The digital evolution in toxicology: pioneering computational education for emerging challenges

Area of Science:

• Toxicology
• Computational Science
• Education

Background:

• Ethical concerns regarding animal testing are driving the integration of computational methods in toxicology.
• Advancements in biotechnology and data analysis further support the shift towards computational toxicology.
• The Toxicology in the 21st century (Tox21) initiative exemplifies this evolving landscape.

Purpose of the Study:

• To examine the evolution and significance of computational toxicology in education.
• To contrast computational toxicology with traditional methods, highlighting the benefits of new approaches.
• To emphasize the importance of integrating computational toxicology into academic curricula.

Main Methods:

• Review of the Toxicology in the 21st century (Tox21) initiative.
• Comparative analysis of traditional versus computational toxicology methodologies.
• Identification of effective teaching content, software tools, and online resources.
• Exploration of challenges and prospects in computational toxicology education.

Main Results:

• Computational toxicology offers new perspectives and overcomes limitations of traditional methods.
• Integration into curricula enhances students' problem-solving, data analysis, and innovation skills.
• Effective teaching strategies include case studies, software, online resources, and literature.

Conclusions:

• Computational toxicology is crucial for modern toxicology education.
• Curricula must adapt to equip students with skills for contemporary chemical safety challenges.
• Further advancements in teaching methods and resources are needed to fully realize the potential of computational toxicology education.