Drug discovery inspired by African natural products
We are setting up an AI/ML platform for the identification of novel antivirals from African medicinal plants at the University of Buea
Novel antimalarial and antituberculosis treatments at H3D
AI/ML models can support the decision-making process at every stage of the drug discovery cascade
Clinical data analysis at CIDRZ, Zambia
We collaborate with the Centre for Infectious Disease Research in Zambia (CIDRZ) to increase the efficiency of cervical cancer screening amongst women living with HIV in Lusaka.
Open source antimalarials
We have contributed to the Open Source Malaria Consortium, aimed at developing antimalarial drugs following a collaborative approach.
A collaborative approach to antimalarial drug discovery
The Open Source Malaria (OSM) consortium aims to identify new treatments against malaria using a fully Open Science approach. This means all findings are disclosed in real time, promoting scientific collaboration and overcoming intellectual property constraints. We propose a wet-lab/dry-lab cycle of collaboration between OSM and Ersilia where new compounds devised by the computer are probed experimentally and undergo successive rounds of modification to achieve a highly potent antimalarial that can progress to clinical trials.
406,000
Potential antimalarial drug candidates
We used generative AI/ML methods to create a long list of antimalarial drug candidates, based on previous expertise by Open Source Malaria.
1,200
Predicted to be highly active
Then, we evaluated each drug candidate with a high-confidence predictive model for activity against the malaria parasite. We also considered synthetic accessibility of the compounds, as well as drug-like properties.
35
Selected for experiments
Finally, we selected a list of high-confidence compounds for experimental validation by the Open Source Malaria team. Experimental validation coming soon!
Capacity building
We believe the best way to transfer skills is by working side-by-side with our collaborators. Based on these interactions, we create resources focused on the dissemination of computational skills (AI/ML and others) to scientists in different fields.