Course · Open to industry

AI- & Data-Driven Drug Design – An Introduction

A one-week, hands-on course at the University of Copenhagen, 9–13 November 2026. Open to pharma and biotech professionals; apply by 30 October.

One week. Five topics. Hands-on every afternoon.

About the course

A one-week introduction to computational and AI-driven drug design at the University of Copenhagen, directed by Professor David Gloriam. Each day covers one topic: databases, structure-based drug design, protein and peptide design, data visualisation, and machine learning. Mornings are lectures; afternoons are hands-on workshops.

Teachers are University of Copenhagen researchers and drug discovery specialists from industry, this year including Lundbeck, Novo Nordisk, Gubra and ZS Discovery.

At a glance

  • When: 9–13 November 2026, 9:00–17:00
  • Where: Universitetsparken 2, 2100 Copenhagen Ø
  • Who: pharma and biotech professionals with a background in pharmacy, chemistry, biology, medicine or similar. PhD enrolment has closed.
  • Fee: DKK 8,040 for industry participants
  • Level: introductory, PhD level (4 ECTS), taught in English
  • Apply: email david.gloriam@sund.ku.dk by Friday 30 October 2026

How to apply

Apply by 30 October 2026

This year’s remaining places are for professionals from the pharmaceutical and biotech industry. A short email to course director Professor David Gloriam at david.gloriam@sund.ku.dk by Friday 30 October 2026 is enough. The button below opens a ready-made email.

Email David Gloriam to apply

Learning objectives

What you will be able to do

  • Find drug, target and disease information in the right online databases and tools
  • Use structure-based drug design to formulate testable hypotheses for optimising small-molecule leads
  • Apply state-of-the-art protein modelling and peptide design methods such as AlphaFold and RoseTTA
  • Analyse and visualise complex datasets
  • Use machine learning for small-molecule and peptide design, and to find the most important features in a drug or target dataset
  • Leave with a taste of each area, a toolbox for your own projects, and a shared language with computational colleagues

Programme

Five days, five topics

Lectures 9–12, lunch, hands-on workshop 13–17. A few speakers are still to be announced; the PDF is the current version. Click the preview to enlarge it.

Course programme, page 1: format and Days 1 to 3
Download the programme (PDF)
  • Mon 9 Nov — Databases. Drug, target and disease databases, an industry talk, and a workshop hunting data for your own project.
  • Tue 10 Nov — Structure-based drug design. The docking toolbox, drug–target interactions, hit-to-lead optimisation from Lundbeck, and a ligand-optimisation competition.
  • Wed 11 Nov — AI/ML tools for peptides and proteins. AlphaFold, Rosetta, ProteinMPNN and BindCraft, case stories from Novo Nordisk and Gubra, and a binder-design workshop.
  • Thu 12 Nov — Data visualisation. Visualisation theory, scripting tools, and a workshop using the AI assistant Claude.
  • Fri 13 Nov — Data analysis using AI/ML. Data preparation, predictive machine learning, an industrial case story from ZS Discovery, and a workshop using Claude.

Speakers

Who teaches

The course director and the teachers named in the programme, with links to their profiles where available. Two industry slots are still to be announced.

Show all 22 speakers Hide the speakers

  • David E. Gloriam Course director

    Professor, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Søren Norge Andreassen

    Academic Research Staff, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Wouter Boomsma

    Professor, Department of Computer Science, University of Copenhagen

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  • Henrik Daver

    Research Scientist, Lundbeck

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  • Kasper Einarson

    Gubra

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  • Aidan Flynn

    Special Consultant, Department of Drug Design and Pharmacology, University of Copenhagen

    Profile

  • Jacob Fredegaard Hansen

    Data Science Specialist, CPDSE, Department of Drug Design and Pharmacology, University of Copenhagen

    ProfileORCIDLinkedInWebsite

  • Kasper Harpsøe

    Research Consultant and Data and Computing Facility Manager, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Alexander S. Hauser

    Associate Professor, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Jascha Henseler

    Research Assistant, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Lars Juhl Jensen

    Director, ZS Discovery; formerly Professor at the Novo Nordisk Foundation Center for Protein Research, University of Copenhagen

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  • Albert J. Kooistra

    Associate Professor, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Pablo Baceiredo Macho

    Guest Researcher, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Jakob Sture Madsen

    PhD Fellow, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Sarah Mittenentzwei

    Data Science Specialist, CPDSE, Department of Public Health, University of Southern Denmark

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  • Rodrigo Alonso Ochoa

    Senior Scientist, Computational Drug Design, Novo Nordisk

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  • Jody Sullivan Pacalon

    Postdoc, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Lykke Pedersen

    Special Consultant, CPDSE, Department of Pharmacy, University of Copenhagen

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  • Javier Sánchez Lorente

    PhD Fellow, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Icaro Ariel Simon

    Postdoc, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Jonas Verhellen

    Postdoc, Department of Drug Design and Pharmacology, University of Copenhagen

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  • Arnault-Quentin Vermillet

    Data Scientist, CPDSE, Department of Drug Design and Pharmacology, University of Copenhagen

    ProfileORCIDLinkedInScholar

Interested? Get in touch by 30 October

Email course director Professor David Gloriam at david.gloriam@sund.ku.dk by Friday 30 October 2026. Read more about him on his KU research profile.

Email David Gloriam