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Educational Programs for Computational Toxicology and Pharmacology

DALE E. JOHNSON*a,b AND RUDY J. RICHARDSONa

aUniversity of Michigan, School of Public Health, Department of Environmental health sciences, Апп arbor, Mi 48109-2029, usA; buniversity of California, Berkeley, Department of nutritional sciences and toxicology, Morgan ШП, Berkeley, CA 94720-3104, usA *e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

Introduction

Computational toxicology is an expanding research endeavor that attempts to meld advances in molecular biology and chemistry with modeling and computational science, in order to increase the predictive power of toxicological assessments. the goals of computational toxicology are to create a more rapid approach to access the potential toxicity of potential new drugs in early stages of research and development, and to create greater efficiency and effectiveness in determining and understanding the hazards and potential risk of the many chemical-related stressors that exist or that will potentially enter the environment. An overall goal is to decrease uncertainties in information (or lack of information) necessary to protect human health and sustainability of the environment. the integration of information from

Issues in Toxicology No. 31

Computational Systems Pharmacology and Toxicology Edited by Dale E. Johnson and Rudy J. Richardson © The Royal Society of Chemistry 2017 Published by the Royal Society of Chemistry, www.rsc.org large-scale datasets utilizing many levels of biological organization and systems biology pathways requires several types of computer tools and modeling techniques, and an intuitive approach to solve problems in new and different ways.1-4

In the past several years, we have witnessed rapid advances in computer science, systems biology, chemistry, and other disciplines that continue to enable powerful new computational tools and models highly applicable for toxicology and pharmacology.4-8 These tools and models hold tremendous promise for advancing applied and basic science, accelerating and streamlining drug efficacy and safety testing,9-11 and to increase the efficiency and effectiveness of hazard identification and risk assessment for the exposure to environmental chemicals.358 These approaches also offer the potential to improve toxicological experimental design, reduce the overall number of experimental toxicology studies needed, and reduce the number of animals used in experimentation. The principles of drug action, covering both efficacy and safety aspects, involve complex interactions, both predicted and experimentally determined between a chemical or biological therapeutic targets and multiple pathways and networks within the body. These in vivo phenomena are influenced by disease, overall health status, and the influences of co-exposures to dietary and environmental chemicals and other therapeutics.9-14

Regulatory agencies world-wide have established computational toxicology programs internally; there is a National Center for Computational Toxicology established by the United States Environmental Protection Agency (EPA) and computational toxicology groups at the US Food and Drug Administration (FDA) in both the drugs and foods divisions.3,8,11,15 Computational approaches are ideally suited to organize, process, and analyze the vast libraries and databases of scientific information and to simulate complex biological phenomena.^7

Because of these continuing advances, todays educational programs in toxicology must be adapted to incorporate a wide range of computational tools to give students the ability to innovate and see a glimpse of the future while learning the basics of the science of toxicology.

 
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