Capstone research project focused on leveraging machine learning for drug discovery. This approach can help speed up early-stage research and reduce the need for costly lab experiments. In the final year of my Honours Computer Science degree, I collaborated with industry partner Living in Silico to develop a tool that facilitates the deployment of RNNs (Recurrent Neural Networks). This can be useful in predicting preclinical models and curing specific diseases. As artificial intelligence and machine learning technologies progress, using SMILES (Simplified Molecular Input Line Entry System) strings offers significant potential for accelerating drug discovery, advancing health bioinformatics, and enhancing outcomes in human health.