Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma

Por um escritor misterioso

Last updated 30 março 2025

Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma

Applying Linear and Non-Linear Methods for Parallel Prediction of Volume of Distribution and Fraction of Unbound Drug

A Novel Methodology for Human Plasma Protein Binding: Prediction Validation and Applicability Domain - Pharmaceutical and Biomedical Research

PDF) Descriptor Free QSAR Modeling Using Deep Learning With Long Short-Term Memory Neural Networks

Pharmaceutics, Free Full-Text

Bayer's in silico ADMET platform: a journey of machine learning over the past two decades - ScienceDirect

Evaluation of quantitative structure property relationship algorithms for predicting plasma protein binding in humans - ScienceDirect

In silico prediction of brain exposure: drug free fraction, unbound brain to plasma concentration ratio and equilibrium half-life. - Abstract - Europe PMC

Descriptor-Free Deep Learning QSAR Model for the Fraction Unbound in Human Plasma

Applying Linear and Non-Linear Methods for Parallel Prediction of Volume of Distribution and Fraction of Unbound Drug

In silico prediction of brain exposure: drug free fraction, unbound brain to plasma concentration ratio and equilibrium half-life. - Abstract - Europe PMC

Toxics, Free Full-Text

Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds

Physicochemical property prediction, pKa, logP, logD

A hybrid modeling approach for assessing mechanistic models of small molecule partitioning in vivo using a machine learning-integrated modeling platform

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