Since the implementation of quality by design and process analytics technology, the adoption of continuous manufacturing appears to be the next step in the modernization of pharmaceutical processes. The pharmaceutical industry and academia are developing a variety of continuous processing trains, each with a unique approach to process controls and assurance of quality. Regulators are monitoring this emerging technology and implementation of continuous manufacturing with the main focus being assurance of product quality and use of GMPs. In this context, the definition of in-process control limits, characterization of process variation, establishment of justified sampling plans, and the evaluation of content or attribute uniformity become especially important and challenging in continuous manufacturing. The use of statistics and statistically-based approaches for evaluating large amounts of data and for establishing limits and criteria that will inform quality decisions (real time and end product) may be the key for the eventual success of continuous manufacturing. This presentation will give an overview of continuous manufacturing elements that may require a different approach from a statistical and evaluation perspective, due to their difference from batch processing. An end-to-end process view will be presented with the goal to engender discussion among CMC statisticians that will be supporting continuous manufacturing development and operation efforts.