To ensure the integrity of each model validation and objective evaluation of its performance, the total compound data set (per model) was randomly divided into two main subsets . The 80% of the data was used as the training and validation set, while the remaining 20% was used as the test set, reserved exclusively to evaluate the predictive capacity of each model on data not seen during training. This division was done using a random selection method for a fixed seed to ensure the reproducibility of these results in future studies.