Teaching
BMS 476: Introduction to Artificial Intelligence and Applications in Pharmacy
2 Credits
This course provides an introduction to the basic/core concepts of artificial intelligence and popular machine learning methods. The course will also introduce recent scientific / technological advances in AI-driven applications in different aspects of pharmacy, such as drug design, pharmaceutics, clinical trials, pharmacovigilance/pharmaceoepidemiology, healthcare policy, clinical practice & patient care, and other related health areas.
Fall Semester 2024
Medc 711: Intro to Computer-Aided Drug Design
3 Credits
Modern molecular modeling methods and techniques as they pertain to structural-based drug design, including protein sequence analysis, protein structure prediction, homology modeling, molecular docking, virtual screening, and molecular dynamics simulation.
Spring Semester 2025, Fall Semester 2022, and 2020
Medc 712: Quantitative Structure-Activity Relation in Drug Design.
3 Credits
The basics and application of Quantitative Structure-Activity Relation (QSAR and 3D-QSAR), and other related ligand-based drug design computational approaches, such as ADMET prediction, pharmacophore modeling, as well as an introduction to multiple machine learning methods in drug design.
Fall Semester 2021 and 2023
