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A Complete Roadmap to Drug Discovery—from Computer Aided Design to the Bench and Bedside

Online training

01 May 2027 - 31 May 2027

Online

Dates: May 2027

Times: TBC

Duration: 3 days, 4 hours per day

Location: Online

Indicative cost: TBC

This three-day online training course offers a comprehensive introduction to the drug discovery pipeline—from computational design to clinical application. Combining expert-led lectures with hands-on practical sessions, the workshop explores key stages of modern drug discovery, including in silico design, protein–ligand interactions, molecular modelling, machine learning approaches, and drug validation. Participants will gain experience using widely adopted tools and open-source resources, while engaging in interactive discussions with academic and industry experts.

This course is designed for graduate students, postdoctoral researchers, and scientists in biology, biochemistry, structural biology, chemistry, bioinformatics, and related disciplines. It is ideal for those looking to build foundational to intermediate expertise in computer-aided drug design and its real-world applications. A basic understanding of molecular science and some familiarity with computational tools is recommended.

By the end of the course, participants will be able to:

  • Understand the fundamental concepts of in silico drug design and delivery, including key components, resources, and interaction mechanisms.
  • Apply mathematical and statistical models, along with relevant algorithms, to analyse and develop drug discovery approaches.
  • Explain how advanced techniques such as artificial intelligence are used to enhance the drug discovery process from design to clinical application.
  • Describe the full translational pathway from initial chemical design to an approved therapeutic.
  • Use computational tools and perform hands-on workflows to design, analyse, and evaluate potential drug molecules.
  • Continue developing your skills independently through applying learned methods, supported by provided datasets, materials, and collaborative discussions.

 

Register your interest

 

 

Key event details

DATE: Saturday, May 1, 2027 - Monday, May 31, 2027
LOCATION: Online
TIME: 12:00 PM - 12:00 PM
EVENT TYPE: Online training