Скачать или смотреть How AI/ML and In-Silico Drug Design Are Transforming Complex Drug Discovery

How AI/ML and In-Silico Drug Design Are Transforming Complex Drug Discovery
Discover how recent breakthroughs in Artificial Intelligence, Machine Learning, and in-silico drug design are redefining the future of complex drug discovery. This video explores how AI models, big data analytics, and computational simulations are making the process faster, cheaper, and more precise — from target identification to clinical candidate optimization.
What you’ll learn:
• How AI/ML algorithms predict molecular binding, efficacy, and toxicity
• Generative AI for designing novel compounds and optimizing chemical space
• Deep learning in virtual screening, molecular docking, and lead optimization
• Integration of in-silico methods with wet-lab validation for end-to-end R&D
• Use of digital twins, quantum computing, and multi-omics for complex disease modeling
• Key tools and platforms driving the shift: DeepMind AlphaFold, Insilico Medicine, Atomwise, and Schrödinger
• Challenges, ethics, and regulatory aspects of AI-enabled pharma innovation
By combining the power of AI with in-silico modeling, researchers can now design smarter, safer drugs in record time.
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Uncover how molecular docking is revolutionizing drug discovery by predicting how potential drug molecules interact with biological targets. This video explains the science, tools, and AI innovations powering faster, more accurate drug candidate identification — helping researchers design better therapeutics with less trial and error.

What you’ll learn:
• Fundamentals of molecular docking and structure-based drug design
• Key algorithms: rigid vs. flexible docking, scoring functions, and binding affinity prediction
• Leading software & tools — AutoDock, PyRx, Schrödinger Glide, MOE, and DockThor
• Role of AI and machine learning in docking accuracy and virtual screening
• Integration with molecular dynamics, QSAR, and pharmacophore modeling
• Real-world case studies in antiviral, anticancer, and neuropharma research
• Challenges, limitations, and future trends in in silico drug discovery

Learn how computational chemistry and AI are shaping the future of pharmaceuticals.
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