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It is impossible to imagine that any of the modern industries at the beginning of twenty‐first century may survive and progress without application of computational modeling. This observation is reflected in industries such as aviation and space, chemical, oil/gas, materials, and pharmaceuticals. In pharmaceutical industry, molecular modeling applications in Drug Discovery have a 30‐year history of great accomplishments; many of society’s greatest medicines were made possible, in part, due to computational modeling. However, computational modeling support of Drug Development has emerged only recently in full strength. An explanation for this hindrance is the high complexity of the modeling systems (solid and liquid phases of relatively large and flexible molecules) coupled with high expectations for accurate predictions that accompany late‐stage drug development. It is fair to state that in order to overcome these challenges, typical modeling applications in Drug Development are pushing the boundaries of fundamental theories and methods initially tested on the simpler “classical” systems. Therefore, many of the modeling applications in Drug Development became more feasible only with the recent advances in computational power of high‐performance computing systems.

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