Join us for an insightful webinar on leveraging machine learning (ML) to tackle the challenges of antibiotic drug discovery amidst rising antimicrobial resistance (AMR). Discover how we developed the AntiMicrobial-KG, a comprehensive knowledge graph of in-vitro antibacterial assay data, and used it to train ML models for identifying potential antimicrobial compounds. Learn how our optimised Random Forest model achieved 75.9% accuracy and was successfully applied to predict active compounds in the EU-OpenScreen and Enamine libraries, offering a promising pathway to accelerate AMR drug discovery.
Time: February 13, 15:00 – 16:30 CET
Speakers:
- Yojana Gadiya, Data Scientist, Fraunhofer ITMP ScreeningPort
- Andrea Zaliani, Senior Data Scientist, Fraunhofer ITMP ScreeningPort
- Dr. Philip Gribbon, Head Discovery Research, Fraunhofer ITMP ScreeningPort
Moderator: Frederik Deroose, CEO, Connecting Pharma
Register for the webinar by clicking this link or pasting https://limesurvey.biocom.de/index.php/635919?lang=en in the browser.
