The data employed for training models has undergone a rigorous verification process, ensuring their reliability of data and a high degree of relevance. The scrutiny process aligns with the stringent standards set forth by regulatory authorities. We prioritized the accuracy and integrity of the data to provide you with the utmost confidence in the results generated by nQTb models.

nQTb allows for a significant reduction in time-consuming and expensive experiments. The predictive models based on machine learning algorithms implemented in the platform enable quick prediction of human toxicity endpoints. In contrast, the related experimental testing is associated with high research costs, e.g., additional tests for dispersion stability and cytotoxicity of specific nanoforms or the need to provide evidence for cell uptake. Thanks to using nQTb, you get the prediction result in a few moments, incurring only the subscription cost.