Will Advanced Technology Simulations Lead To More And Better Drugs? Start-Up Schrodinger Says It Can

One of the big mysteries of modern science is how molecules and proteins interact to establish the biological origins of health and disease. Rearranging this complex repetitive cycle of molecular binds and lapses to yield a positive change in the topography of illness is – unfortunately – an exercise in statistical improvisation. The possible combinations to yield a single molecule with drug-like properties against a pathogenic target is estimated at 10 to the 50th power, a number so large it comes close to what mathematics defines as infinity. Yet, to date, drug discovery in biopharma relies on a grain-in-the-sand calculus of potential, with the average new drug emerging from a screening process involving a little more than 5,000 molecular/protein targets. Industry’s prevailing discovery protocol is one of trial and error within an absurdly small field of possibilities, resulting in wide variations in pharmacological effect among individual patients and often quite modest therapeutic improvements overall.

It is no surprise that key stakeholders in biopharma – academia, regulators, patients and industry itself – are united in