Executive Development Programme in Computational Methods for Drug Discovery
-- ViewingNowThe Executive Development Programme in Computational Methods for Drug Discovery is a certificate course designed to equip learners with essential skills in drug discovery. This program emphasizes the importance of computational methods in modern drug discovery, which are used to predict drug behavior, identify potential drug candidates, and streamline the drug development process.
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โข Introduction to Computational Methods in Drug Discovery: Overview of computational methods, drug discovery process, and their integration. Understanding of structure-based and ligand-based drug design, molecular dynamics simulations, and QSAR models.
โข Data Analysis and Visualization: Data manipulation tools, data visualization techniques, and statistical analysis for large datasets in drug discovery. Hands-on experience with popular data analysis tools and libraries.
โข Machine Learning and AI in Drug Discovery: Machine learning techniques, including supervised and unsupervised learning algorithms, and their applications in drug discovery. Overview of deep learning and AI methods and their role in drug discovery.
โข Molecular Modeling and Simulation: Molecular mechanics, molecular dynamics simulations, and free energy calculations for drug discovery. Hands-on experience with popular molecular modeling software and simulation tools.
โข Quantitative Structure-Activity Relationship (QSAR): Design and validation of QSAR models, including feature selection, model training, and model evaluation. Hands-on experience with popular QSAR tools and libraries.
โข Pharmacokinetics and Pharmacodynamics Simulations: Overview of pharmacokinetics and pharmacodynamics, including absorption, distribution, metabolism, and excretion (ADME) models. Hands-on experience with popular ADME tools and libraries.
โข Genomics and Next-Generation Sequencing: Overview of genomics, next-generation sequencing, and their applications in drug discovery. Hands-on experience with popular genomics tools and libraries.
โข Regulatory and Ethical Considerations in Computational Drug Discovery: Overview of regulatory and ethical considerations in computational drug discovery, including guidelines, regulations, and ethical considerations. Hands-on experience with popular regulatory and ethical frameworks.
โข Case Studies in Computational Drug Discovery: Real-world case studies and examples of computational drug discovery, including success stories and lessons learned. Hands-on experience with popular case studies and
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