19 citations · 19 across the 4 of their papers we have counts for
4 papers
DrugGen 2: A disease-aware language model for enhancing drug discovery
Ali Motahharynia, Mohammadreza Ghaffarzadeh-Esfahani, Mahsa Sheikholeslami +4
Current computational approaches for drug design typically focus on generating molecules conditioned on specific targets or general molecular properties, often neglecting the influ…
AAVGen: Precision Engineering of Adeno-associated Viral Capsids for Renal Selective Targeting
Mohammadreza Ghaffarzadeh-Esfahani, Yousof Gheisari
Adeno-associated viruses (AAVs) are promising vectors for gene therapy, but their native serotypes face limitations in tissue tropism, immune evasion, and production efficiency. En…
DrugReasoner: Interpretable Drug Approval Prediction with a Reasoning-augmented Language Model
Mohammadreza Ghaffarzadeh-Esfahani, Ali Motahharynia, Nahid Yousefian +3
Drug discovery is a complex and resource-intensive process, making early prediction of approval outcomes critical for optimizing research investments. While classical machine learn…
DrugGen: Advancing Drug Discovery with Large Language Models and Reinforcement Learning Feedback
Mahsa Sheikholeslami, Navid Mazrouei, Yousof Gheisari +3
Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials. Deep learning a…