load_pampa_approved_drugs

skfp.datasets.tdc.adme.load_pampa_approved_drugs(data_dir: str | PathLike | None = None, as_frame: bool = False, verbose: bool = False) → DataFrame | tuple[list[str]] | ndarray

Load the approved drugs subset of PAMPA dataset.

PAMPA (parallel artificial membrane permeability assay) is an assay to evaluate drug permeability across the cellular membrane. The task models only the passive membrane diffusion [1] [2]. This is the “approved drugs” subset that includes 142 marketed-approved drugs assessed by NCATS [1].

This dataset is a part of “absorption” subset of ADME tasks.

Tasks	1
Task type	classification
Total samples	142
Recommended split	scaffold
Recommended metric	AUROC

Parameters:

• data_dir ({None, str, path-like}, default=None) – Path to the root data directory. If None, currently set scikit-learn directory is used, by default $HOME/scikit_learn_data.

• as_frame (bool, default=False) – If True, returns the raw DataFrame with columns: “SMILES”, “label”. Otherwise, returns SMILES as list of strings, and labels as a NumPy array (1D integer binary vector).

• verbose (bool, default=False) – If True, progress bar will be shown for downloading or loading files.

Returns:

data – Depending on the as_frame argument, one of: - Pandas DataFrame with columns: “SMILES”, “label” - tuple of: list of strings (SMILES), NumPy array (labels)

Return type:

pd.DataFrame or tuple(list[str], np.ndarray)

References

[1] (1,2)

Siramshetty, V.B., Shah, P., et al. “Validating ADME QSAR Models Using Marketed Drugs” SLAS Discovery 2021 Dec;26(10):1326-1336.

[2]

Huang, Kexin, et al. “Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development” Proceedings of Neural Information Processing Systems, NeurIPS Datasets and Benchmarks, 2021