compait

🔍 Overview

CoMPAIT (Collaborative Modeling Project for Acute Inhalation Toxicity) is a harmonized dataset of acute inhalation toxicity studies. It contains curated LC50 data (in mg/L and ppm), exposure phase (gas, vapor, aerosol), chemical identifiers (SMILES, DTXSID, CASRN), and hazard categories across multiple regulatory frameworks (e.g. GHS, EPA OPPT, EPA OPP, CPSC, DoT). The dataset supports development and evaluation of in silico models for inhalation toxicity and regulatory classification.

📦 Data Source

• NICEATM CoMPAIT Consortium
  URL: https://ntp.niehs.nih.gov/go/iccvam
  Citation: Kleinstreuer et al. (2018) Comp Tox; Strickland et al. (2023); Karmaus et al. (2022)
  License: CC BY 4.0

🔄 Transformations

• Preserved the original CoMPAIT challenge data as released by NICEATM
• Converted raw CSVs to a single Parquet file for efficient access
• No modifications, cleaning, or additional processing was applied

📁 Assets

• LC50_Tr.parquet (Parquet): Training set with curated LC50 data and chemical metadata

• PredictionSet.parquet (Parquet): Evaluation set for model predictions

🧪 Usage

biobricks install compait

import biobricks as bb
import pandas as pd

paths = bb.assets("compait")

# Available assets:

df_1 = pd.read_parquet(paths.LC50_Tr_parquet)

df_2 = pd.read_parquet(paths.PredictionSet_parquet)


print(df_1.head())      # Preview the first asset