Extending the high-throughput toxicokinetics R package to include brain and adipose compartments

Chemical risk assessment has traditionally been performed based on in vivo studies. These studies have limited throughput, consequently leading to limited toxicity information for the majority of chemicals in industrial and commercial use. In addition, the translation from animal to human effects can be challenging. To increase human-relevant toxicity knowledge, high-throughput in vitro approaches have been developed. However, one challenge in employing these assays for hazard and risk assessment is the translation of in vitro bioactive concentrations to in vivo doses and internal tissue concentrations. To improve decision-making in chemical risk assessment, as well as drug discovery for humans, the U.S. Environmental Protection Agency has developed a simple physiologically based toxicokinetic (PBTK) model as part of the High-throughput Toxicokinetics open-source R package (httk ). In this study, the PBTK model was extended to include compartments for the brain and adipose tissues. The model incorporates a blood–brain barrier to control chemical penetration and disposition, which is essential for predicting neurotoxicity. The integration of an adipose tissue compartment further enables the prediction of bioaccumulation, particularly for lipophilic chemicals. The model’s performance was evaluated by comparing predicted chemical concentrations against experimental data from both oral and intravenous routes. This PBTK model extends the applicability of httk to allow for assessing potential neurotoxicity and chronic exposure to lipophilic chemicals and better evaluate chemical pharmacokinetics. Moreover, this PBTK model can act as a tool for optimizing dosages and other study parameters to reduce and refine the design of in vivo studies.

Authors

Institutions

Publication Details

Journal
Frontiers in Pharmacology
Published
2026-10-28
DOI
https://doi.org/10.3389/fphar.2026.1895108
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Extending the high-throughput toxicokinetics R package to include brain and adipose compartments

Aswani Unnikrishnan, John F. Wambaugh, Xiaoqing Chang, James Patrick Sluka et al.
1 links
Frontiers in Pharmacology
Computational Drug Discovery Methods
article

Extending the high-throughput toxicokinetics R package to include brain and adipose compartments

Aswani Unnikrishnan, John F. Wambaugh, Xiaoqing Chang, James Patrick Sluka, Matthew W. Linakis, Helena T. Högberg, Nicole Kleinstreuer, Anna Kreutz, Dingsheng Li
article en

Abstract

Chemical risk assessment has traditionally been performed based on in vivo studies. These studies have limited throughput, consequently leading to limited toxicity information for the majority of chemicals in industrial and commercial use. In addition, the translation from animal to human effects can be challenging. To increase human-relevant toxicity knowledge, high-throughput in vitro approaches have been developed. However, one challenge in employing these assays for hazard and risk assessment is the translation of in vitro bioactive concentrations to in vivo doses and internal tissue concentrations. To improve decision-making in chemical risk assessment, as well as drug discovery for humans, the U.S. Environmental Protection Agency has developed a simple physiologically based toxicokinetic (PBTK) model as part of the High-throughput Toxicokinetics open-source R package (httk ). In this study, the PBTK model was extended to include compartments for the brain and adipose tissues. The model incorporates a blood–brain barrier to control chemical penetration and disposition, which is essential for predicting neurotoxicity. The integration of an adipose tissue compartment further enables the prediction of bioaccumulation, particularly for lipophilic chemicals. The model’s performance was evaluated by comparing predicted chemical concentrations against experimental data from both oral and intravenous routes. This PBTK model extends the applicability of httk to allow for assessing potential neurotoxicity and chronic exposure to lipophilic chemicals and better evaluate chemical pharmacokinetics. Moreover, this PBTK model can act as a tool for optimizing dosages and other study parameters to reduce and refine the design of in vivo studies.

Frontiers in PharmacologyVol. 17
University of Nevada, Reno (US), National Institute of Environmental Health Sciences (US), UL Research Institutes (US), Applied Research Associates (United States) (US), Indiana University (US)
Good health and well-being
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon