A tool to evaluate nonlinearity in calibration curves involving isotopic internal standards in mass spectrometry

Abstract

Isotopic internal standards are widely employed for accurate quantitation in chemical and clinical analysis. Although this type of internal standardization – also referred to as isotope dilution mass spectrometry (IDMS) – has calibration curves that are inherently nonlinear, most analysts fit linear model to calibration data and use R2 as a metric to decide whether the calibration curves are reasonably linear.We show that this approximation can lead to significant errors even in cases when R2 > 0.99. We present a simulation approach – available as supplementary Excel spreadsheet – able to predict the IDMS calibration curves and estimate the errors that are introduced by the linear simplification. The simulation does not require experimental input and was validated using examples to cover cases of large, intermediate, and unnoticeable nonlinear calibration curves. This spreadsheet can be a valuable tool to plan IDMS experiments and to assess if a linear model is fit for purpose.