# QSAR Models for Predicting Oral Bioavailability and Volume of Distribution and Their Application in Mapping the TK Space of Endocrine Disruptors

## TL;DR

This paper develops QSAR models to predict how chemicals behave in the body, focusing on endocrine disruptors that may pose health risks.

## Contribution

The novel contribution is the development of QSAR models for oral bioavailability and VDss using machine learning and their application to endocrine-disrupting chemicals.

## Key findings

- QSAR models achieved a Q2F3 of 0.34 for oral bioavailability prediction using R-CatBoost.
- The best VDss prediction model had a geometric mean fold error (GMFE) of 2.35 using R-RF.
- The models identified endocrine-disrupting chemicals with high risk based on their toxicokinetic profiles.

## Abstract

Toxicokinetic (TK) properties are essential in the framework of chemical risk assessment and drug discovery. Specifically, a TK profile provides information about the fate of chemicals in the human body. In this context, Quantitative Structure–Activity Relationship (QSAR) models are convenient computational tools for predicting TK properties. Here, we developed QSAR models to predict two TK properties: oral bioavailability and volume of distribution at steady state (VDss). We collected and curated two large sets of 1712 and 1591 chemicals for oral bioavailability and VDss, respectively, and compared regression and classification (binary and multiclass) models with the application of several machine learning algorithms. The best predictive performance of the models for regression (R) prediction was characterized by a Q2F3 of 0.34 with the R-CatBoost model for oral bioavailability and a geometric mean fold error (GMFE) of 2.35 with the R-RF model for VDss. The models were then applied to a list of potential endocrine-disrupting chemicals (EDCs), highlighting chemicals with a high probability of posing a risk to human health due to their TK profiles. Based on the results obtained, insights into the structural determinants of TK properties for EDCs are further discussed.