Spektron Systems’ approach shortens discovery timelines from 8 – 11+ years to 3 – 4 years. We target a $10M cost of discovery opposed to $100M – $1.0B. Our approach shows a strong potential to disruptively improve pharmaceutical pipeline success.
Spektron Systems has developed a platform, Q-MAP™, for designing new molecules which we will carry through pre-clinical testing and sell to Big Pharma to develop through clinical testing. Q-MAP™ is designed to be agnostic to therapeutic drug class. As such, Spektron is inherently operating as a platform company.
The average cost of introducing a new drug has reached $2.6 billion. Pre-clinical trials alone can cost up to $1+ billion. Glacially slow discovery takes 8-11+ years per drug because traditional methods focus on scarce “low-hanging fruit”. Investment returns are low and dropping.
It is generally considered that Machine Learning (ML) and Artificial intelligence (AI) based approaches replace “brute force” experimentation and “needle in a haystack” luck with precise, directed design via vastly more efficient drug engineering solutions. Only one company—Spektron Systems — works closely with the FDA to establish reliable, repeatable methods for predictive toxicology and cost-effective new ML/AI drug discovery.
