One of the long‐established tenets in quality management—decreasing variability — is very much applicable to treatment planning, and is therefore one of the driving forces behind the development of more automated approaches. One proposed solution is based on the concept of machine learning. A database of previously accepted plans for a specific disease site is built. A new plan is supposed to achieve quality comparable to the previous cases with similar patient anatomy and objectives. 7 , 8 , 9 , 10 Another approach to partially automating the dose optimization process is implemented in the AutoPlanning (AP) software module, an option with Pinnacle v. 9.10 TPS (Philips Medical Systems, Fitchburg, WI). It requires no formal prior database of successful plans, but uses instead the iterative approach of progressive optimization. (11) The concept is largely to capture the steps that a skilled human operator would take and then mimic them for a new patient.