Gemini Digital Twins are computational representations of disease that capture genetic and molecular interactions that causally drive clinical and physiological outcomes.
Simulate genetic knockdowns in the Gemini Digital Twins to discover and cross validate novel drug targets that are causally linked to clinical endpoints
Genetically and biologically validate novel drug targets to add additional evidence to the novel targets through conducting a range of wet lab assays
Identify and advance molecular entities into development candidates and IND-enabling studies
Continuously apply Gemini Digital Twins to inform translational medicine approach, identify specific patient populations, and optimize clinical trial designs
Significantly increased probability of success
Deriving insights from Human datasets; by starting with human data, Aitia eliminates the need to use outdated model systems that are poor predictors of human biology
Discovering targets at a speed and scale that is not possible through high-throughput experiments or other platforms; Aitia evaluates the impact of trillions of parameters on clinical outcomes in each of trillions of simulation experiments
Identifying targets causally linked to clinical outcomes decades before anyone else; Aitia runs counter factual “in silico” experiments testing hypotheses across millions of patient-data derived Digital Twins
Starting with biomarkers and targets tied to specific patient populations and identifying responders vs non-responders early in development
