"Computational chemistry is playing an increasingly important role for research in the pharmaceutical industry, oils & plastic, and materials development. Simulation and high-throughput screening can be orders of magnitude cheaper than experiments in the early stages of drug design. The ERC project preceding this application has developed several new techniques that make it orders-of-magnitude more efficient to calculate free energies from simulations rather than approximate docking screening. We have already had great academic success, but the requirement of large computer clusters or access to the Folding@Home network makes it difficult to implement in industry.To address this, we have developed a new framework for peer-to-peer distributed computing combined with Markov state models (called “Copernicus”) to be presented at Supercomputing’11. Copernicus completely removes the need to deal with single simulations, and allows users to specify workflows - directly on their laptop - in terms of free energy calculations or sampling of complex processes such as protein folding. Workflows are transparently uploaded to a server and split into distributed calculation workunits (e.g. in a company), computer clusters, but also cloud computing to deal with peaks in usage. The results are again transparently moved to the user’s machine.This provides a clear competitive advantage in terms of efficiency, and it removes all investment and support costs related to high-performance computing. This is of course not limited to molecular simulation, and in addition to the pharmaceutical track we want to investigate usage in the financial industry. We have just submitted a patent application for the dynamic data flow network that makes the peer-to-peer usage possible, but we would need a programmer to turn the research-level code into a working proof-of-concept for high-throughput screening applications in the pharmaceutical industry and another person to work on business development."