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

Pharmaceutics, Free Full-Text

Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization – arXiv Vanity

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

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

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

AMPL: A Data-Driven Modeling Pipeline for Drug Discovery – arXiv Vanity

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

Ensemble Machine Learning Approaches Based on Molecular Descriptors and Graph Convolutional Networks for Predicting the Efflux Activities of MDR1 and BCRP Transporters

QSAR Model of Unbound Brain-to-Plasma Partition Coefficient, Kp, uu, brain: Incorporating P-glycoprotein Efflux as a Variable

Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships: The Report and Recommendations of ECVAM Workshop 521,2 - Tatiana I. Netzeva, Andrew P. Worth, Tom Aldenberg, Romualdo Benigni

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

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

Pharmaceutics, Free Full-Text

IJMS, Free Full-Text

DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning, Journal of Cheminformatics