Nitrosamine Mutagenicity and Their Relationship to Rodent Carcinogenic Potency

Physicochemical drug properties associated with in vivo toxicological outcomes: a review

Finding the rules for successful drug optimisation

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