The translation layer between causal human biology and decisions.

Does this target affect disease progression, or just susceptibility?

Applies novel longitudinal methods to distinguish genes that cause disease incidence from those that drive progression once established. That distinction changes the patient population and clinical strategy.

Which of these validated targets should we prioritize?

Allows direct comparison of the anticipated effect size of pharmacologically manipulating validated targets using apples-to-apples comparisons. Also enables prediction of whether inhibition or activation is required.

Are there additive, synergistic or redundant effects when influencing multiple targets?

Uses advanced human causal biology methods to pick which combination of targets will have therapeutic benefit beyond standard of care.

Which gene at this GWAS locus actually drives disease?

Uses an ML algorithm to combine various genomics data sets to assign a probability of causality to each gene at a GWAS locus, yeilding a easily interpretable method prioritize targets across the human genome.