Predicting response to venetoclax/azacitidine in AML by determining cytologic variability in AML blasts with generative AI image analysis combined with single-cell transcriptomics (B01)

• Subject Area: Hematology, Oncology ; Medical Informatics and Medical Bioinformatics
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 533056198

Project B01 will analyze variability of AML blasts as determinants of response to venetoclax and azacytidine treatment. Advanced multiomics scRNA-Seq and generative AI- based image analysis will be applied to paired primary samples (diagnosis/relapse) to integrate cellular morphology with molecular analyses in order to predict treatment outcomes and to identify novel VEN/AZA response biomarkers.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1709: Cellular Plasticity in Myeloid Malignancies: From Mechanisms to Therapies
• Applicant Institution: Ruprecht-Karls-Universität Heidelberg
• Project Heads: Maike Janssen; Professor Dr. Jakob Nikolas Kather