Research Articles
Beyond the Balance: Advanced Strategies for Tackling Imbalanced Data in ADMET Machine Learning
This article provides a comprehensive guide for drug discovery scientists and computational researchers on overcoming the pervasive challenge of imbalanced datasets in ADMET machine learning.
A Practical Guide to SwissADME: Mastering In Silico Pharmacokinetic Profiling for Drug Discovery
This guide provides researchers, scientists, and drug development professionals with a comprehensive framework for using SwissADME, a pivotal in silico tool for predicting the pharmacokinetic properties of small molecules.
A Practical Protocol for OCHEM: Accelerating Drug Discovery with Online Chemical Modeling
This article provides a comprehensive guide for researchers and drug development professionals on leveraging the Online Chemical Modeling Environment (OCHEM).
Beyond the Molecule: Best Practices in Molecular Representation for Robust ADMET Modeling
Accurate prediction of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties is a critical bottleneck in drug discovery.
Implementing Random Forest for ADMET Classification: A Practical Guide for Drug Development
This article provides a comprehensive guide for researchers and drug development professionals on implementing Random Forest (RF) models for predicting Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties.
Deep Neural Networks in Toxicity Endpoint Prediction: Transforming Drug Safety with AI
This article provides a comprehensive overview of the application of Deep Neural Networks (DNNs) for predicting chemical and drug toxicity endpoints.
Quantum Mechanics in Metabolic Stability Prediction: From Fundamental Principles to Quantum Computing
This article provides a comprehensive examination of quantum mechanical (QM) applications in predicting metabolic stability, a critical parameter in drug discovery.
Integrating Molecular Docking with ADMET Prediction: Strategies for Accelerating Drug Discovery
This article provides a comprehensive overview of the integrated computational approach of molecular docking and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling in modern drug discovery.
Advancing Drug Safety: A Comprehensive Guide to QSAR Modeling for Cytochrome P450 Inhibition Prediction
This article provides a comprehensive overview of Quantitative Structure-Activity Relationship (QSAR) modeling for predicting Cytochrome P450 (CYP) enzyme inhibition, a critical factor in assessing drug-drug interactions (DDIs) and ensuring drug...
Machine Learning for Caco-2 Permeability Prediction: A Comprehensive Guide for Drug Development
This article provides a comprehensive analysis of machine learning (ML) applications for predicting Caco-2 cell permeability, a critical parameter in oral drug development.