Tox
Toxicity
Task Overview
Majority of the drugs have some extents of toxicity to the human organisms. This learning task aims to predict accurately various types of toxicity of a drug molecule towards human organisms.
Impact
Toxicity is one of the primary causes of compound attrition. Study shows that approximately 70% of all toxicity-related attrition occurs preclinically (i.e., in cells, animals) while they are strongly predictive of toxicities in humans. This suggests that an early but accurate prediction of toxicity can significantly reduce the compound attribution and boost the likelihood of being marketed.
Generalization
Similar to the ADME prediction, as the drug structures of interest evolve over time, toxicity prediction requires a model to generalize to a set of novel drugs with small structural similarity to the existing drug set.
Product
Small-molecule.
Pipeline Stage
Efficacy and safety - lead development and optimization.
Usage Example
You can access these datasets using the PyTDC library:
from tdc_ml.single_pred import Tox
# Load a dataset
data = Tox(name='hERG')
# Access the data
df = data.get_data()
print(df.head())