Antimicrobial susceptibility test: from bacterial population analysis to therapy.

The statistical methods and parameters commonly used to define bacterial susceptibility to antibiotics in vitro such as MIC(50), linear regression or others, usually lead to a considerable loss of information: they do not take into account the heterogeneity of the bacterial population. In contrast, multivariate data analyses are more adapted to the description of biological systems. In this way, a population of a given bacterial species can be separated into homogenous classes corresponding to the different sensitivity and resistance phenotypes. The applications of this mathematical approach include: (i) a new model for more relevant interpretation of antimicrobial susceptibility test results; (ii) numerical estimation of breakpoints having a known risk; (iii) calibration of a technique relative to a reference technique; (iv) detection of strains with new phenotypes; (v) in vitro evaluation of the activity of new compounds.