Drug Discovery
CH-630 / 2 crédits
Enseignant: Cavalli Andrea
Langue: Anglais
Remark: Next time: December 2025. Timetable via doodle after registration
Frequency
Every year
Summary
The course gives an overview of drug discovery. Computational methods in drug design and discovery, including methods for free energy and residence time, drug-target interactions, pharmacodynamics, pharmacokinetics, and drug delivery,biophysical methods, interaction including ITC, SPR, MST, and NMR.
Content
Basic concepts of drug discovery 1h
Structure-based methods in drug discovery (docking, compound libraries, and virtual screening) 1h
From static to dynamical docking 1h
Ligand-based methods in drug discovery (principal component analysis, support vector machine, machine learning, and QSAR) 2h
Physics-based methods in computational drug discovery (molecular dynamics, enhanced sampling methods, free energy and kinetics, and residence time) 2h
Basic concepts of pharmacodynamics (drug-target recognition and interaction) and pharmacokinetics (DM/PK and toxicology) 1h
Basics concepts of drug delivery 1h
Innovative approaches to drug delivery (micelles, nanoparticles, and vectors) 2h
Biophysical methods in drug discovery 1h
Drug-target interactions utilizing biophysical approaches (SPR, ITC, MST, and NMR) 2h
Note
EuroTeQ course
Next time September 29th 2025
The course materials are recorded videos, which can be accessed at any time after the course starts, so this material is time-independent.There will also be 3 hours of Q&A sessions and 14 hrs of practical work sessions which will be time-dependent. These will be rescheduled sessions as soon as they will be agreed by all the instructors.
Keywords
Drug Discovery, Medicinal Chemistry, Computational Chemistry, Drug Delivery, Biophysics, Drug-target interaction, Free Energy and Residence Time, Pharmacodynamics and Pharmacokinetics
Learning Prerequisites
Required courses
(Introductory knowledge of organic chemistry, biochemistry, genetics, computational sciences, and physics)
Learning Outcomes
By the end of the course, the student must be able to:
- Manage the most common software for docking simulations and molecular dynamics. The basics of Python scripting will also be part of the practical exercises.
- Develop knowledge in drug discovery and development, with a particular focus on computational methods, intelligent drug delivery, and biophysical approaches
Dans les plans d'études
- Nombre de places: 25
- Forme de l'examen: Exposé (session libre)
- Matière examinée: Drug Discovery
- Cours: 14 Heure(s)
- TP: 14 Heure(s)
- Type: optionnel