We successfully concluded the second edition of our capacity-building workshop focused on applying AI in drug discovery. Participants gained valuable insights into:

- Data curation from databases like ChEMBL and the African Natural Products Database (ANPDB)
- Leveraging the Ersilia model hub
- Machine learning algorithms
- Assessing model performance and interpreting outputs

We extend our sincere gratitude to Gemma Turon and Miquel Duran-Frigola from the Ersilia Open Source Initiative, for their invaluable contributions and dedication to making this workshop a huge success.

Two of our PhD candidates recently embarked on research visits to prestigious German institutions.

Miss Solange Ayukncha travelled to Martin Luther University Halle-Wittenberg to conduct research on the synthesis of pseudo-natural products with potential latency-reversing activity against Histone Deacetylase 1 (HDAC1).

Mr. Jude Betow completed a six-week internship at the University of Münster where he gained valuable experience in cheminformatics and artificial intelligence applied to drug discovery.

These experiences have significantly enhanced their scientific knowledge and provided them with a deeper understanding of cutting-edge methodologies in drug discovery and development.

We had a 2-weeks hands-on training on AI/ML methods for drug discovery in parallel with the Biomedical Technicians Training (BTT), followed by a 3 days drug discovery hybrid workshop under the theme “Artificial Intelligence, Computational and Medicinal Chemistry-based Approaches for Antiviral Drug Discovery”. The workshop gathered experts from the fields of natural products chemistry, chemical synthesis, nanotechnology and AI/ML, who gave informative and enriching talks on antiviral research.