Aitia has developed a causal AI platform (REFS) that uses human multiomic data to create Gemini Digital Twins, or computational models of human diseases.
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder marked by progressive motor neurons degeneration, muscle weakness, and respiratory failure, with a median survival of 2-5 years after symptom onset. Few genetics causes have been identified for the disease, and the vast majority are of idiopathic origin. Conventional approaches in ALS research do not fully explain disease variability, nor consistently yield actionable therapeutic strategies.
To address this gap, Aitia proposes to build ALS Digital Twins leveraging the REFS technology and the multi-omics data in the UK Biobank to enable a causal, systematic understanding of ALS disease mechanisms and discover novel drug targets and biomarkers of drug response. Specifically, Aitia plans to use the ALS Digital Twins for:
1. Novel Target & Drug Discovery – Simulate gene and protein knockdowns to discover, prioritize and cross validate novel causal targets in ALS that drive clinical outcomes.
2. Translational – Simulate and explore both known and novel biology in the context of pathways and networks connected to genes, proteins, clinical outcomes, and other variables of relevance to novel targets discovered from the Digital Twins, including drug target prioritization, combination therapy discovery and optimization, and new prognostic biomarker and drug response biomarker discovery.
3. Drug & Trial Simulation – In silico!simulations will be conducted to determine and confirm mechanisms of drug efficacy and to discover drivers of patient response/non-response for patient stratification for clinical trial design.