Dried blood spots (DBS) are formed by deposition of a small amount of blood on specific adsorbent paper and its physical drying. DBS are employed as a sampling method in several fields of life sciences and drug research. A concern about DBS is the so-called 'Hematocrit (Ht) effect', as a different Ht leads, due to different viscosity, to different spot size, affecting assay bias. Solutions have been proposed, including the correction of quantified concentrations with a suitable correction factor. In order to quantitatively assess Ht impact on the DBS measurements, a computational approach was developed and implemented in R® language. First, the % relative error was modeled with respect to Ht. Then, Monte Carlo simulations were performed in virtual men/women populations with different Ht levels and the % relative error in relation to the Ht used for calibrators was quantified. An upper level for % relative error being a 'tolerable contribution' of Ht effect to % total analytical error was finally suggested, defining, for the first time, a potential Ht range for analysis of adults' samples, where correction of concentrations of unknown samples may be omitted. Such tolerable level for % relative error may be defined in each laboratory, also based on experimental parameters (type of paper and blood volume). Using a Ht calibration value representing the study population is fully rationalized, leading to reduced probability for concentration corrections. Regulatory criteria for bioanalysis can thus be targeted, moving towards wider utilization of DBS in human pharmacokinetic and clinical trials.
Keywords: Dried blood spots; Monte Carlo simulations; correction factor; hematocrit effect; relative error.