For example, machine learned models have been used to predict results of free energy calculations or molecular docking . Subsequently, a fraction of the compounds was selected for calculations in the next iteration. Feeding the results of the calculations back into the ML training and iterating the process in a loop allowed to efficiently screen through a large chemical library.