90% of drugs fail in human trials, with 30% of them because of unforeseen side effects. This is an incredibly costly endeavor, since big pharma reports 1 failed drug costs $1 billion.

We believe that through more accurate computational models of disease we can pick better drug targets by predicting their side effects early. 

This would then increase the success rate of all the following stages in the drug development pipeline.

Our main focus is on collaborations with any organization developing treatments for Alzheimer’s disease, from biotech startups to established pharma.

• Current treatments cause brain bleeding as a side effect *

• Central nervous system drugs require long safety windows and predictability of side effects — our system’s strength

• Off-target effects and long-term metabolic impact are major reasons CNS drugs fail in trials — exactly the gap our models close