computational cell biology in oncology, which pertains to the analysis of multiple cellular components – such as tubulin, actin, focal adhesions, and the endoplasmic reticulum – to evaluate with high precision the activity of drug regimens. The computational assays we are proposing could successfully be applied to evaluate treatment strategies for any human organ. Our aims are to elucidate mechanisms and discover biomarkers of drug resistance, and provide technology enabling innovative drug development and the selection of drug regimens that overcome drug resistance.

Quantitative cell biological profiling of subcellular interactions in disease is required to understand the mechanisms of pathogenesis and elucidate the mechanisms of drug action. During pathogenesis, or due to drug treatment in disease, cells change their intracellular organization, rearrange their internal components as they grow, divide, andadapt mechanically to a hostile environment. These functions depend on proteins, cytoskeletal filaments, and focal adhesion complexes, which provide the cell shape and its capacity for directed movement. The integration of measurements of intracellular dynamics and the contribution of multiple genetic pathways in degenerative diseases is vital for the development of biomarkers for the early detection of pathogenesis and therapy efficacy. We are developing biological cell image analysis software, designed to run on personal computers, smartphones and smart glasses, for resource-constrained computing and a functional screening of novel therapeutics as well as high-content analysis in clinical medicine.