Importance of QuantificationThe underlying premise for this paper is that research articles, especially in tissue engineering/ regenerative medicine have to show how the proposed design helps meet the clinical performance requirements (in engineering terminology: clinical performance design constraints). Too often research papers that are trying to design a better clinical treatment use the scientific method vs. the engineering design process. It is not good enough to prove that the new design gives a statistically significant difference in an important bioprocess without discussing how this difference would lead to meeting the clinical performance requirement. So, without knowing the relationship between improvements in the measured bioprocess(es) and clinical performance little can be said about the clinical relevance of the study. The effectiveness of a clinical treatment is judged by quantification of results. This can be effectiveness for an individual or for a group of patients in a study to prove effectiveness of a treatment compared to current treatments. This can be in terms of patient health, time (treatment, recovery, return to work, etc.), cost (to patient, to healthcare providers, or insurance companies), or human factors (success rate, ease of use, or training required). This paper will concentrate on bioprocesses that affect patient health, but also relate to the other measures of effectiveness. The theme is that quantification of the rate of these bioprocesses is critical to designing successful clinical treatments. Patient health can be assessed in a number of ways from levels of specific biochemicals to functional tests. Although it is important to quantify all these bioprocesses, to be useful they need to be related to the clinical performance bioprocesses (typically performance design constraints measured as rates).