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Fudan University

Artificial Intelligence Drug Design

Fudan University via XuetangX

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Overview

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Artificial Intelligence in Drug Design is a cutting-edge 2-credit course developed by the School of Pharmaceutical Sciences at Fudan University, integrating AI technology across the entire drug research and development workflow. The course is led by Professor Wei Fu and features joint instruction from several professors within the School of Pharmaceutical Sciences as well as industry experts from Insilico Medicine.

You will systematically learn key technologies such as AI-driven target discovery, AlphaFold protein structure prediction, molecular generation, and ADMET property prediction. Through practical case studies and hands-on computer sessions, you will gain firsthand experience operating AI-powered drug design tools.

This course is ideal for students with a pharmaceutical background seeking to rapidly acquire core competencies in AI-empowered drug discovery, fostering interdisciplinary innovation capabilities for the future.


Syllabus

  • Chapter 0：How to Learn This Lession
    • 0.1 HOW to Learn AIDD
    • 0.2 Course Outcomes
    • 0.3 Knowledge Graph
  • Chapter 1：Introduction
    • 1.1 AI in Drug Discovery（1）
    • 1.2 AI in Drug Discovery（2）
    • 1.3 Development of AI（1）
    • 1.4 Development of AI（2）
    • 1.5 AIDD & CADD-1（1）
    • 1.6 AIDD & CADD-1（2）
    • 1.7 AIDD & CADD-2（1）
    • 1.8 AIDD & CADD-2（2）
  • Chapter 2：The Application of AI in Drug Design
    • 2.1 AI Methods in Drug Discovery
    • 2.2 AI Applications in Drug Discovery-1
    • 2.3 AI Applications in Drug Discovery-2
    • 2.4 AI Applications in Drug Discovery-3
    • 2.5 AI Applications in Drug Discovery-4
    • 2.6 AI Drug Discovery Industry's Challenges
  • Chapter 3：Introductin to Artificial Intelligence
    • 3.1 Convolutional Neural Network
    • 3.2 Graph Neural Network
  • Chapter 4：AI-Based Drug Target Identification
    • 4.1 Concept of Drug Target
    • 4.2 Drug Target Identification Technologies
    • 4.3 Data Sources for Drug Target Identification
    • 4.4 AI-Based Target Identification & Application Scenarios
  • Chapter 5：Protein Structure Prediction and Design
    • 5.1 Protein Structure Prediction
    • 5.2 Traditional Protein Design
    • 5.3 AI for Protein Design
    • 5.4 AlphaFold
  • Chapter 6：AI-Assisted Drug Structure Design
    • 6.1 Basic Principles of Drug Design
    • 6.2 Direct Drug Design
    • 6.3 Indirect Drug Design
    • 6.4 Molecular Characterization Methods
    • 6.5 Introduction to AI-powered Molecular Generation Methods
    • 6.6 Selection, Training, and Optimization of AI Models and Related Challenges-1
    • 6.7 Selection, Training, and Optimization of AI Models and Related Challenges-2
  • Chapter 7：Design of artificial intelligence assisted drug delivery system
    • 7.1 Why use artificial intelligence to assist in the design of drug delivery systems
    • 7.2 AI-assisted design of DDS formulation
    • 7.3 AI-assisted screening of new delivery materials
    • 7.4 AI in assisting DDS delivery mechanisms
  • Chapter 8：Applications of Artificial Intelligence in Molecular Generation and Retrosynthetic Analysis
    • 8.1 Overview of Molecular Generation
    • 8.2 Molecular Representation I
    • 8.3 Molecular Representation II
    • 8.4 Molecular Generation I
    • 8.5 Molecular Generation II
    • 8.6 Overview of Retrosynthetic Analysis
    • 8.7 Template-Based Retrosynthetic Analysis
    • 8.8 Template-Free Retrosynthetic Analysis
  • Chapter 9：AI-Driven Drug Property Prediction
    • 9.1 Drug-Target Binding Affinity
    • 9.2 Computational Methods for Drug-Target Binding Affinity
    • 9.3 Concept of Druggability
    • 9.4 ADMET Prediction
  • Chapter 10：AI in Drug Research and Development
    • 10.1 Introduction to AI in Drug Discovery and Target Identification
    • 10.2 Protein Structure Prediction and AlphaFold Revolution
    • 10.3 Deep Learning Architectures for Drug Discovery and Applications
    • 10.4 Generative Deep-Learning Models for Drug and Biologics Design
  • Chapter 11：Application of AI in Drug Discovery
    • 11.1 Application of AI in Drug Discovery
    • 11.2 Case study Generative AI Empowered Drug Discovery for Inflammatory Bowel Disease (IBD)
  • Final-examination

    Taught by

    Wei Fu, Wei Li, Wei Lu, Yifei Qi, and Yan Li

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