Global Conference on Ai-powered Drug Discovery & Molecular Modeling

Important dates

1. 6 Nov

   Abstract / full paper deadline

   Passed

2. 3–4 Dec

   Conference

   Chicago, Illinois, USA

All deadlines are as published by the organizer. Check the official website for the time zone.

About this conference

Global Conference on Ai-powered Drug Discovery & Molecular Modeling GCAPDDMM, organized by World Research Association for Education and Science, is a leading international conference that connects researchers, engineers, healthcare professionals, academicians, scientists, industry experts, and professionals from around the world. The conference provides a global platform to share groundbreaking research, discuss emerging developments, showcase innovative ideas, and build meaningful professional collaborations. By bringing together diverse academic and professional communities, Global Conference on Ai-powered Drug Discovery & Molecular Modeling GCAPDDMM aims to promote knowledge exchange, interdisciplinary collaboration, innovation, and the advancement of research on a global scale.

Topics and scope

• AI-Driven Drug Discovery
• Molecular Modeling Techniques
• Machine Learning Drug Design
• Deep Learning Applications
• Generative AI Molecules
• Computational Drug Design
• Virtual Screening Methods
• Protein-Ligand Interaction Modeling
• Molecular Docking Techniques
• Molecular Dynamics Simulations
• Quantum Chemistry Applications
• AI-Based QSAR Modeling
• Structure-Based Drug Design
• Ligand-Based Drug Design
• ADMET Prediction Methods
• AI-Driven Drug Repurposing
• AI-Powered Lead Optimization
• Drug-Target Interaction Prediction
• Explainable AI Applications
• AI-Powered Personalized Medicine
• Multiscale Molecular Modeling
• Protein Structure Prediction
• AI-Based Biomolecular Design
• Pharmacophore Modeling Techniques
• Reinforcement Learning Drug Design
• Graph Neural Networks
• Molecular Property Prediction
• AI-Based Synthesis Planning
• Retrosynthetic Analysis Methods
• Molecular Representation Learning
• Protein Folding Prediction
• AI-Driven Biomarker Discovery
• Drug Resistance Prediction
• Multi-Target Drug Design
• De Novo Drug Design
• Natural Language Processing
• Large Language Models
• AI-Powered Drug Screening
• Pharmacokinetic Modeling
• Future Computational Drug Discovery

Call for papers

The call for papers closed on 6 November 2026. For other conferences, see open calls for papers in this field.