We start with patients' RNA...
Diseases aren't all the same and can change. Unlike DNA, RNA tells us exactly what's going on in the disease in that patient at that time. But rather than look at any one gene, our proprietary model of human health allows us to uncover network-level effects.
...and compute proprietary XIPcodes to define each patient's molecular signature
XIPcodes (Cross-system Interaction Pathway codes) define each disease based on molecular signatures and therapeutic response pathways, stratifying patients into therapeutic response groups.
We then predict drugs that restore disease XIPcodes back to health...
Using our proprietary Bayesian network of 12,000+ gene interactions and database of 40,000+ compounds calculated from ground-thruth datasets, we identify drugs that restore health without needing a target.
...identify effective drugs using our SquishyWare tadpole screen...
In just 3 weeks, we generate in vivo disease models using CRISPR editing and screen for clinically-relevant metrics.
...use effective drugs to uncover therapeutically-meaningful targets...
All drugs impact hundreds of proteins in a cell, but typicaly most of these proteins are ignored as "off targets". We use effective drugs as "bait" to uncover these overlooked proteins that matter to a particular disease.
...and quickly test drugs in patients to derisk targets.
We derisk new drug targets by using existing drugs to validate targets in patients. We partner with clinicians and foundations to test drugs in the clinic as quickly as possible.
We use validated targets to develop new drugs...
In parallel to clinical tests of predicted drugs, we develop entirely new, tailored drugs that more effectively engage clinically-proven drug targets .
...and our XIPcode-powered platform identifies other diseases that may benefit from the new drug
Since XIPcodes provide a unique path to identifying patients with shared therapeutic response profiles, we computationally find additional patient groups that may also benefit from the developed drugs, independent of clinical disease definitions and symptoms. These predictions can be rapidly tested by iterating through our BioNAV platform.