Mind the Gap! A Journey towards Computational Toxicology

Area of Science:

• Computational toxicology
• Drug discovery and development
• In silico modeling

Background:

• Computational methods are advancing toxicology with target-specific models.
• In silico models present both advantages (cost-effectiveness) and disadvantages (potential for misleading results).
• Safety/toxicity studies are crucial for chemical prioritization in industries, especially pharmaceuticals.

Purpose of the Study:

• To review scientific and regulatory recommendations for deriving and applying computational models.
• To examine the integration of computational toxicology within drug discovery and development.
• To provide a realistic perspective on the capabilities and limitations of current in silico approaches.

Main Methods:

• Review of existing scientific literature and regulatory guidelines.
• Analysis of the strengths and weaknesses of in silico models.
• Exploration of the relationship between computational toxicology and pharmaceutical R&D.

Main Results:

• In silico models are valuable, cost-effective alternatives to traditional toxicity testing.
• Uncritical use of computational models can lead to inaccurate predictions.
• A balanced view is necessary, acknowledging both the potential and limitations of these methods.

Conclusions:

• Adherence to scientific and regulatory standards is essential for the reliable development and application of computational toxicology models.
• Computational toxicology plays a key role in modern drug discovery and development pipelines.
• Realistic expectations and careful validation are crucial for harnessing the full potential of in silico methods in safety assessment.