In this study , meta-learning was studied and evaluated on the ability to enhance the performance and outcomes' quality of different models, specifically on potent compounds generation task. Particularly, meta-learning served as a compensation for the lack in comprehensive data; resulting with higher accuracy in Known-Target Compounds (KTCs) predictions compared to other benchmarks.