Despite its advantages, in silico toxicology faces several challenges:
Data Quality: The accuracy of in silico predictions heavily depends on the quality and completeness of the input data. Inaccurate or incomplete data can lead to erroneous predictions. Complexity of Biological Systems: Biological systems are highly complex, and modeling their interactions accurately is challenging. Simplified models may not capture all relevant factors, leading to potential inaccuracies. Validation: In silico models must be validated against experimental data to ensure their reliability. This validation process can be time-consuming and requires access to high-quality experimental results.
