IN-VITRO-TO-IN-SILICO TRANSLATION BY µIND ENGINE
After the cellular device is being exposed, and 10-40 subcellular and cellular responses monitored resulting in 3 000 – 10 000 images acquired per sample per day, automated quantification firstly translates the images into up to 40 000 time-correlations per sample (exposure) per day using predetermined (material-agnostic) algorithms searching for evolution of surfaces, colocalizations, morphology and dynamics.
Mode-of-action (MoA) Discovery
Then, the correlations are translated into local interaction couplings between the in-vitro-observed functional units, defining Mode-of-Action (MoA) and the corresponding equations of motion of a local part (more than 90%) of a digital twin of early disease evolution. The remaining systemic (local-to-system coupling) part (less than 10%) of a digital twin of early disease evolution is derived from calibration to more than 2000 animal experiments.
The remaining systemic (local-to-system coupling) part (less than 10%) of a digital twin of early disease evolution is derived from calibration to more than 2000 animal experiments.
Long-term disease evolution in a digital twin
Finally, automated prediction of disease evolution for up to 12 months beyond the exposure and duration of the in vitro monitoring is calculated for the selected dose by propagating the initial states within the given digital twin.
