AI in Drug Discovery & Development
About Course
AI in Drug Discovery & Development
Pharmaceutical industries worldwide are increasingly using AI to accelerate drug discovery, development, and clinical trials. Traditional methods take years and cost billions, but AI helps reduce both time and expense. This course will expose B. Pharma students to how machine learning, bioinformatics, and predictive modeling are transforming pharma R&D, helping them align with the skills needed by the industry.
1. Objectives of the Program
The program aims to:
- Introduce students to AI-driven drug discovery processes.
- Familiarize them with tools for molecular modeling, target identification, and compound screening.
- Explain how AI is applied in clinical trials and regulatory approval.
- Encourage students to explore AI-related career roles in pharma R&D.
2. Key Program Features
- Duration: 5 days (5 online sessions).
- Learning Mode: Online lectures, and online digital assignments.
3. Program Structure (5 Day) – 1 online session per day
|
Module |
Key Topics |
|
Module 1: Introduction to AI in Pharma R&D |
· Role of AI in modern pharmaceutical sciences · Overview of AI tools in drug discovery |
|
Module 2: Target Identification & Molecular Modeling |
· AI in genomics and protein structure prediction (AlphaFold example) · Virtual screening of drug molecules |
|
Module 3: AI in Preclinical & Clinical Trials |
· Patient data analysis using AI · Predicting drug efficacy & toxicity |
|
Module 4: AI in Regulatory & Pharmacovigilance |
· Safety monitoring with AI · AI for adverse event prediction and drug recalls |
|
Module 5: Case Studies & Group Activity |
· Examples: Pfizer-BioNTech (COVID vaccine), Novartis, etc. · Mini-project: “Design an AI-based solution for faster drug development” |
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