Standardized Procedure for the Simultaneous ... - ACS Publications

Article pubs.acs.org/ac

Standardized Procedure for the Simultaneous Determination of the Matrix Effect, Recovery, Process Efficiency, and Internal Standard Association Jean-François Bienvenu,* Gilles Provencher, Patrick Bélanger, René Bérubé, Pierre Dumas, Sébastien Gagné, Éric Gaudreau, and Normand Fleury Centre de toxicologie du Québec (CTQ), Institut national de santé publique du Québec (INSPQ), 945 Wolfe, Québec, Québec, Canada G1 V 5B3 S Supporting Information *

ABSTRACT: The matrix effects (MEs) on the quantification of an analyte can be significant and should not be neglected during development and validation of an analytical method. According to this premise, we developed a standardized procedure based on a set of six tests performed on six different sample matrices to detect and characterize the effects of the matrix for single and multiple analytes methods. The link between the matrix effect, recovery, process efficiency, accuracy, precision, and calibration curve was underscored by calculations performed with peak areas, ratios of standard/ internal standard peak area, and concentrations. The terms instrumental ME and global ME were introduced, and the term recovery was subdivided for clarity. The test accounts for the presence of ubiquitous and endogenous analytes through background subtraction. The results showed the necessity for using samples with an original concentration in the same range and that the concentration selected for the addition had a definite impact on the results. The use of six-sample matrices provided a standard deviation on the results, and this information could be inserted in a method performance result to show precision. The tool also allows for testing of different analytes/internal standard combinations, which helps with the selection of the association with minimum MEs. A UPLC-MS/MS method for the quantification of several phthalate metabolites in urine was developed and validated with this test. This methodology responds to a scientific need for homogeneity, clarity, and understanding of the results and facilitates the decision-making process while lowering the required costs and time.

A

ccording to the IUPAC,1 a matrix is defined as all of the components of the sample other than the analyte, so the effect of the matrix may have a multitude of origins. These effects are well-documented in the scientific literature, even if the terminology used is not universal2 (Table S1, Supporting Information). Kebarle and Tang3 were the first to describe this phenomenon, and since then, there have been numerous works reporting matrix effects (MEs) on liquid chromatography (LC)4,5 instruments, and other analytical techniques, such as gas chromatography (GC)6,7 and inductively coupled plasma8 (ICP), are also affected by the MEs. In LC-MS and ICP-MS, the term ME is often used to discuss variation in the ionization efficiency of the analyte of interest. This type of ME arises from the presence of coexisting compounds from the matrix with the analyte. MEs depend on the ionization type, and the electrospray ionization (ESI) technique is well-known for showing signs of this type of ME.3,9−12 When a separation technique is used, the ME is also affected by it, either by the separation performance or the carryover.2 To encompass the separation technique and the ionization phenomenon, the term instrumental ME was coined. © XXXX American Chemical Society

With ICP-MS, the addition of a source of carbon increases the signal of some analytes. This phenomenon is known as the carbon enhancement effect, and it is also an instrumental ME.13,14 In GC, the term ME refers to what is known as the matrix-induced response enhancement effect.15 This type of ME originates from deactivation of noninert sites on the instrument by the matrix, leading to an increase in the signal intensity, and it may also be considered an instrumental ME. In methods used for biomonitoring, in which specimens come from very different sources, the MEs may be very diverse, and it is necessary to control them. Otherwise, MEs may lead to over- or underestimation or even to the nondetection of an analyte. MEs have an impact on the sensitivity, the accuracy, and the ruggedness of the analytical method.4 There are a few procedures for assessing the MEs: postcolumn infusion, and the pre- and postextraction spike methods. While postcolumn infusion provides mostly visible Received: April 12, 2017 Accepted: June 19, 2017

A

DOI: 10.1021/acs.analchem.7b01383 Anal. Chem. XXXX, XXX, XXX−XXX

Article

Analytical Chemistry

is sometimes possible. When an STD does not have an SILISTD, it is necessary to select an ISTD that mimics the behavior of the STD during both the sample preparation and the instrumental analysis. How this ISTD is selected is not always trivial, and substantial data must be consulted. To address all the generated data and possibilities, a Microsoft Office Excel tool was developed to minimize the time spent for the calculations and to help with the analysis of the data during the development and validation of the analytical methods. This tool helps us at the CTQ to produce more robust, accurate, and precise methods in an ISO/IEC-17025 laboratory. As an example, a method for the biomonitoring of phthalate metabolites in urine by LC-MS/MS is presented. This method was used for the Canadian Health Measures Survey (CHMS).34 Phthalates are used as plasticizers to produce plastics that are more flexible and resilient. They are metabolized to their respective monoester derivative and subsequently oxidized into other compounds, which are excreted in urine largely as glucuronide conjugates.

information, the pre- and postextraction spike methods report quantifiable results for determining the importance of the MEs. The postcolumn infusion technique15 is a valuable technique for identifying the chromatographic region where the MEs are more likely to occur and serves as a tool for modifying the chromatography or the sample preparation to remove the analyte from the suppression zones. The postcolumn infusion also provides ME profiles that may be used to compensate for the ME in quantification of multianalytes methods.16−18 A good example of the postextraction spike method has been presented by Matuszewski et al.19 In this work, what he referred to as the absolute ME is measured by comparison between an extracted sample matrix spiked with the standard (STD) and the internal standard (ISTD), with a solution of the STD and the ISTD in the neat reconstitution solvent. What is actually monitored here is the instrumental MEs. The variation (expressed as the relative standard deviation (RSD (%)) between the different specimens of the matrix is referred to as the relative ME (the variation between the different matrix lots), and it is an important aspect when preparing a method for a wide range of sample sources (e.g., biomonitoring) A few years later, Matuszewski20 presented a work on the importance of relative ME, this time using pre-extraction spike calibration curves. This technique is representative of the actual method samples by encompassing the effects of the matrix on the instrument and on the recovery, and it may be referred to as the process efficiency (PE)20 or global ME. The pre- and postextraction spike methods are useful to quantify the extent of the MEs. If a problem in the quantification of an analyte arises, the combination of these techniques helps to pinpoint its source. Because some STDs are sometimes ubiquitous and finding matrix specimens in which all the required analytes are absent is time-consuming and sometimes impossible (such as compounds selected for biomonitoring studies), the tests were designed to use real matrix specimens that already contained a positive original level of the monitored analyte and not only real blank specimens. Numerous ways of circumventing the presence of MEs have been presented in the literature.21−27 Therefore, the main objective of this work is to bring a better understanding of the ME phenomenon and give an insight into where efforts must be deployed to minimize the influence of MEs on the results. Especially with LC and GC, in an ideal situation, all of the analytes should have their own stable isotope labeled internal standard (SIL-ISTD), where 13C, 15N, and 17O are the preferred isotopes to incorporate in the molecule,28−30 but they may not be equivalent.31 When these SIL-ISTD are not available, 2H becomes the isotope of choice, but the deuterium isotope effect32 is possible due to the difference in lipophilicity between deuterium and hydrogen. The positioning of the deuterium must be carefully selected to prevent the possibility of exchange with hydrogens from the matrix. A mass difference of at least 3 between the STD and the coeluting ISTD is important for preventing cross-talk.30 However, even the presence of an SIL-ISTD does not guarantee success.28,33 As mentioned by Stahnke et al.,16 the physicochemical properties of an analyte have a lesser influence on the extent of MEs than the matrix components eluting at the same time as the analyte. So, as a last resort, a structural analogue or an unrelated compound may also be used as an ISTD. For analytical methods containing other STD and ISTD, the association of the “orphan” STD and an ISTD already present in the method

■

EXPERIMENTAL SECTION Materials. The following standards were purchased from Cambridge Isotope Laboratories (Tewksbury, MA, USA): monobenzyl phthalate (MBzP), monocyclohexyl phthalate (MCHP), monoisononyl phthalate (MiNP), monoethyl phthalate (MEP), monomethyl phthalate (MMP), mono-nbutyl phthalate (MnBP), mono-2-ethylhexyl phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono(2-propylheptyl) phthalate (MiDP), mono(2-hydroxyisobutyl) phthalate (2-OH-MiBP), mono(3-hydroxy-n-butyl) phthalate (MHBP), mono(3-carboxypropyl) phthalate (MCPP), mono(5-carboxy-2-ethylpentyl) phthalate (MECPP), mono(6-hydroxy-2-propylheptyl) phthalate (MHiDP), mono(6-oxo-2-propylheptyl) phthalate (MOiDP), mono(7-carboxy-2,7-dimethylheptyl) phthalate (MCiNP), mono(7-carboxy-n-heptyl) phthalate (MCHpP), and monoisobutyl phthalate (MiBP) were purchased from CanSyn Chem. Corp. (Toronto, Ontario, Canada). Internal standards, MBzP-13C4, MCHP-13C4, MiNP-13C4, MEP-13C4, MMP-13C4, MnBP- 13 C 4 , MnOP- 13 C 4 , MEHP- 13 C 4 , MEHHP- 13 C 4 , MEOHP-13C4, MCPP-13C4, and MECPP-13C4. Mono-n-octyl phthalate (MnOP), mono-(2-carboxy-methylhexyl) phthalate (MCMHP), MCMHP-d4, 2-OH-MiBP-d4, and MHBP-d4 were purchased from Toronto Research Chemicals (Toronto, Ontario, Canada). MiBP-d4 and MiDP-d4 were obtained from CDN isotopes Inc. (Pointe-Claire, Québec, Canada); mono(7hydroxy-methyl-octyl) phthalate (MHiNP), mono(8-carboxyoctyl) phthalate (MCiOP), and mono(oxoisononyl) phthalate (MOiNP), from the Institut für Dünnschichttechnologie and Mikrosensorik e.V (Teltow, Germany). General Sample Preparation. Briefly, for the enzymatic deconjugation, in a 10 mL tube was added the urine sample (500 μL) followed by the ISTD solution (25 μL), 2% βglucuronidase solution (100 μL) in ammonium acetate (1 M, pH 6.5), and water (500 μL). The tube was sealed and placed in a water bath (37 °C, 75 min). The extraction was performed on a Janus robotized workstation (PerkinElmer, Waltham, MA, USA) by adding 50% orthophosphoric acid solution (25 μL) and a mixture of hexane:ethyl acetate (1:1; 4.5 mL), agitated for 5 min, and centrifuged at 3000 rpm. The extracts (1.8 mL) were evaporated until dryness using a Turbo Vap (Zymark B


Article

Analytical Chemistry Corp., Hopkinton, MA, USA); recovery solution (400 μL) was added, transferred to a glass vial (2 mL), and 7.5 μL was injected via partial loop with needle overfill mode on a UPLCMS/MS on a Xevo TQ-S platform (Waters, Milford, MA, USA). The chromatography was performed on an ACE Excel C18-AR (2.1 mm × 50 mm, 2 μm; Advanced Chromatography Technologies Ltd., Aberdeen, Scotland) with 0.1% acetic acid in water and 0.1% acetic acid in methanol as mobile phases. The MS was equipped with an electrospray ionization source using multiple reaction monitoring (MRM) in the negative mode. An Experimental Section complement containing the preparation of the calibration curve, the recovery solutions preparation, and the preparation of the biological samples for the six sets is available in the Supporting Information. Excel Tool. Data were collected with MassLynx (Waters, Milford, MA, USA), transferred into Excel (Microsoft Corp., Redmond, WA, USA), and a series of macros provided tables and graphs of the results (see detailed results in the Supporting Information).

■

RESULTS AND DISCUSSION The main objective of the test is to determine if the results of the analytical methods are accurate and precise and if there is uncertainty to determine what the cause of this variation is. For methods that are used for biomonitoring, there is a requirement for reliability and sustainability of the results over the years, thereby keeping the MEs under control. Based on the principle of the pre- and postextraction spiking method presented by Matuszewski et al.19,20 in which a series of three sets is used; in this study, a series of six sets was created to obtain a more complete picture of the MEs. Quickly obtaining a clear image of the different effects while keeping the number of samples as low as possible has been a priority in the present study. Based on the guidelines for bioanalytical method validation,35,36 the use of a six-sample matrix for the test was selected, but the use of more samples is also possible. This should give a good overview of how well the MEs are controlled. Using samples with the greatest variety possible was important. For example, when urine is the targeted matrix, a good strategy could be to use samples where the variation in specific gravity could range from approximately 1.005 to approximately 1.030. The utilization of this test is not limited to biological matrices. The test was separated into six different sets performed with the six-sample matrix (Figure 1). Set A. The STD and the ISTD were added to the neat reconstitution solvent. Set B. The sample preparation was performed on the matrix, and the STD and ISTD were added afterward. Set C. The STD was added to the matrix before the sample preparation, and the ISTD was added afterward. Set D. The STD and the ISTD were added to the matrix before the sample preparation. Set E. The ISTD was added to the matrix before the sample preparation, and no STD was added. Set F. The sample preparation was performed on the matrix, the ISTD was added afterward, and no STD was added. To deal with the lack of blank matrix, spiking the matrix samples before (set E) and after sample preparation (set F) enables the use of matrices containing a basic quantity of the analyte by background subtraction.37 It is a good practice to screen the sample matrix before performing the series of tests

Figure 1. Graphical representation of the series of six sets performed on a six-sample matrix.

to ensure an appropriate spike level that should be at least 4 times the original concentration as recommended by Ellison and Thompson.38 Always keep in mind that the precision of the results depends in part on Q, which is the ratio of the added concentration (C) divided by the original concentration (T).38 As previously noted,19,20 performing the test at more than one concentration to obtain a better understanding of the ME is a good practice, as the effects of the matrix may be dependent on or independent39 of the concentration of the analyte and may not be uniform across the concentration range.40,41 Instrumental ME. The effect of the separation technique and the detection instrument are encompassed in the term instrumental ME. According to Matuszewski et al.,19 to observe the presence of an absolute ME (or instrumental ME), the peak area of the STD in set B is divided by the peak area of the same analyte in the neat reconstitution solvent (set A): set B instrumental ME (%) = × 100 (1) set A Set A is considered the reference point, but always keep in mind that the neat reconstitution solvent is also a matrix and may affect the results. If the analyte is already present in some samples, this original quantity must be subtracted from the results of set B. For the determination of this original quantity, the addition of a set in which the “blank” sample is extracted becomes important. When calculating the instrumental ME with areas, set E and set F may be used as the initial area value since there is no addition of the STD in the sample. Using set F, the equation for the instrumental ME becomes (see the details of the equations in the Supporting Information): instrumental ME (%) =

(set B − set F) × 100 set A

(2)

When calculated with peak area, this instrumental ME may be an indication of the presence of components other than the analyte during the ionization process, which are interfering in C


Article

Analytical Chemistry some way with the detection of the analyte. The average value for the six-samples matrix provides an idea of the importance of the instrumental ME on the samples in general. The SD calculated with these values may be considered the relative instrumental ME.19 The greater the value obtained, the greater the variation in the instrumental ME between the different samples. As underscored by Peters et al.,42 the SD is as important as the average value of the measured ME. Thus, when providing data concerning the instrumental ME, the SD on the six samples should also be provided to show precision. For the ISTD, eq 1 may be used for the determination of the instrumental ME with only the peak area of the ISTD since the only difference between the two sets is the matrix extract. To verify how differently the STD and the ISTD are affected by the matrix on the instrument, an ISTD-normalized STD instrumental ME must be calculated. If the ISTD is compensating for the instrumental ME of the STD, the ISTD-normalized value should be close to 100%. Equation 1 (or eq 2) must be used with the ratio of the STD peak area divided by the ISTD peak area (aka the response ratio). For eq 2, set F must be used in the calculation, because the ISTD is added at the end of the preparation for sets B and F. If set E is used in the calculation of eq 2, the recovery of the ISTD may interfere with the results. While the instrumental ME calculated with peak area indicates a variation in the signal of the STD or the ISTD, the ISTD-normalized instrumental ME calculated with the response ratio provides information on the similarity of the variations on the STD and the ISTD. Always keep in mind that for a sample, even if the ISTD-normalized instrumental ME is correct, if the STD instrumental ME is important, then the expected limit of detection may be compromised.10 When the instrumental ME was calculated with concentrations using eq 3 (or eq 4 for matrices with an original concentration), it provided information on the impact of the instrumental ME on the quantification of the analyte. instrumental MEconc (%) =

set B × 100 added conc

(3)

instrumental MEconc (%) =

(set B − set F) × 100 added conc

(4)

In this situation, set C and set D are interchangeable because, in both cases, the STD is added to the sample matrix before the analytical procedure, which compares with adding the analyte after the completion of the method (set B). As mentioned previously, when considering STD areas, sets C and D should be almost identical. If this is not the case, the reason should be determined. The same is true for set E and set F: if an original quantity is present and the STD was not added to the matrix, then the areas should be almost identical. To obtain the recovery of the STD with the use of the ISTD to compensate for instrumental variations, an ISTD-normalized STD RE may be calculated with response ratios, using again eq 5 (or eq 6). The STD is added before (set C) and after the sample preparation (set B), while the ISTD is added only at the end of the procedure for both sets. This way, the ISTD recovery does not interfere with the ISTD-normalized STD RE. For the fraction of the ISTD recovered after the analytical procedure, the ISTD RE may be calculated with the ISTD peak area only using eq 7. ISTD RE (%) =

set C × 100 set B

(5)

STD RE (%) =

(set C − set F) × 100 (set B − set F)

(6)

(7)

To obtain the ISTD RE when the STD is used to normalize the results, eqs 7 and 8 may be used with the response ratios. The STD is added at the beginning of the procedure for sets C and D, and the ISTD is added at the beginning (set D) and at the end (set C) of the analytical procedure. STD‐normalized ISTD RE (%) =

(set C − set F) × 100 (set D − set E) (8)

Because ISTDs are used in the method, it is desirable to know how well the selected ISTD follows the STD regarding sample preparation. Equations 9 and 10 may be used with response ratios, to obtain information on how closely the recoveries of the STD and the ISTD are related. When using sets B and D, both the STD and the ISTD are added at the same time, at the beginning (set D) and the end (set B) of the procedure. Thus, obtaining a value close to 100% is highly expected. The term ISTD-normalized STD recovery factor (RF) was selected to bring more precision.

Note that when comparing eq 3 (and eq 4) with eq 1 (and eq 2), the added concentration is used instead of set A. This ensures that the calibration curve is considered in the determination of the effect of the extracted matrix on the concentration obtained versus the expected concentration. The matrix factor (MF), which is equal to 1 minus the instrumental ME, may also be used to represent the instrumental impact of the matrix on the area of the STD. However, as noted,43 it may not be enough to obtain reliable results. The recovery and global ME must be added to obtain a complete picture. Recovery. The recovery (RE) is defined as the fraction of the analyte recovered after a chemical procedure,1 and it may be evaluated with the peak area according to eq 5 (and eq 6 for matrices containing an original quantity of the STD). STD RE (%) =

set D × 100 set C

ISTD‐normalized STD RF (%) =

set D × 100 set B

ISTD‐normalized STD RF (%) =

(set D − set E) × 100 (set B − set F)

(9)

(10)

The ISTD-normalized STD RF is calculated as the ISTDnormalized STD RE divided by the inverse of the STDnormalized ISTD RE (see Supporting Information for calculation details). Since all the formulas for the RE and RF are related, they are independent of the calibration curve, and they provide the same results when calculated with response ratios or with concentrations. Process Efficiency. According to Matuszewski et al.,19 the process efficiency (PE) is the combined effect of the instrumental ME multiplied by the RE. The PE represents the difference induced by the matrix on the analyte during the complete analysis procedure compared to the analyte in the neat reconstitution solvent (set A). D


Article

Analytical Chemistry Table 1. Overview of the Results Generated for the Different Phthalate Metabolite STDs with the Associated ISTDa

a

Symbols: *, associated deuterated SIL-ISTD; **, associated 13C SIL-ISTD; †, Orphan STD.

it is the combination of the ISTD-normalized STD RF (eqs 9 and 10) and the instrumental MEconc (eqs 3 and 4). Very careful attention must be placed on the results of the global ME to obtain reliable results for all the samples analyzed with this method. Even if the value of the global ME has its importance, the SD of the values obtained for the six samples is also very important.20 This SD represents the precision and should be provided with the global ME value when showing the method’s performance. Calibration Curve Factor. To compare the response ratios in the neat reconstitution solvent and in the matrix used for the calibration curve, a calibration curve factor is calculated with concentrations using eq 15.

When the STD PE is calculated using eq 11 (or eq 12) with peak area, set C and set D are interchangeable because the STD is added at the beginning in both sets. When calculated with response ratios, sets C and D are not interchangeable, and only the set where the ISTD is added before the extraction (set D) may be used in eq 11 (and eq 12). When evaluated with the response ratios, the ISTD-normalized PE is equal to the ISTDnormalized STD RF (eqs 9 and 10) multiplied by the STD instrumental ME (eqs 1 and 2). PE (%) =

set D × 100 set A

(11)

PE (%) =

(set D − set E) × 100 set A

(12)

curve factor (%) =

Using eq 11, the ISTD PE may also be calculated with the ISTD peak area only. Global Matrix Effect. A procedure used in analytical chemistry for the determination of what is called recovery by some researchers2 may be used to provide an indication on how well the samples are quantified. Other terms are also used to describe the observed phenomena such as matrix variation,44 total or overall matrix effect.45 Equation 13 is a modification of the formula presented by Matuszewski et al.19 (eq 14) for accuracy. global ME (%) =

(set D − set E) × 100 added conc

(13)

global ME (%) =

set D × 100 added conc

(14)

set A × 100 added conc

(15)

When dealing with ubiquitous analytes, obtaining good results with this descriptor provides insights to the possible use of a surrogate matrix37 for the calibration curve and may be considered an indication of the need for using a matrix matched calibration curve,46 but it must be validated.47 Results Overview. An overview of the results for the methods are presented in Table 1 (see Supporting Information for more detailed results). With a multianalytes method, dealing with the numerous data obtained during the development and the validation may not be as trivial as it might seem. Thus, conditional formatting of the cells containing the results of the average of the six biological specimens and the associated SD provided a quick overview of the method’s behavior. For all the descriptors, an average value between 95 and 105% and an SD below 5% were considered acceptable, and the cells were listed in green. When the average value differed by ±10% to 100% or when the SD was between 5 and 10%, the results may still have been acceptable, but they needed to be investigated to find the cause of the variation. These results were listed in yellow. With descriptor results oscillating between ±15% or with SD oscillating between 10 and 15% (colored in orange), the root cause of this bias or variation

These two sets (D and E) are as close as possible to the real samples that will be measured with the final analytical method. In set E, only the ISTD solution is added to the sample matrix, and in set D, the solution of STD and the solution of ISTD are added to the sample before the sample preparation. The global ME (eqs 13 and 14) is a PE calculated with concentrations, and E


Article

Analytical Chemistry needed to be pinpointed. The results between ±15 and ±20% were listed in red, and the results exceeding ±20% showed where the attention should be focused. The same color code was applied for all of the data produced. To obtain a visual idea of where the diagnostic work could have been done, a chart containing the link between the different descriptors was prepared (see Figure S1, Supporting Information). The global ME and the corresponding SD (or precision), when calculated with concentrations, was the most important aspect to verify. If a problem was encountered, verification of the ISTD-normalized STD PE and the curve factor were the next avenues to pursue. The problem might have arisen from two major sources: the instrumental side or the sample preparation (laboratory) side. The instrumental side was verified by taking a closer look at the ISTD-normalized STD instrumental ME. Any difference between the STD and the associated ISTD instrumental ME will be perceptible with this descriptor. The investigation was then continued on the sample preparation side. The first descriptor of this portion to verify was the ISTD-normalized STD RF, as it highlighted the gap between the difference in the recovery of the STD and the associated ISTD. Within the structure of the test, multiple verifications of the solutions used and sample homogeneity were also possible (see Figure S1, Supporting Information). For the sake of the discussion, samples with a Q value below 4 may have been removed to highlight their impact on the results. It is suggested to either select another sample with the same characteristics or increase the concentration added to this sample to the adequate amount in order to confirm that the quantification is acceptable on that sample. In the present phthalate example (Table 1), most of the results obtained for the global ME were considered acceptable and did not require further investigation. In the cases of MHBP, MnBP, MiBP, and MEP, the global ME provided interesting results. MHBP. For the MHBP, there was a bias of +15% for the global ME, but the SD was only 2.9%. When considering the ISTD-normalized STD PE, the result was 102.6% and the SD was only 2.6%. This showed that both the MHBP and MHBPd4 behaved similarly in the neat reconstitution solvent (set A) and in the real samples (sets D and E) but differently in the calibration curve. A curve factor of 112% confirmed that the reason behind this bias lay in the calibration curve made from washed urine, a matrix different from the real samples. When the instrumental MEconc (123.6 ± 9.9%) is compared with the ISTD-normalized STD ME (110.4 ± 8.8%), the effect of the calibration curve on the results may also be observed. When calculated with the STD peak area alone, the high SD of the STD instrumental ME (107.3 ± 11.4%) came mostly from one sample having a Q value of 0.5. If this sample matrix was removed, the STD instrumental ME decreases to 102.9 ± 3.4%. The associated MHBP-d4 (ISTD instrumental ME, 93.2 ± 4.1%; Table 2) did not effectively compensate for this difference, causing an increase in the ISTD-normalized instrumental ME value. The difference in retention time (RT) between the STD (3.92 min) and the ISTD (3.88 min) is a result of the deuterium effect, providing different environments for the analytes, thus creating a difference in the instrumental ME. The difference between the STD RE (76.1 ± 4.2%) and the ISTD RE (84.0 ± 2.9%) indicates that MHBP and MHBP-d4 were not extracted in the exact same manner. The proximity of these values with the results obtained for the ISTD-normalized

Table 2. Overview of the Method’s PE, Instrumental ME, and RF and RE for the ISTD

STD RE (78.3 ± 5.5%) and the STD-normalized ISTD RE−1 (83.7 ± 5.2%) showed that their behavior is similar during sample preparation. The small difference between these two normalized values is observed in the ISTD-normalized STD RF (93.5 ± 8.0%). MnBP. The high SD for the global ME (93.6 ± 11.6%) is perhaps partly due to the fact that the original concentration for four samples (out of the six originally selected) was 3.6−8.2 times higher than the added concentration. Thus, a Q value well below the recommended value of 4 is obtained, providing variability in the results. After careful examination of the results obtained with MnBP and the associated ISTD (MnBP-13C4), this variation came from one specimen providing results almost 30% lower than expected. If this sample was removed, a global ME of 98.0 ± 5.3% was obtained. If the same specimen was removed from the ISTD-normalized STD PE, the value increased from 92.0 ± 11.4 to 96.2 ± 5.2%. The instrumental MEconc (85.7 ± 12.1%) was 14.3% lower than expected, and the same effect was present when the ISTDnormalized STD ME (84.3 ± 11.8%) was considered (−15.7%), showing that the associated ISTD did not compensate for this effect. However, the calibration curve was correct, as shown by the curve factor (101.5%). When only the areas were taken into consideration, the SD of the STD instrumental ME was high (102.7 ± 21.5%). This high SD was mostly due to one biological sample that already contained a great amount of the analyte (Q value of 0.1) and provided a very high STD instrumental ME (145.5%; see the Supporting Information). Once removed, the value of the STD instrumental ME decreased to 94.2 ± 5.8%. The difference between this value and the value of the ISTD instrumental ME (86.3 ± 6.3%) is difficult to explain because the ISTD is a 13C analogue and both the STD and the ISTD had the same RT. The ISTD-normalized STD RF decreased from 110.8 ± 21.1 to 102.8 ± 8.8% when a sample with a low Q value was removed. It might be tempting to conclude that the associated ISTD (MnBP-13C4) did not correct for the STD recovery; once again, the Q values for four out of six samples were below 1. MiBP. The global ME (106.0 ± 15.9%) was only 6% over the ideal value, but the SD was relatively high. This high SD mainly resulted from one sample in which the original concentration of the analyte was twice the amount of the F


Article


to the logarithm of the matrix concentration,49 the dilution and injection of the sets may also provide information on the maximum dilution possible for obtaining MEs. Other STD Recovery. For the other STD of the method, the ISTD-normalized STD RF was near 100 ± 5%, except for MCMHP (93.2 ± 2.0%), showing that there was a slight difference for the recovery in favor of the deuterated analog. As mentioned before, the ISTD-normalized STD RF shows how well the ISTD is following the STD with regard to the recovery. ISTD Selection. The results obtained with the test were used to select the ISTD to be associated with the “orphan” STD. New calibration curves were calculated with a weighting of 1/x (as in the actual method). The results for the global ME and the associated SD with all the ISTD present in the method are presented in Table S27 (Supporting Information). As already mentioned,48 the variation between the STD and the ISTD are different between the different sample lots, and SD should be as low as possible. For the seven orphan STDs, three possible ISTDs (MEHHP-13C4, MECPP-13C4, and MCMHPd4) stood out as having acceptable global ME values and very low SDs. To determine the best ISTD, the instrumental MEconc and the ISTD-normalized STD RF were used (see Table S28, Supporting Information). The MEHHP-13C4 showed the best results for the instrumental MEconc and the corresponding SD for all the STDs. With regard to the ISTD-normalized STD RF, the MEHHP-13C4 was again a better match than the two others for all the analytes. Each orphan STD may have had a preferred ISTD, but the same ISTD was selected for the quantification of these analytes. To verify if the association of an STD with an ISTD, as obtained with the test results, is viable, MiBP was selected as an example because reference values were available from an interlaboratory program, the German External Quality Assessment Scheme (G-EQUAS).50 The previously mentioned methodology was used to look for a possible replacement for MiBP-d4 to quantify MiBP. Of all the ISTD present, MBzP-13C4 provided the best results (see Table S3, Supporting Information), and when it was used as an ISTD for MiBP, the calculated global ME decreased from 106.0 ± 15.9 to 97.2 ± 4.0%, the instrumental MEconc decreased from 105.2 ± 15.2 to 103.5 ± 8.3%, and the ISTD-normalized STD RF decreased from 101.2 ± 9.5 to 94.4 ± 8.0%. These results seemed to indicate that both ISTDs could be used in the current method. To verify this hypothesis, the results for in-house QC (three levels: 2.30, 11.3, and 151 μg/L) and four G-EQUAS reference materials (expected concentrations: 16.5, 47.5, 114.6, and 287.7 μg/L) were compared for MiBP (Chart 1) with both ISTDs (see Table S29, Supporting Information). The correlation was very good (r2 = 0.9968), and the slope of the curve (0.9732) was very close to unity. These results indicate that the test results, with the help of the Excel tool, provided information that may be applied to the analytical method. It was then possible to foresee that, for an orphan STD, a mixture of ISTD may be added to the test, and the data collected may then be used to select the best possible combination between the STD and the ISTD.

added concentration (Q = 0.5). When this sample was remove the global ME value decreased to 100.3 ± 8.8%. The same phenomenon was observed for the ISTD-normalized STD PE (102.2 ± 15.4%), which decreased to 96.8 ± 8.5% upon removal of the sample. The matrix used for the calibration curve was correct, as shown by the curve factor (103.3%) There was a clear instrumental ME for MiBP (87.2 ± 11.1%) and the associated ISTD, MiBP-d4 (79.7 ± 13.6%), as shown by the relatively high SD results of the STD (and ISTD instrumental ME (Tables 1 and 2). The added value of sorting the sample by increasing the specific gravity was easily perceived with the trend observed for the values of the individual MiBP-d4 instrumental ME. The ISTD-normalized instrumental ME (101.5 ± 14.7%) showed the importance of providing the SD with the average result, as two samples (Q values of 0.5 and 0.8) showed great variation from 100% (+19.6% and −23.7%). The original concentration of the analyte had an impact on the results and was probably the reason for the high SD. The STD RE (93.9 ± 6.6%) and the ISTD RE (95.7 ± 6.7%) were similar, and the SD was considered correct. The ISTDnormalized STD RF (101.2 ± 9.5%) showed that, with regard to the recovery, the STD and the ISTD behaved the same way. MEP. For this analyte, two samples had an original concentration higher than the concentration added to the sample (Q = 0.6), and the impact was observable in the values for the different descriptors. The global ME (93.7 ± 6.9%) and the ISTD-normalized STD PE (90.8 ± 6.7%) showed improvement (97.7 ± 3.8 and 94.8 ± 3.6%, respectively) when these two samples were removed. The curve factor (102.8%) showed that it was possible to use the washed urine as a matrix for the calibration curve. Even if the instrumental ME (75.8 ± 9.9%) was below 80%, the MEP-13C4 (73.2 ± 9.8%) was shown to properly follow the STD with regard to the instrumental ME. This was highlighted by the ISTD-normalized STD instrumental ME and the STD instrumental MEconc. The ISTD-normalized STD RF (94.5 ± 3.7%) increased to 96.5 ± 0.9% when the two previously mentioned samples were removed. This showed that the recoveries of the STD and the ISTD have the same behavior. Other STD Global ME. It was interesting to note that MECPP and MEHHP had three samples in which the value of Q was below 1, and their global ME could still be considered acceptable. If these samples were to be replaced with samples having the same properties and a lower original concentration, the SD would most likely be smaller. From the results we obtained, it appears important to select matrices with original concentrations in the same range in order to add a concentration being at least 4 times the original one. Following this recommendation38 may be useful when using standard addition method for quantification. Other STD Instrumental ME. The STD instrumental ME was 78% for MiDP and MMP. For these analytes, the associated ISTD was compensating correctly for these area variations, as shown by the results of the ISTD-normalized ME. The calibration curve was also correct because the results of the instrumental MEconc were close to 100%. MEs may be minimized with a better chromatographic separation.48 Thus, the reinjection of the sets with different chromatographic or MS conditions may be used without reextraction of the samples to verify the extension of the MEs variations. Because the extent of the instrumental ME is linked

■

CONCLUSION A standardized procedure was developed to assist scientists in the determination of the most important factors for the quantification of the analyte. The test was performed with the G



■

Chart 1. Comparison between the Concentrations Obtained for MiBP Calculated with MiBP-d4 and MBzP-13C4 for the Different Reference Materials

Article

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Fax: (418) 6542754. ORCID

Jean-François Bienvenu: 0000-0002-8861-6701 Author Contributions

J.-F.B. designed the study and wrote the manuscript; G.P. designed the study, performed the experiments, and analyzed the data; P.B., R.B., P.D., and S.G. participated in the design of the study and analyzed the data; E.G. and N.F. wrote part of the manuscript. Funding

Financial support was provided by an internal budget dedicated to development and research. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We are very grateful to Nathalie Morissette, Yves Simard, and Simon Chouinard of the CTQ for their technical support and to Ciprian Mihai Cirtiu and Pierre Ayotte, who revised the manuscript.

use of six sets of a six-sample matrix, to verify the quantification of the analyte, and give insights into the possible cause(s) of the quantification variation between samples. The results showed that a sample with an original concentration of the analyte may be used for the test, but the range of concentration of the sixsample matrix should be small, and some high SD may be attributed to low Q values. For clarity, the terms instrumental and global matrix effect were introduced, and the results they provided are complementary and linked together. The term recovery was given more precision and distinguished from the recovery factor. The most important aspect to verify was the global ME. If a problem is observed, the instrumental side (instrumental ME) and the laboratory side (ISTD-normalized STD RF) are the two aspects that should be investigated. The standardized procedure also provides an easy way to check the association of an analyte with an ISTD, and it helps in the selection when a SIL-ISTD is not available. The most important aspects to consider when associating an ISTD with an STD are the global ME (and corresponding SD), followed by the results of the ISTD-normalized STD RF and the instrumental MEconc. The possible replacement of MiBP-d4 with MBzP-13C4 provided similar results for in-house and external QC, showing that the methodology used for the selection of the ISTD was valid. The urinary phthalate metabolites method is a good example of the type of information that can be obtained with the standardized procedure and the Excel tool. So far, more than 30 methods have been developed and validated with this methodology at the CTQ.

■

■

REFERENCES

(1) IUPAC. Compendium of Chemical Terminology, 2nd ed. (the ″Gold Book″); McNaught, A. D., Wilkinson, A., Eds.; Blackwell Scientific Publications: Oxford, U.K., 1997. XML on-line corrected version: http://goldbook.iupac.org and https://doi.org/10.1351/ goldbook, 2006 (created by Nic, M.; Jirat, J.; Kosata, B.; updates compiled by Jenkins, A.). (2) Huang, Y.; Shi, R.; Gee, W.; Bonderud, R. Bioanalysis 2012, 4, 1919−1931. (3) Kebarle, P.; Tang, L. Anal. Chem. 1993, 65, 972A−986A. (4) Taylor, P. J. Clin. Biochem. 2005, 38, 328−334. (5) Van Eeckhaut, A.; Lanckmans, K.; Sarre, S.; Smolders, I.; Michotte, Y. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2009, 877, 2198−2207. (6) Poole, C. F. J. Chromatogr. A 2007, 1158, 241−250. (7) Akutsu, K.; Yoshimitsu, M.; Kitagawa, Y.; Takatori, S.; Fukui, N.; Osakada, M.; Yamaguchi, S.; Kajimura, K.; Obana, H.; Watanabe, T. J. Sep. Sci. 2017, 40 (6), 1293−1300. (8) Mermet, J.-M. J. Anal. At. Spectrom. 1998, 13, 419−422. (9) Souverain, S.; Rudaz, S.; Veuthey, J.-L. J. Chromatogr. A 2004, 1058, 61−66. (10) Annesley, T. M. Clin. Chem. 2003, 49, 1041−1044. (11) Dams, R.; Huestis, M. A.; Lambert, W. E.; Murphy, C. M. J. Am. Soc. Mass Spectrom. 2003, 14, 1290−1294. (12) Cappiello, A.; Famiglini, G.; Palma, P.; Pierini, E.; Termopoli, V.; Trufelli, H. Anal. Chem. 2008, 80, 9343−9348. (13) Allain, P.; Jaunault, L.; Mauras, Y.; Mermet, J. M.; Delaporte, T. Anal. Chem. 1991, 63, 1497−1498. (14) Larsen, E. H.; Stürup, S. J. Anal. At. Spectrom. 1994, 9, 1099− 1105. (15) Bonfiglio, R.; King, R. C.; Olah, T. V.; Merkle, K. Rapid Commun. Mass Spectrom. 1999, 13, 1175−1185. (16) Stahnke, H.; Reemtsma, T.; Alder, L. Anal. Chem. 2009, 81, 2185−2192. (17) Liao, H.-W.; Chen, G.-Y.; Tsai, I.-L.; Kuo, C.-H. J. Chromatogr. A 2014, 1327, 97−104. (18) Rossmann, J.; Gurke, R.; Renner, L. D.; Oertel, R.; Kirch, W. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2015, 1000, 84−94. (19) Matuszewski, B. K.; Constanzer, M. L.; Chavez-Eng, C. M. Anal. Chem. 2003, 75, 3019−3030.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.7b01383. Terminology comparison table; experimental section complement details of the mathematical equations; graphical representation of the links between descriptors; STDs and associated ISTD table; complete results for all the STDs with associated ISTD; calculated descriptors for the “orphan” STD; and QC results obtained for MiBP with MiBP-d4 and MBzP−13C4 (PDF) H


Article

Analytical Chemistry (20) Matuszewski, B. K. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2006, 830, 293−300. (21) Trufelli, H.; Palma, P.; Famiglini, G.; Cappiello, A. Mass Spectrom. Rev. 2011, 30, 491−509. (22) Gosetti, F.; Mazzucco, E.; Zampieri, D.; Gennaro, M. C. J. Chromatogr. A 2010, 1217, 3929−3937. (23) Cote, C.; Bergeron, A.; Mess, J. N.; Furtado, M.; Garofolo, F. Bioanalysis 2009, 1, 1243−1257. (24) Chambers, E.; Wagrowski-Diehl, D. M.; Lu, Z.; Mazzeo, J. R. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2007, 852, 22−34. (25) Xu, R. N.; Fan, L.; Rieser, M. J.; El-Shourbagy, T. A. J. Pharm. Biomed. Anal. 2007, 44, 342−355. (26) Mallet, C. R.; Lu, Z.; Mazzeo, J. R. Rapid Commun. Mass Spectrom. 2004, 18, 49−58. (27) Kim, H.-J.; Kang, J.-S. Biodesign 2016, 4, 46−58. (28) Wang, S.; Cyronak, M.; Yang, E. J. Pharm. Biomed. Anal. 2007, 43, 701−707. (29) Li, W.; Cohen, L. H. Anal. Chem. 2003, 75, 5854−5859. (30) Stokvis, E.; Rosing, H.; Beijnen, J. H. Rapid Commun. Mass Spectrom. 2005, 19, 401−407. (31) Li, X. Q.; Zhang, Q. H.; Yang, Z.; Li, H. M.; Huang, D. F. Anal. Bioanal. Chem. 2017, 409, 3233−3243. (32) Iyer, S. S.; Zhang, Z. P.; Kellogg, G. E.; Karnes, H. T. J. Chromatogr. Sci. 2004, 42, 383−387. (33) Lindegardh, N.; Annerberg, A.; White, N. J.; Day, N. P. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2008, 862, 227−236. (34) Canadian Health Measures Survey (CHMS). http://www23. statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&Id=136652. (35) Committee for Medicinal Products for Human Use (CHMP). Guideline on bioanalytical method validation; European Medicines Agency: London, United Kingdom, 2014. (36) Viswanathan, C. T.; Bansal, S.; Booth, B.; DeStefano, A. J.; Rose, M. J.; Sailstad, J.; Shah, V. P.; Skelly, J. P.; Swann, P. G.; Weiner, R. Pharm. Res. 2007, 24, 1962−1973. (37) Thakare, R.; Chhonker, Y. S.; Gautam, N.; Alamoudi, J. A.; Alnouti, Y. J. J. Pharm. Biomed. Anal. 2016, 128, 426−437. (38) Ellison, S. L.; Thompson, M. Analyst 2008, 133, 992−997. (39) Thompson, M.; Ellison, S. L. Accredit. Qual. Assur. 2005, 10, 82−97. (40) Kruve, A.; Auling, R.; Herodes, K.; Leito, I. Rapid Commun. Mass Spectrom. 2011, 25, 3252−3258. (41) Liu, G.; Ji, Q. C.; Arnold, M. E. Anal. Chem. 2010, 82, 9671− 9677. (42) Peters, F. T.; Remane, D. Anal. Bioanal. Chem. 2012, 403, 2155−2172. (43) Bilodeau, J.; Lafontaine, N.; Caron, P.-Y.; Viel, F.; Lachance, S.; Boudreau, N.; Levesque, A. Evaluation of Matrix Effect when Matrix Factor is not Enough for LCMSMS Bioanalytical Method. Poster for European Bioanalysis Forum 6th Open Symposium. Barcelona, Spain, Nov. 2022, 2013. (44) Thompson, M.; Ellison, S. L. R.; Wood, R. Pure Appl. Chem. 2002, 74, 835−855. (45) Huang, Y.; Louie, A.; Yang, Q.; Massenkoff, N.; Xu, C.; Hunt, P. W.; Gee, W. Bioanalysis 2013, 5, 1397−1407. (46) Hewavitharana, A. K. J. Chromatogr. A 2011, 1218, 359−361. (47) Kruve, A.; Kunnapas, A.; Herodes, K.; Leito, I. J. Chromatogr. A 2008, 1187, 58−66. (48) Matuszewski, B. K.; Constanzer, M. L.; Chavez-Eng, C. M. Anal. Chem. 1998, 70, 882−889. (49) Stahnke, H.; Kittlaus, S.; Kempe, G.; Alder, L. Anal. Chem. 2012, 84, 1474−1482. (50) German External Quality Assessment Scheme (G-EQUAS). http://www.g-equas.de.

I


Standardized Procedure for the Simultaneous ... - ACS Publications

Recommend Documents