Estimating the Limit of Detection for LC-MS Analysis

Anneli Kruve, Schulich Faculty of Chemistry, Technion, Haifa, Israel
Hanno Evard, Institute Of Chemistry, University Of Tartu, Tartu, Estonia
Ivo Leito, Institute Of Chemistry, University Of Tartu, Tartu, Estonia

A large body of literature exists on the limit of detection (LOD), but there is still a lot of confusion about this important validation parameter. This confusion mainly stems from its statistically complex background. LOD estimates are strongly dependent on different assumptions and the approach used, and therefore caution must be exercised when using the estimate or when comparing different estimates.

In this work LOD is estimated for the LC-MS/MS analysis method to detect pesticides in tomatoes. The assumptions and practicality of different approaches to estimate LOD are compared based on these analyses. Different aspects of the analytical method that strongly influence LOD estimates (e.g. linearity, scedasticity and day-to-day variability of LOD) together with experimental design considerations when estimating LOD are discussed. The performance of different tests on the data necessary for LOD estimation are discussed and the results of different approaches under review in this tutorial are compared. As a result, a decision tree is proposed for estimating and monitoring LOD. A detailed working procedure for estimating LOD is presented.