AI in Drug Discovery – AlphaFold3 & Virtual Screening

What you'll learn
The Career Pivoter - Joining the AI Drug Discovery
Academic Researchers
Digital Transformation Leads
Future Bio-Entrepreneurs
Requirements
Fundamental Biology & Chemistry
General AI/ML Knowledge
Scientific Curiosity
Description
Unlock the Future of Drugs Discovery with AI: A Comprehensive to Molecular Design and Scalable AI.The pharmaceutical industry is at a breaking point. With drug development costs exceeding $2 billion and success rates hovering below 10%, the traditional "trial and error" method is no longer sustainable. AI-Driven Drug Discovery and Manufacturing is the solution the industry has been waiting for. This course provides a complete, end-to-end blueprint for using Artificial Intelligence to revolutionize how we find, design, and produce life-saving medicines.We begin by diving into the AlphaFold Revolution. You will learn how to leverage AlphaFold 3 to solve the protein-folding problem, predicting complex 3D structures and protein-protein interactions with unprecedented accuracy. From there, you will master Structure-Based Drug Design (SBDD), moving beyond simple docking to AI-enhanced scoring functions that predict binding affinity more reliably than ever before.What sets this course apart is its holistic approach. We don't stop at discovery; we bridge the gap between the lab and the factory. You will explore:Generative AI: Using VAEs and GANs to "invent" novel molecules with optimized properties.Predictive ADMET: Reducing clinical failure by predicting toxicity and metabolism in silico.Case Studies: Real-world breakdowns of AI-designed drugs like Halicin and Rentosertib.AI in Manufacturing: Utilizing Machine Learning for Quality by Design (QbD) and optimizing the chemical synthesis of the Active Pharmaceutical Ingredient (API).Whether you are a biologist looking to master computational tools, a data scientist pivoting into biotech, or a manufacturing professional optimizing formulations, this course provides the hands-on exercises and theoretical depth needed to excel in the "Self-Driving Lab" era.Join us to gain the technical expertise required to shorten discovery timelines from years to months and play a pivotal role in the next generation of pharmacology.
Who this course is for
Bioinformaticians & Computational Chemists: Professionals looking to upgrade their toolkit with Generative AI, AlphaFold 3 workflows, and automated retrosynthesis.
Pharmaceutical Scientists & Pharmacologists: Traditional "wet-lab" researchers who want to understand the "dry-lab" AI revolution to better collaborate with computational teams or transition into In Silico roles.
Data Scientists & AI Engineers: Tech professionals looking to pivot into the high-impact field of HealthTech and Drug Discovery by learning how to apply Deep Learning to biological data.
Graduate Students (Masters/PhD): Students in Pharmacy, Biotech, or Computer Science seeking a practical, industry-aligned supplement to their academic studies.
Biotech Entrepreneurs & Product Managers: Non-technical leaders who need to understand the realistic capabilities (and limitations) of AI to lead drug discovery startups or innovation teams.
Process Engineers & Manufacturing Specialists: Those interested in the final "API" stage—how AI optimizes chemical synthesis, formulation, and Quality by Design (QbD) in a factory setting.
Homepage
https://www.udemy.com/course/ai-in-drug-discovery-alphafold3-feras-naser/

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hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part1.rar
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hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part3.rar
hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part4.rar
hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part5.rar

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hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part3.rar.html
hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part4.rar.html
hjrlx.AI.in.Drug.Discovery..AlphaFold3..Virtual.Screening.part5.rar.html