Comprehensive learning platform for drug discovery - from beginner basics to expert-level systems biology
Master the complete drug discovery pipeline with curated video tutorials, hands-on exercises, and real-world case studies. Learn at your own pace from beginner to expert level.
10
50+
100+
200+
Foundation course covering the drug discovery pipeline from target identification to clinical trials
Drug Discovery and Development Process
Channel: Armando Hasudungan
Watch on YouTubeStudy the development timeline of 5 blockbuster drugs from discovery to market
Evaluate potential drug targets for Type 2 Diabetes using disease biology
Introduction to computer-aided drug design including molecular docking and pharmacophore modeling
Learn molecular docking by reproducing the aspirin-COX-2 crystal structure
Create a pharmacophore model from known kinase inhibitors
Prerequisites: Basic chemistry, Introduction to Drug Discovery
Apply genomics to identify drug targets, understand disease mechanisms, and predict drug response
Identify genetic loci associated with Alzheimer's disease risk from GWAS data
Analyze TCGA data to identify actionable mutations in lung cancer
Predict warfarin dosing based on CYP2C9 and VKORC1 genotypes
Prerequisites: Genetics basics, Molecular biology
Apply deep learning and AI to predict drug properties, design molecules, and optimize lead compounds
Build a random forest model to predict aqueous solubility from molecular descriptors
Train a graph convolutional network to predict kinase inhibitor activity
Use a variational autoencoder (VAE) to generate novel drug-like molecules
Prerequisites: Python programming, Machine learning basics, Chemistry fundamentals
Use proteomics to validate drug targets, understand mechanisms of action, and identify biomarkers
Identify differentially expressed proteins in cancer vs normal tissue
Use thermal proteome profiling to measure target engagement of a kinase inhibitor
Prerequisites: Biochemistry, Protein structure basics
Analyze RNA-seq data to identify dysregulated genes, pathways, and potential drug targets
Find differentially expressed genes in breast cancer RNA-seq data
Identify enriched pathways in drug-treated vs control samples
Analyze single-cell RNA-seq to identify cell types in tumor microenvironment
Prerequisites: Molecular biology, Statistics basics
Design clinical trials, analyze patient data, and navigate regulatory pathways for drug approval
Create a trial protocol for testing a new cancer immunotherapy
Perform Kaplan-Meier analysis on cancer clinical trial outcomes
Review a real NDA submission and identify key components
Prerequisites: Statistics, Pharmacology, Drug discovery basics
Use protein structures from X-ray, cryo-EM, and AlphaFold for structure-based drug design
Examine the binding mode of FDA-approved drugs in their target proteins
Use AlphaFold-predicted structures to design inhibitors for a novel target
Identify fragment hits and grow them into lead compounds using structure
Prerequisites: Biochemistry, Protein structure basics
Apply systems-level thinking to drug discovery using network analysis and multi-omics integration
Introduction to Systems Biology
Channel: Systems Biology Ireland
Watch on YouTubeConstruct a protein interaction network for a disease and identify hub proteins
Use network proximity to identify repurposing candidates for COVID-19
Integrate genomics, transcriptomics, and proteomics for cancer subtype classification
Prerequisites: Omics sciences, Bioinformatics, Statistics
Apply metabolomics to discover biomarkers, understand drug metabolism, and identify off-target effects
Identify unknown metabolites from LC-MS/MS data using spectral libraries
Perform metabolic pathway analysis on diabetes patient samples
Prerequisites: Biochemistry, Analytical chemistry basics