Accelerating drug discovery with a new class of explainable AI

Science for Lunch with Abzu
Abzu is a specialist drug discovery consultancy that uses explainable machine learning to reveal deeper insight within drug discovery. Unlike the dominant neural networks, our approach is able to explain our predictions. At our lunch talk, we will be presenting a case study of our partnership with Peptomyc, a Spanish university spin-out.
Built on over 20 years’ research led by Laura Soucek, Omomyc (OMO-103) is a therapeutic mini-protein which targets and inhibits the Myc oncogene. Until Peptomyc’s successful clinical trial with OMO-103, Myc was thought to be undruggable. Peptomyc used the QLattice and Abzu’s expertise in patient stratification to reveal early predictive response-biomarkers to treatment with OMO-103 in metastatic patients. The analysis by the QLattice was conducted on a very small clinical trial of 22 patients.
“Partnering with Abzu and using the QLattice increased our ability to really take advantage of all our clinical results to find unexpected and extremely valuable data that we could have missed otherwise,” says Laura Soucek, CEO of Peptomyc.
3 Takeaways from the lunch meeting
- Disease understanding
- Biomarkers discovery
- Patient stratification in clinical trials
Speakers
Marco Salvatore, Head of Target and Biomarker Discovery.
Marco holds a PhD in Bioinformatics from Stockholm University where he specialized in Machine Learning for Life Science. He is an accomplished professional with a strong focus on precision medicine and biomarkers discovery. At Abzu, Marco works at the interface between technology and customers, leading the application of Abzu technology in a variety of bioinformatics projects, from target identification to biomarker discovery and genomic medicine. Family first for Marco, then motorbikes and football.
Meera Machado, Data Scientist.
Meera holds a PhD in Physics from the University of Copenhagen in High Energy Physics, specializing in Heavy Ions. At Abzu, Meera explores how machine learning is applied in physics and science. She reads web comics, devours podcasts, pole dances, and is a secretly competitive cyclist.
Company website: https://www.abzu.ai/
Information
- When: to
- Where: Bistro Merge, The Spark building, Medicon Village, Scheeletorget 1, Lund
- Organizer: Medicon Village in co-operation with Abzu
- Language: English
Registration
Please register no later than Monday 9 October 2023
Contact information
- Lottie Norrsén
- lottie.norrsen@mediconvillage.se