Rong2020 - Grover-clintox: A classification model to predict the likelihood of failure in clinical trials due to toxicity

This model has been trained using the GROVER transformer and the Molecule Net dataset ClinTox, the authors trained a classification model to predict the likelihood of failure in clinical trials due to toxicity. The dataset has been built using FDA approved drugs (non-toxic) and a set of drugs that have failed at advanced clinical trial stages. Model Type: Predicitive machine learning model. Model Relevance: Probability that a molecule is approved by the FDA and probability that a molecule shows toxicity in clinical trials. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos6fza