Post by Ardigen

Predicting proteomic profiles from cell morphology is not a trivial problem. At SBI2 2026 in Cambridge (July 7–8), Michal Warchol, PhD, Magdalena Otrocka, PhD, Ada Borowa, PhD, and Sean Melville will be presenting Ardigen's work on integrating multimodal data across cell imaging and small molecule design, and how phenAID connects those layers into a coherent analytical workflow. If you work in image-based drug discovery, two things are worth putting in your calendar: Adriana will lead the educational course "Navigating Deep Learning for High Content Image Analysis" on Day 1 at 10:00 - 11:00. And look for our poster: "Bridging the Phenotype-Proteome Gap: A Multi-Modal AI Framework for Analysis of Cell Painting Images", on using deep learning to predict proteomic profiles from morphological features. We will be on site throughout both days. If you want to discuss multimodal data integration, Cell Painting workflows, or what it takes to move from image features to biological interpretation, find us there. #SBI2 #CellPainting #HighContentImaging #MorphologicalProfiling #ImageBasedDrugDiscovery #AIinLifeSciences