Intro to Drug Discovery for Computer Scientists

This course has concluded!

Are you a computer science or computer engineering student, or a professional looking to break into the exciting world of healthcare R&D? This course is designed for you! We'll explore opportunities in drug discovery, focusing on the crucial role of computational methods.

We'll begin by examining the history of modern drug discovery, with a strong emphasis on computational approaches like Computer-Aided Drug Discovery (CADD) and Machine Learning (ML).

You'll gain insights into three major challenges driving innovation in drug discovery:

• Protein Structure Prediction (CASP): Understanding how proteins fold is fundamental to drug design.
• Drug Design Resource Grand Challenge (D3R): Exploring and leveraging resources for efficient drug design.
• Protein-Drug Interaction Modeling (SAMPL): Predicting how drugs interact with their targets.

We'll delve deeply into the computational models and software used in drug candidate discovery, drawing on practical experience in this area. You'll also hear directly from industry professionals – computer scientists working in big pharma R&D, biotech companies, and software companies developing cutting-edge drug design tools.

By the end of this course, you'll have a solid foundation in the drug candidate discovery process. You'll be able to identify key challenges and understand current cutting-edge solutions in the field. We'll emphasize that this is a rapidly evolving area, and the goal is to spark your interest in drug discovery and highlight how computer science can make a significant impact.

Ultimately, this course aims to inspire you to pursue a career where your skills can contribute to developing life-saving medications. Building a career in drug discovery is a rewarding and valuable path for computer scientists. We hope this course ignites your passion and encourages you to explore this dynamic and impactful field further.