Impact of hemolysis during sample collection: how different is drug concentration in hemolyzed plasma from that of normal plasma?

Hemolysis is a common phenomenon in clinical studies. Despite the growing interest in hemolysis matrix effect, how hemolysis impacts the representability of hemolyzed plasma samples was rarely evaluated. The purpose of this research is to perform such an evaluation by theoretical consideration and experiment. A formula for estimating the impact is proposed, which includes the degree of hemolysis and the drug's red blood cell (RBC): plasma concentration ratio. The impact of hemolysis on the representability of hemolyzed plasma samples is compound-dependant. Given the same degree of hemolysis, the stronger a drug binds to RBCs, the more significant the impact of hemolysis. For a drug with high affinity to RBCs, the results of hemolyzed plasma samples may not be useful even though they are accurate. There is an overall agreement between theoretical predication and experimental results. Among the ten different drug compounds tested, only methazolamide, which binds strongly to RBCs, showed significant change in plasma concentration due to hemolysis.

Analyte and internal standard cross signal contributions and their impact on quantitation in LC-MS based bioanalysis.

Cross signal contributions between an analyte and its internal standard (IS) are very common due to impurities in reference standards and/or isotopic interferences. Despite the general awareness of this issue, how exactly they affect quantitation in LC-MS based bioanalysis has not been systematically evaluated. In this research, such evaluations were performed first by simulations and then by experiments using a typical bioanalytical method for tiagabine over the concentration range of 1-1000 ng/mL in human EDTA K(3) plasma. The results demonstrate that when an analyte contributes to IS signal, linearity and accuracy can be affected with low IS concentration. Thus, minimum IS concentrations have been obtained for different combinations of concentration range, percentage of cross contribution, and weighting factor. Moreover, while impurity in analyte reference standard is a factor in cross signal contribution, significant systematic errors could exist in the results of unknown samples even though the results of calibration standards and quality controls are acceptable. How these systematic errors would affect stability evaluation, method transfer, and cross validation has also been discussed and measures to reduce their impact are proposed. On the other hand, the signal contribution from an IS to the analyte causes shifting of a calibration curve, i.e. increase of intercept, and theoretically, the accuracy is not affected. The simulation results are well supported by experimental results. For example, good inter-run (between-run) accuracy (bias: -2.70 to 5.35%) and precision (CV: 2.07-10.50%) were obtained when runs were extracted with an IS solution containing 1-fold of the lower limit of quantitation.