Exemplifying the pursuit for superior discriminatory power, the amplicon profile enhancement was treated with non-linear OAs for the epidemiological typing of Pseudomonas aeruginosa, in an arbitrarily-primed PCR procedure. Through the implemented AP-PCR protocol, it was attempted to adjust four well-known controlling factors which included the concentrations of: 1) MgCl2, 2) dNTP, 3) a primer and 4) the DNA template. It is interesting that the researchers proceeded to completing their study by executing concurrently the two sequentially prescribed tasks – process screening and parameter optimization – in a single effort. In brief, process screening filters out weak influences from an initial group of investigated factors. Parameter optimization gears towards finding those optimal settings of the identified strong factors, such that the performance of the predicted response is maximized. The strategy of running the two sequential tasks concurrently commands agility in dealing with two intertwined outcomes which in turn is redeemed with delivering cheaper and faster results. As a concept it is not new to modern production operations, since it essentially mirrors solid reengineering tactics as recommended by stringent lean-engineering principles. In planning the recipes for the AP-PCR procedure, the above researchers were vigilant about the behavior for each individual influence in case not conforming to linearity. Therefore, they designed their trials with the ABT-199 molecular weight provision to capture potential curvature trends if they were present. By implementing an L9 OA, the four controlling factors were optimally programmed to saturation ensuring that each individual factor is tested at least on three settings – to uncover possible nonlinearity. Furthermore, it was decided that the scheduled experimental recipes not to be replicated in order to curtail dramatically the turnaround time and the associated costs for the study. Subsequent response graphs summarized the behavior of the four controlling factors in a practical manner. In their report, the researchers concluded that all studied factors appeared to play some role in affecting the discriminatory power in the AP-PCR trials. The quality of their ensuing diagnosis was dependable on magnifying the resolution of the amplicon bands, thus allowing a greater dispersion of the detected polymorphism. Nevertheless, the reported profiles lacked of assigning any statistical significance on the outcomes. This is because standard techniques, such as analysis of variance or general regression, cannot retrieve error contributions from saturated and unreplicated OAplanned datasets. This paradox stems from the fact that all degrees of freedom gained from the conducted trials are exclusively distributed among the effects. Consequently, no remaining degrees of freedom are available to form a pooled error for sizing the magnitude of the experimental uncertainty. Hence, the data translation step is interrupted prematurely producing no statistical significances while any computed descriptive statistics may only be assessed subjectively. Additional concerns are raised when attempting to describe small-data designs, besides those that deal with the conditions of unreplication, saturation and non-linearity.