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Cheminformatics Analysis of Assertions Mined from Literature That Describe Drug-Induced Liver Injury in Different Species
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/hep.21095openalex-snapshot
Drug-induced liver injury: Summary of a single topic clinical research conference
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Computational chemistry approach for the early detection of drug‐induced idiosyncratic liver toxicity
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Concordance of the Toxicity of Pharmaceuticals in Humans and in Animals
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The Nature of Statistical Learning Theory
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High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening
inferredcites →https://doi.org/10.1007/s10822-005-9008-0openalex-snapshot
Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures
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Predictive value of in vitro safety studies
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In silico prediction of drug safety: despite progress there is abundant room for improvement
inferredcites →https://doi.org/10.1016/j.jmgm.2004.03.009openalex-snapshot
Modelling in vitro hepatotoxicity using molecular interaction fields and SIMCA
inferredcites →https://doi.org/10.1016/j.taap.2008.01.037openalex-snapshot
Microarray analysis in rat liver slices correctly predicts in vivo hepatotoxicity
inferredcites →https://doi.org/10.1016/j.toxlet.2008.09.017openalex-snapshot
Use of toxicogenomics to understand mechanisms of drug-induced hepatotoxicity during drug discovery and development
inferredcites →https://doi.org/10.1016/s0168-8278(97)80494-1openalex-snapshot
Hepatotoxicity in drug development: detection, significance and solutions
inferredcites →https://doi.org/10.1016/s0378-4274(98)00261-6openalex-snapshot
The predictivity of the toxicity of pharmaceuticals in humans from animal data — an interim assessment
inferredcites →https://doi.org/10.1021/ci700443vopenalex-snapshot
Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis
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Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection
inferredcites →https://doi.org/10.1021/tx600260aopenalex-snapshot
Applying Mechanisms of Chemical Toxicity to Predict Drug Safety
inferredcites →https://doi.org/10.1023/b:jcam.0000021834.50768.c6openalex-snapshot
In silico models for the prediction of dose-dependent human hepatotoxicity
inferredcites →https://doi.org/10.1080/07366290601067481openalex-snapshot
QSPR Modeling of the AmIII/EuIIISeparation Factor: How Far Can we Predict ?
inferredcites →https://doi.org/10.1093/toxsci/kfn109openalex-snapshot
Cellular Imaging Predictions of Clinical Drug-Induced Liver Injury
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Evaluation of the Characteristics of Safety Withdrawal of Prescription Drugs from Worldwide Pharmaceutical Markets-1960 to 1999
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Drug-Induced Liver Injury
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Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening
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In Vitro Methods to Study Chemically-Induced Hepatotoxicity: A Literature Review
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ISIDA - Platform for Virtual Screening Based on Fragment and Pharmacophoric Descriptors
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Drug‐Induced Hepatotoxicity: Advances in Preclinical Predictive Strategies and Tools
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BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs
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The Nuremberg Code subverts human health and safety by requiring animal modeling
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Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation
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Expectations for methodology and translation of animal research: a survey of health care workers
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Animal to human translation: a systematic scoping review of reported concordance rates
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Efficiency of different measures for defining the applicability domain of classification models
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Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)
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Synthesis, DFT, in-silico molecular docking, molecular dynamic simulation and ADMET studies of (Z)-2,6-bis(4-bromophenyl)-3,3-dimethyl-4-(2-(2,4,6-trichlorophenyl) hydrazono) piperidine derivatives against the SARS-CoV-2 main-protease
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In silicomodels for drug-induced liver injury – current status
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The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors
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Exploring Quantitative Nanostructure-Activity Relationships (QNAR) Modeling as a Tool for Predicting Biological Effects of Manufactured Nanoparticles
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Applications of Machine Learning Methods in Drug Toxicity Prediction
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Toward Predictive Models for Drug-Induced Liver Injury in Humans: Are we There Yet?
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Animal Models in an Age of Personalized Medicine
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Artificial Intelligence in Drug Discovery and Development Against Antimicrobial Resistance: A Narrative Review
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Metabolic activation in drug-induced liver injury
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Hepatotoxicity: A scheme for generating chemical categories for read-across, structural alerts and insights into mechanism(s) of action
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Computer-aided design of carbon nanotubes with the desired bioactivity and safety profiles
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SYNTHESIS, SPECTRAL, QUANTUM CHEMICAL METHOD, In-silico MOLECULAR DOCKING, AND ADMET ANALYSIS OF (E)-ISOBUTYL 2-(2-(4-CHLOROPHENYL) HYDRAZONO)-3- OXOBUTANOATE DERIVATIVES
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Inhibitory effect of Fisetin against the aggregation process of SOD1 E100K mutant: computer-based drug design as a potential therapeutic for ALS disease
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A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts
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An In Silico Model for Predicting Drug-Induced Hepatotoxicity
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Toxicological Potential of the FDA-Approved Treatment against Monkeypox. Comment on Zovi et al. Pharmacological Agents with Antiviral Activity against Monkeypox Infection. Int. J. Mol. Sci. 2022, 23, 15941
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In Silico Identification and In Vitro Validation of Repurposed Compounds Targeting the RSV Polymerase
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Hepatotoxicity Modeling Using Counter-Propagation Artificial Neural Networks: Handling an Imbalanced Classification Problem
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Artificial Intelligence-Driven Drug Toxicity Prediction: Advances, Challenges, and Future Directions
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Applications of Chemoinformatics in Predictive Toxicology for Regulatory Purposes, Especially in the Context of the EU REACH Legislation
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Per Aspera Ad Astra : Application of Simplex Qsar Approach in Antiviral Research
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Atomoxetine: toxicological aspects of a new treatment for attention deficit hyperactivity disorder in Brazil
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New Insights into Toxicity and Drug Testing
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Systematic Reviews of Animal Models: Methodology versus Epistemology
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