Spatial drug activity contexts, or DACs, capture how the various spatial organisations of the products of our genome cause drugs to have variable effects. To measure all DACs relevant for drug discovery, Apricot has developed a unique platform based on 17 years of pioneering R&D in the field of image-based systems biology. This high-throughput platform collects information from multiple spatial scales to train machine learning models that predict cellular responses to drugs with unprecedented accuracy. Apricot is generating a unique data resource in which multi-scale DACs are profiled for compounds covering a highly diverse chemical space with the aim to uncover generalizable predictive rules that connect molecular-scale predictions of compound-target interactions to higher-scale cellular responses and treatment outcomes. This will re-define drug discovery and personalized medicine approaches in the next decade.
of many single cells
Cells are in different states that cause pathways to have different responses.
Single-cell DACs reveal how the cellular state influences the downstream effects of drugs on various pathways.
within multicellular assemblies
The surroundings of cells vary a lot, and this causes cells to be in different states.
Multicellular DACs define how drug responses are conditioned by the cellular microenvironment and tissue ecosystem.