Our innovative product engine draws inspiration from nature and evolution, which can be a source of insights into cancer targets, disease mechanisms and therapeutic approaches. We pay particular attention to natural products that are inherently rich with biological function as a result of natural selection and can inform and guide our discovery and development of small molecules that can modulate such targets. Our use of biologically relevant chemical information from nature depends on our ability to synthesize and modify complex natural products, specific portions of these complex compounds, and entirely original molecules inspired by natural products.
Our REVBLOCKS™ platform builds upon the research of the company’s academic founder, Martin D. Burke, M.D., Ph.D., who invented a transformative method for synthesizing chemical compounds including complex natural products, analogs or original small molecules that are pharmaceutically optimized. REVBLOCKS is a rapid, standardized and powerful process for conducting advanced medicinal chemistry by assembling simple “chemical building blocks” into refined structures that have significant potential as best-in-class drug candidates. REVOLUTION Medicines is thus able to synthesize, modify and improve many complex compounds that would be very challenging or even impossible to modify without this approach. We practice this technology under an exclusive license agreement with the University of Illinois.
In addition to our modular synthesis technology, REVOLUTION Medicines deploys its REVEAL™ platform to help guide design of compounds. REVEAL is a knowledge-driven informatics system designed to recognize advantageous structural and functional properties of scaffolds that can be exploited to engage protein targets. By learning from nature's experience in this way, we can elevate certain preferred compounds or portions of compouds as chemical starting points for optimization as drug candidates that will engage and modulate important disease targets. This computational platform also supports the process of optimization of lead compounds.