---
license: mit
task_categories:
- tabular-regression
- graph-ml
- text-classification
tags:
- chemistry
- biology
- medical
pretty_name: Biogen ADME Solubility
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: solubility.csv
---
# Biogen ADME Solubility

Biogen_ADME_Solubility dataset from the Biogen ADME benchmark [[1]](#1). It is intended to be used through
[scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) library.

The task is to predict log10 of aqueous solubility at pH 6.8 (in ug/mL) of molecules.

| **Characteristic** |  **Description**  |
|:------------------:|:-----------------:|
|        Tasks       |         1         |
|      Task type     |    regression     |
|    Total samples   |       2173        |
|  Recommended split |       time        |
| Recommended metric |        MAE        |

## References
<a id="1">[1]</a>
Fang, Cheng, et al.
"Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective"
J. Chem. Inf. Model. 2023, 63, 11, 3263-3274
https://doi.org/10.1021/acs.jcim.3c00160