ATSDR’s Simulation Science Section
Computational modeling is a process that uses computers to simulate and study complex systems using math, physics, and computer science. ATSDR’s Simulation Science Section uses computational modeling to support a variety of public health research projects and initiatives focused on protecting the health of people and communities. The Simulation Science Section collaborates with public health professionals, health assessors at CDC and state health departments, emergency response teams, and academic researchers at colleges and universities.
With computational modeling, researchers can use several data streams and apply mathematical methods to figure out what might happen in a chemical incident or outbreak. ATSDR researchers use computational modeling to do the following:
- Estimate chemical levels in the body
- Understand how chemicals transport and change in the environment
- Link chemicals with potential human health effects
- Provide missing data on potential harmful effects of chemicals
Computational modeling helps researchers gain insight into public health issues and efficiently find solutions. With computational modeling, researchers can evaluate thousands of hazardous substances to identify potential health risks quickly and inexpensively.
Computational modeling also allows researchers to generate reliable data without using human subjects or lab animals in experiments. This is helpful for assessing potential health risks from situations that have never happened before or circumstances that are hard to recreate in an experimental lab.
The bottom line: Computational modeling saves time and resources by maximizing efficiency and filling in data gaps.
ATSDR’s Simulation Science Section uses four main types of computational modeling:
- Physiologically based toxicokinetic (PBTK) models describe what happens when chemicals enter a person’s body. These models help researchers to link environmental exposures to internal body burden levels.
- Benchmark dose models help researchers determine whether a specific chemical dose or concentration will produce a certain effect in a person’s body (like weight loss or growth of a tumor).
- Structure-activity relationship (SAR) models help researchers learn about the potential health effects of unknown or poorly understood substances by comparing them to well-studied substances with similar chemical structures.
- Fate and transport models predict how chemicals move in and transfer between air, soil, and water. Water models are a subtype of the fate and transport model that ATSDR researchers have used to identify people who may have been exposed to harmful levels of contaminated drinking water.
If you’re interested in collaborating with ATSDR’s Simulation Science Section, or if you’d like to use computational modeling in your research project or initiative, contact Simulation Science Section Chief Patricia Ruiz at email@example.com.
Read recent publications from the Simulation Science Section:
- Exploring Mechanistic Toxicity of Mixtures Using PBPK Modeling and Computational Systems Biology – PubMed (nih.gov)
- Meta-analysis of animal studies applied to short-term inhalation exposure levels of hazardous chemicals
- Development, validation and integration of in silico models to identify androgen active chemicals – PubMed (nih.gov)
- Development of a human Physiologically Based Pharmacokinetic (PBPK) Toolkit for environmental pollutants
- 3,3′-Dichlorobiphenyl Is Metabolized to a Complex Mixture of Oxidative Metabolites, Including Novel Methoxylated Metabolites, by HepG2 Cells – PubMed (nih.gov)
- Application of computational tools to health and environmental sciences, Volume II
- Human CYP2A6, CYP2B6, AND CYP2E1 Atropselectively Metabolize Polychlorinated Biphenyls to Hydroxylated Metabolites – PubMed (nih.gov)
- Bayesian toxicokinetic modeling of cadmium exposure in Chinese population – PubMed (nih.gov)
- Characterization of the Metabolic Pathways of 4-Chlorobiphenyl (PCB3) in HepG2 Cells Using the Metabolite Profiles of Its Hydroxylated Metabolites – PubMed (nih.gov)
- Metabolism of 3-Chlorobiphenyl (PCB 2) in a Human-Relevant Cell Line: Evidence of Dechlorinated Metabolites – PubMed (nih.gov)
- S. Federal Agencies and Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM).
- Advances in Assessing Hazard and Risk to Emerging Threats and Emergency Response: Comparing and Contrasting Efforts of 3 Federal Agencies – PubMed (nih.gov)
- CATMoS: Collaborative Acute Toxicity Modeling Suite – PubMed (nih.gov)
- CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity – PubMed (nih.gov)
- Exploring current read-across applications and needs among selected S. Federal Agencies – PubMed (nih.gov)
- IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making – PubMed (nih.gov)
- PBPK model reporting template for chemical risk assessment applications – PubMed (nih.gov)
- In Silico Protocol Consortium
- In silico toxicology protocols – PubMed (nih.gov)
- Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches – PubMed (nih.gov)