In the initial data preprocessing phase, the MTE accepts the simplified molecular-input line entry system (SMILES) strings of molecules as input and performs data cleaning. Due to unavoidable lab environment differences (e.g., temperature, equipment conditions, etc.), the same chemical compound may have different target values observed, resulting in that the same SMILES string appearing multiple times but for different values or labels of a single drug property. For the duplicated data, we record the mean of the targets and remove duplicated SMILES strings. In addition, any outliers or irregularities are removed in the target data, preventing them from unduly influencing the ML model. Finally, data normalization of the target values is conducted to ensure they are on a consistent scale, preventing biased model training and allowing for better convergence during optimization.