Wei2022 - HobPre: accurate prediction of human oral bioavailability for small molecules

HobPre predicts the oral bioavailability of small molecules in humans. It has been trained using public data on ~1200 molecules (Falcón-Cano et al, 2020, complemented with other literature and ChEMBL compounds).

Model Type: Predictive machine learning model.
Model Relevance: Predicts Probability of a compound having high oral bioavailability.
Model Encoded by: Hellen Namulinda (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam

Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos2lqb