Webinar Recording Available All Levels Dr. Omics

Unlocking the Potential of Computer-Aided Drug Design (CADD): Bridging Theory and Practice

Master AI-driven drug discovery frameworks to design next-generation therapeutics. Bridge computational chemical theory and practical laboratory application in life sciences.

  • 4.0/5
  • English
  • Updated Aug 2026
Unlocking the Potential of Computer-Aided Drug Design (CADD): Bridging Theory and Practice

About this course

Welcome to the forefront of pharmaceutical innovation, where artificial intelligence meets modern medicine. This intensive course bridges the gap between theoretical chemistry and actionable laboratory practice in Computer-Aided Drug Design (CADD). As shown in 18.png, this specialized online international program is tailored for the evolving life sciences landscape. You will explore how generative AI models, deep learning, and predictive machine learning algorithms accelerate the traditional drug discovery timeline. Throughout this curriculum, participants will dive deep into virtual screening workflows, lead optimization, and molecular docking algorithms. By utilizing advanced software tools, you will learn to predict pharmacological properties and simulate complex molecular interactions with precision. This training empowers you to bypass expensive wet-lab trial-and-error by predicting target-ligand affinities computationally. Ultimately, this course provides the comprehensive theoretical foundation and hands-on software expertise needed to build a highly competitive career in AI-driven biotechnology.

What you will learn

Core fundamentals of Computer-Aided Drug Design (CADD) and its real-world industrial applications.
How to implement artificial intelligence and machine learning algorithms for high-throughput screening.
Practical methods for molecular docking, receptor-ligand interaction analysis, and structure-based design.
Techniques for predicting absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles using AI tools.
Advanced strategies to identify, optimize, and refine lead drug compounds completely in silico.

Skills you will gain

Chemoinformatics Docking Virtual-Screening AI-Modeling ADMET-Prediction Ligand-Design Deep-Learning Simulation
Certification

Available

Issued by Dr. Omics

Course curriculum

1 module

  • Introduction to pharmaceutical pipelines and the transformative role of AI in CADD.
  • Target identification, protein preparation, and structural bioinformatics databases.
  • Ligand-based drug design, quantitative structure-activity relationship (QSAR) modeling, and chemical space mapping.
  • Structure-based drug design, molecular docking protocols, and interaction score calculation.
  • Virtual screening workflows using artificial intelligence and machine learning filters.
  • ADMET profiling, pharmacokinetic optimization, and translational research frameworks.

What you need to start

  • A basic background in biochemistry, organic chemistry, or general life sciences.
  • No prior programming experience or deep computational knowledge is required; all primary CADD software tools will be taught step-by-step.

Who this course is for

  • Pharmacy & Pharmacology Professionals: Chemists and pharmacologists wanting to integrate AI tools into traditional drug formulation pipelines.
  • Life Science Researchers: Biotech, bioinformatics, and biochemistry scholars looking to complement wet-lab assays with powerful dry-lab computation.
  • Aspiring AI Bio-Engineers: Data scientists eager to apply specialized computational intelligence to the pharmaceutical sector.
INR

₹199

₹999 80% off
USD

$5

$20 75% off

Indian learners pay in INR; international learners are billed in USD.

This course includes
  • Format Recording Available
  • Level All Levels
  • Language English
  • Modules 1
  • Access 3 months
  • Certificate Yes
  • Provider Dr. Omics
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