---
license: unknown
task_categories:
- tabular-classification
- graph-ml
- text-classification
tags:
- chemistry
- biology
- medical
pretty_name: TDC Caco-2 Wang
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: train
    path: tdc_caco2_wang.csv
---
# TDC Caco-2 Wang

Caco-2 Wang dataset [[1]](#1), part of TDC [[2]](#2) benchmark. It is intended to be used through 
[scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) library.

The task is to predict the rate at which drug passes through Caco-2 cells that serve as in vitro simulation of human intestinal tissue.

This dataset is a part of "absorption" subset of ADME tasks.

| **Characteristic** |      **Description**     |
|:------------------:|:------------------------:|
|        Tasks       |            1             |
|      Task type     |        regression        |
|    Total samples   |           910            |
|  Recommended split |         scaffold         |
| Recommended metric |           MAE            |

## References
<a id="1">[1]</a>
Wang, NN, et al.
"ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting"
Journal of Chemical Information and Modeling 2016 56 (4), 763-773
https://doi.org/10.1021/acs.jcim.5b00642

<a id="2">[2]</a> 
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
https://openreview.net/forum?id=8nvgnORnoWr