Chapter 1
Computational Toxicology Promotes
Regulatory Science
Rebecca Kusko and Huixiao Hong
Abstract New tools have become available to researchers and regulators including genomics, transcriptomics, proteomics, machine learning, artificial intelligence,
molecular dynamics, bioinformatics, systems biology, and other advanced techniques. These new advanced approaches originated elsewhere but over time have
perfused into the toxicology field, enabling more efficient risk assessment and safety
evaluation. While traditional toxicological methods remain in full swing, the continuing increase in the number of chemicals introduced into the environment requires
new toxicological methods for regulatory science that can overcome the shortcoming
of traditional toxicological methods. Computational toxicology is a new toxicological method which is much faster and cheaper than traditional methods. A variety
of methods have been developed in computational toxicology and some have been
adopted in regulatory science. This book summarizes some methods in computational toxicology and reviews multiple applications in regulatory science, indicating
that computational toxicology promotes regulatory science.
Keywords Computational toxicology · Regulatory science · Risk assessment ·
Safety evaluation · Chemicals
Abbreviations
3D
Three dimensional
AI
Artificial intelligence
R. Kusko
Immuneering Corporation, Cambridge, MA, USA
e-mail: bkusko@immuneering.com
H. Hong (B)
National Center for Toxicological Research, U.S. Food and Drug Administration,
Jefferson, AR, USA
e-mail: Huixiao.Hong@fda.hhs.gov
© This is a U.S. government work and not under copyright protection in the U.S.; foreign
copyright protection may apply 2019
H. Hong (ed.), Advances in Computational Toxicology, Challenges and Advances
in Computational Chemistry and Physics 30,
https://doi.org/10.1007/978-3-030-16443-0_1
1
Computational Toxicology Promotes
Regulatory Science
Rebecca Kusko and Huixiao Hong
Abstract New tools have become available to researchers and regulators including genomics, transcriptomics, proteomics, machine learning, artificial intelligence,
molecular dynamics, bioinformatics, systems biology, and other advanced techniques. These new advanced approaches originated elsewhere but over time have
perfused into the toxicology field, enabling more efficient risk assessment and safety
evaluation. While traditional toxicological methods remain in full swing, the continuing increase in the number of chemicals introduced into the environment requires
new toxicological methods for regulatory science that can overcome the shortcoming
of traditional toxicological methods. Computational toxicology is a new toxicological method which is much faster and cheaper than traditional methods. A variety
of methods have been developed in computational toxicology and some have been
adopted in regulatory science. This book summarizes some methods in computational toxicology and reviews multiple applications in regulatory science, indicating
that computational toxicology promotes regulatory science.
Keywords Computational toxicology · Regulatory science · Risk assessment ·
Safety evaluation · Chemicals
Abbreviations
3D
Three dimensional
AI
Artificial intelligence
R. Kusko
Immuneering Corporation, Cambridge, MA, USA
e-mail: bkusko@immuneering.com
H. Hong (B)
National Center for Toxicological Research, U.S. Food and Drug Administration,
Jefferson, AR, USA
e-mail: Huixiao.Hong@fda.hhs.gov
© This is a U.S. government work and not under copyright protection in the U.S.; foreign
copyright protection may apply 2019
H. Hong (ed.), Advances in Computational Toxicology, Challenges and Advances
in Computational Chemistry and Physics 30,
https://doi.org/10.1007/978-3-030-16443-0_1
1