If you’re working in pharma or biotech, you likely rely on artificial intelligence (AI) to help you identify new drug targets or plausible biomarkers for disease within large data sets. Yet AI alone isn't enough. A large proportion of Biomedical data have errors and are unstructured. For AI models to provide reliable insights, the underlying data must be of ‘high quality’, meaning it’s accurate, comprehensive, up-to-date and standardized.  

Jesper Ryge (Idorsia Pharmaceuticals), Alex Jarasch (Neo4j) and Venkatesh Moktali (QIAGEN Digital Insights) come together to showcase the practical applications of high-quality biomedical relationships data from the QIAGEN Biomedical Knowledge Base (BKB) to accelerate, improve and transform research in drug discovery and pharmaceutical development. By applying AI to a gene-disease knowledge graph, they identify promising drug targets and key mechanisms underlying diseases. A brief introduction to Neo4j shows how graph-centric analysis and visualizations facilitate the effective exploration of large knowledge graphs like BKB. This integration of high-quality curated data, AI-driven analysis and advanced visualization provides valuable insights and accelerates the progress of precision medicine.  

In this webinar, you’ll learn how you can:  

  • Build disease interactomes using protein-protein interactions  
  • Identify high-quality drug targets using inferred causal interactions  
  • Choose targets with the least likelihood of adverse outcomes by leveraging the depth of the data in BKB 
  • Formulate plausible hypotheses using state-of-the-art graph visualization  

Don't miss this chance to learn how to supercharge your AI toolbox to transform your drug discovery.

About the speaker
Alexander Jarasch, Ph.D., Technical Consultant Pharma and Life Sciences, EMEA/APAC
Dr. Alexander Jarasch is Technical Consultant for Pharma and Life Sciences at Neo4j - the world's leading graph database.With a background in bioinformatics, his career extends across several industries, including chemistry, biotech, pharma and IT. He has expertise in machine learning and data engineering, combined with his deep domain knowledge in pharma.In his previous roles, Alexander has been the Head of Data and Knowledge Management at the German Center for Diabetes Research (DZD). He has received numerous awards for the innovative use of advanced analytics techniques, such as knowledge graphs, to help combat widespread diseases, such as diabetes.
Venkatesh Moktali, Ph.D., Global Product Manager
QIAGEN Digital Insights
Venkatesh Moktali currently serves as Global Product Manager for QIAGEN Biomedical Knowledge Base from QIAGEN Digital Insights. Dr. Moktali is a seasoned bioinformatics product manager with experience from Mission Bio, Twist and Thermo Fisher. He completed his Ph.D. in 2012 from Penn State University in Bioinformatics.
Jesper Ryge, Ph.D., Senior Data Scientist
Idorsia Pharmaceuticals
Dr. Jesper Ryge currently holds the position of Senior Data Scientist at Idorsia Pharmaceuticals. Dr. Ryge is a biophysicist with a Ph.D. in Neuroscience from the Karolinska Institute (Sweden) and postdoctoral training from the EPFL (Switzerland), where he led his own group in pioneering the use of single-cell transcriptomics to unravel the cellular taxonomy of the mammalian brain. He also held a professorship position in Cellular Neuroscience at the UFRN in Brazil.His current line of research involves data-driven translational science, focusing on the analysis and integration of large ‘omics datasets with single-cell resolution for drug development and biomarker discovery. A recent focus has been on using knowledge graphs for ‘omics integration and interpretation, as well as a tool for predictive modeling to accelerate drug discovery and development. He is particularly passionate about applying novel single-cell technologies to drive personalized medicine and drug discovery in immunology and neuroscience and using large knowledge graphs for comprehensive data integration, interpretation and modeling.
Date of recording:Tuesday, October 3, 2023
Duration:60 minutes
Other Clinical Focus
Bioinformatics - Interpretation
Informatics & Data