開發具高靈敏度毛細管電泳及基質校正之串聯式液相層析質譜分析方法於生醫檢體應用

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國立臺灣大學醫學院藥學研究所博士論文

Graduate Institute of Pharmaceutical Science College of Medicine

National Taiwan University Doctoral Dissertation

開發具高靈敏度毛細管電泳及基質校正之串聯式液相層析質譜分析方法於生醫檢體應用

Development of matrix effects corrected liquid

chromatography-mass spectrometry and sensitive capillary electrophoresis methods for bio-pharmaceutical

applications

廖曉偉 Hsiao-Wei Liao

指導教授：郭錦樺博士 Advisor: Ching-Hua Kuo, Ph.D.

中華民國 103 年 2 月

Feb 2014

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致謝

感謝一直以來幫助我的各位老師及學長姐學弟妹們，有您們的幫助我才能夠順利的完成這份論文；以及感謝家人們和朋友們支持我完成博士學位的攻讀即給予我的鼓勵。首先要感謝我的指導教授郭錦樺老師，一直以來無論是實驗上或是生活上您的指導以及關心都讓人倍感窩心，能夠接受您指導真是一件既幸福又幸運的事。

感謝口試委員吳秀梅博士、何國榮博士、傅明仁博士及陳家揚博士，您們用心的建議及審查讓我論文能夠更加完整，也感謝您們給予我許多實驗上的建議和方向讓我獲益良多。

感謝 1241 大家庭裡的每一位成員們，在實驗上和生活上的幫助。感謝每一位學長姐的幫忙與指導解決我實驗上所遭遇到的問題。尤其是伊琳大姐頭和冠元小朋友，感謝您們花了許多時間與我分享實驗上的想法以及不時提供我許多意見。

感謝 1241 的每一個有趣及活潑的大家庭成員，有您們的陪伴讓實驗室裡處處充滿溫馨以及歡樂的氣氛，能遇見大家真是太好了。

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中文摘要

由於近幾年來生醫樣品分析的需求量逐漸增加，例如藥物治療監測、藥物動力學研究、篩選生物標誌、以及個人化醫療的發展，因此如何開發快速並準確的生醫樣品分析方法成為重要課題之一。液相層析搭配電噴灑電離子化質譜儀（liquid chromatography-electrospray ionization mass spectrometry）和毛細管電泳（capillary electrophoresis）是兩種常用於生醫樣品的分析平台。液相層析搭配電噴灑離子化質譜儀具有較高的靈敏度和選擇性的優點，常被用來作為生物樣品分析平台。毛細管電泳是一種具有高解析度、高分析速度、高度自動化、低成本且低汙染的分析技術。本論文採用此兩種平台發展生醫檢體的分析技術。

在生醫檢體分析中常常遇到的兩個重要問題，例如隨著樣品的高複雜度而

來的嚴重基質效應（matrix effect），以及分析物濃度過低所造成的無法定量或較

大的誤差都會影響到分析品質。基質效應常被指出會嚴重影響液相層析搭配電

噴灑電離子化質譜儀的精密度（precision）及準確性（accuracy）。因此我們發展

柱後注入內部標準品（postcolumn infused-internal standard）的校正方法來校正基質效應所造成的定量誤差，我們使用這個方法定量 25 個尿液檢體中的 6 個

benzodiazepines 藥物濃度，超過 90%結果的定量誤差小於 20%，且所有分析結果的定量誤差皆小於 30%。由於單純使用柱後注入內部標準品技術對於校正基質組成差異過大的樣品有其限制，為此，我們另外提出合併基質標準化參數

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(matrix normalization factors) 與柱後注入內部標準品的方法校正不同體液中顯著不同程度的基質效應，並且簡化定量方式。我們使用這個方法定量血液及腦脊液中的etoposide 與 etoposide catechol 濃度，確效結果顯示大於 93%分析結果之定量誤差小於 20%，且 99% 的分析結果定量誤差小於 30%。我們另以此方法應用於定量內生性代謝物（endogenous metabolites），解決過去正確定量內生性物質只能用標準品添加法(standard addition method)或同位素內標法(isotopically labeled internal standard (SIL-IS)) 的限制，我們以此方法定量血液中之 androstenedione 與 testosterone 濃度，該方法定量結果與同位素內標法定量結果之相關係數高達 0.98。

靈敏度是生醫檢體分析另一個常見的問題，為了解決這個問題，我們使用了線上濃縮（on-line concentration）的技術來提高毛細管電泳的檢測極限，以最

適化分析條件定量血液中的 posacnazole 濃度，定量極限可達到 10 ng mL^-1。另

外，我們也建立了一個毛細管膠電泳（capillary gel electrophoresis）的分析平台來同時檢測單核苷酸多態性（single nucleotide polymorphism）及拷貝數變異（copy

number variation），簡化基因檢測的步驟，我們以多重聚合媒鏈鎖反應結合毛細

管電泳法偵測 50 個 DNA 檢體 CYP2D6 基因的單核苷酸多態性及拷貝數變異，

並將分析結果與 DNA 定序法及長聚合媒鏈鎖反應法所得結果比較，各方法分析結果之相關技術大於 90%。

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本研究對於所發展的柱後注入內部標準品的校正方法，線上濃縮技術和基因檢測方法新技術皆以實際的臨床案例評估其可行性，我們證明所發展的技術具有高準確度、經濟、靈敏的優點，期望未來能透過這些技術應用於更多的臨床實例，提供準確的醫療數據，改善治療成效。

關鍵字：生醫樣品分析、液相層析搭配電噴灑離子化質譜儀、基質效應、

線上濃縮、毛細管膠電泳、柱後注入內部標準品校正方法、基質標準化參數

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Abstract

Nowadays, bio-pharmaceutical analysis gains growing importance due to the increasing needs in medication care such as therapeutic drug monitoring, biomarker discovery, and genotype testing. Liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) and capillary electrophoresis (CE) are two of the commonly used platforms for bio-pharmaceutical analysis. LC-ESI-MS is a versatile analytical tool and has been applied for many quantitative purposes because of its excellent sensitivity and selectivity. CE is an environmental friendly analytical technique which shows advantages in high resolution, high analysis rate, automation and low cost. This thesis used both platforms to develop analytical methods for bio-pharmaceutical analysis.

Two main challenges encountered in bio-pharmaceutical analysis include the serious matrix effects (MEs) come along with high sample complexity, and the low analyte concentration. MEs have been regarded as the “Achilles heel” of LC-ESI-MS because MEs cause poor precision and quantification accuracy. To overcome this problem, we proposed a postcolumn-infused internal standard (PCI-IS) strategy for universal correction of MEs in biospecimens. When the PCI-IS method was used to correct the 6 benzodiazepines in 25 real human urine samples, over 90% of the test results exhibited quantification errors of less than 20%, and all of the test results had

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quantification errors of less than 30%. As PCI-IS method could not provide good correction efficiency for different biofluids that exhibited distinct MEs, we additionally introduced matrix normalization factors (MNFs) combined with PCI-IS method to improve quantification accuracy. When using the PCI-IS method in combination with MNFs, the calibration curve generated from standard solutions can be applied to

quantify the target analytes in various biofluids. We applied this new approach to quantify etoposide and etoposide catechol in plasma and CSF. The accuracy test showed that over 93% of the data have quantification errors less than 20%, and 99% of the data have quantification errors less than 30%. We further applied the MNFs combined with PCI-IS method to quantify endogenous metabolites. In order to acquire the MNF values in the specific sample matrix without interfering by the endogenous metabolites, excessive amount of analyte was spiked in to the specific sample matrix. This method provides a new economic and effective approach to quantify endogenous metabolites.

We used the MNFs combined with PCI-IS method to quantify androstenedione and testosterone. The result showed a correlation coefficient of 0.98 for both compounds compared to the results acquired by the stable isotope labeled-internal standard method.

The sensitivity requirement is another challenge for bio-pharmaceutical analysis, especially when using CE for measurement. To solve this problem, on-line

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concentration technique was used to improve the detection limit of CE. We used the ﬁeld-ampliﬁed sample stacking (FASS) technique to quantify posaconazole

concentration in plasma samples, and the limit of quantification could reach 10 ng mL^-1. Moreover, considering that genotype testing gains high attentions for personalized medicine, we built a genotype determination method for simultaneous identification of both single nucleotide polymorphism and copy number variation by capillary gel electrophoresis. The multiplex PCR combined with CE method was applied to test 50 patients, and all of the test results were compared with the DNA sequencing method, long-PCR method and real-time PCR method. The correlation of the analytical results between the proposed method and other methods were higher than 90 %.

This study developed the PCI-IS correction method, the on-line concentration method, and genotype testing method to solve problems in bio-pharmaceutical analysis.

All of these methods had been applied to real cases to demonstrate their feasibility for clinical measurement. We anticipate these methods can provide accurate and sensitive quantitation for other clinical applications to improve the quality of medication care.

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Keywords: bio-pharmaceutical analysis, liquid chromatography-electrospray ionization mass spectrometry, matrix effects, on-line concentration, capillary gel electrophoresis, postcolumn infused-internal standard correction method, matrix normalization factors

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Table contents

Table 2.1 Accuracies (%recovery) of the 6 BZD drugs in urine at three

concentrations (n=5 for each concentration). ... 51

Table 3.1 The intra-day and inter-day precision. ... 90

Table 4.1 The quantitative results obtained from SAM, SIL-IS, and PCI-IS combined with MNF method. ... 125

Table 4.2 Quantification precision of androstenedione and testosterone by the PCI-IS combined with MNF method (RSD %) ... 126

Table 4.3 Quantification accuracy of androstenedione and testosterone by the PCI-IS combined with MNF method (n = 4, %) ... 127

Table 5.1 Precision and accuracy of the SPE-FASS method ... 164

Table 6.1 The six primers used in this study. ... 206

Table 6.2 Definition of the parameters in the simulation equation. ... 207

Table 6.3 The number of binding sites of the most common genotypes in the Asian population. ... 208

Table 6.4 The range of area percentages of each DNA fragment for the genotypes mostly found in Asian populations. ... 209

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Table 6.5 The distribution of CYP2D6 genotypes in the 50 volunteers determined by CE or the real time PCR plus long chain PCR method. 210

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Figure contents

Figure 2.1 Schematic illustrations of the instrumental setting and the performance of the PIC-IS method. ... 52

Figure 2.2 (a) MRM chromatograms of 5 different concentrations of urine matrixes spiked with 200 ng mL^-1 flunitrazepam. (b) MRM chromatograms of the PCI-IS in 5 different concentrations of urine matrixes. (c) Adjusted flunitrazepam chromatograms obtained using the PCI-IS method. ... 53

Figure 2.3 The MRM chromatogram of (a) HKP (used as PCI-IS) (b) nitrazepam, (c) diazepam, (d) estazolam, (e) temazepam, (f) flunitrazepam, and (g) flurazepam... 54

Figure 2.4 Comparison of the calibration performance (in coefficients of variation (CV)) of various PCI-ISs. Five concentrations of urine matrixes were spiked with (a) nitrazepam, (b) diazepam, (c) estazolam, (d) temazepam, (e) flunitrazepam, and (f) flurazepam at 5 different concentrations. ... 55

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Figure 2.5 The coefficients of variation (CV), before and after adjustment by internal standard or PCI-IS methods for (a) flunitrazepam, (b) nitrazepam, (c) diazepam, (d) estazolam, (e) temazepam, and (f) flurazepam responses in 5 different concentrations of urine matrixes. ... 56

Figure 2.6 Correction performance of the same concentration of BZD drugs in different urine matrixes using different PCI-ISs (in coefficients of variation (CV). Five concentrations of urine matrixes were spiked with flunitrazepam at 5 concentrations. ... 57

Figure 2.7 The structures of nordiazepam, nitrazepam, diazepam, estazolam, temazepam, flunitrazepam, flurazepam, HKP, TKDA, and TMA. ... 58

Figure 2.8 The coefficients of variation (CV) for flunitrazepam responses in 5 concentrations of urine calculated before and after adjustment by the IS method, SIL-IS method, or PCI-IS method. ... 59

Figure 2.9 The calibration curves of 6 BZD drugs in 3 different concentration urine matrixes obtained before (a-1 to f-1) or after (a-2 to f-2) PCI-IS adjustment: (a-1, a-2) nitrazepam, (b-1, b-2) diazepam, (c-1, c-2)

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estazolam, (d-1, d-2) temazepam, (e-1, e-2) flunitrazepam, and (f-1, f-2) flurazepam. ... 60

Figure 2.10 The average calibration curves of 6 BZD drugs in 3 different concentration urine matrixes obtained before (a-1 to g-1) or after (a-2 to g-2) PCI-IS adjustment: (a-1, a-2) nitrazepam, (b-1, b-2) diazepam, (c-1, c-2) estazolam, (d-1, d-2) temazepam, (e-1, e-2) flunitrazepam, and (f-1, f-2) flurazepam. ... 61

Figure 2.11 The recoveries of 6 BZD drugs spiked into 3 different urine matrixes at 5 different concentrations, calculated before and after PCI-IS adjustment. (a) nitrazepam, (b) diazepam, (c) estazolam, (d) temazepam, (e) flunitrazepam, and (f) flurazepam. ... 62

Figure 2.12 The recoveries of 6 BZD drugs spiked into 25 different human urine samples, calculated before and after adjustment by the sample dilution or PCI-IS method. (a) nitrazepam, (b) diazepam, (c) estazolam, (d) temazepam, (e) flunitrazepam, and (f) flurazepam. ... 63

Figure 3.1 The electropherograms of plasma and CSF subjected to different PPT methods. (a) A 1,000-fold dilution of the plasma sample; (b) plasma

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deproteinized by 4x volume of methanol; (c) plasma deproteinized by 2x volume of ACN; (d) CSF without any sample pretreatment; (e) CSF deproteinized by 4x volume of methanol; (f) CSF deproteinized by 2x volume of ACN. ... 91

Figure 3.2 The MRM chromatograms of (a) 500 ng mL^-1 of etoposide, (b) 100 ng mL^-1 PCI-IS (teniposide), (c) etoposide corrected by the response ratio of etoposide to PCI-IS, and (d) etoposide after correction with etoposide to PCI-IS and MNFSTD-CSF or MNFSTD-plasma in standard, plasma, and CSF biofluids. ... 92

Figure 3.3 The accuracy test results of etoposide catechol (a1, a2, and a3) and etoposide (b1, b2, and b3) before correction (a1 and b1), after correction by MNFs alone (a2 and b2), and after correction by both MNFs and the PCI-IS (teniposide) (a3 and b3) in plasma samples. ... 93

Figure 3.4 The accuracy test results of etoposide catechol (a1, a2, and a3) and etoposide (b1, b2, and b3) before correction (a1 and b1), after correction by MNFs alone (a2 and b2), and after correction by both MNFs and the PCI-IS (teniposide) (a3 and b3) in CSF samples. ... 94

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Figure 3.5 The pharmacokinetic profiles of etoposide in CSF (a and b) and plasma (c and d) and etoposide catechol in plasma (e and f) obtained from a patient with a brain malignancy undergoing etoposide treatment.

... 95

Figure 4.1 The MRM chromatograms of (a) 100 ng mL^-1 of testosterone (b) 1 ng mL^-1 of PCI-IS (progesterone) (c) corrected results by PCI-IS combined with the MNFSTD-plasma methodin standard solution, and plasma.

... 128

Figure 4.2 The correlation of SIL-IS method and PCI-IS combined with MNF method of (a) androstenedione (b) testosterone of 50 real plasma samples.

... 129

Figure 4.3 The accuracy of androstenedione (a) before PCI and MNF corrected, (b) after PCI and MNF corrected, testosterone (a) before PCI and MNF corrected, (b) after PCI and MNF corrected of 50 real plasma samples. ... 130

Figure 5.1 Structure of posaconazole and itraconazole ... 165

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Figure 5.2 CE electropherograms of samples using (a) 60% (b) 70% (c) 80%

(d) 90% methanol solution as the wash solution in SPE procedure.

Separation conditions: fused-silica capillary: 40 cm × 50 m I.D., 30 cm effective length; background electrolyte: 1.25 M formic acid; sample, 1000 ng/mL posaconazole dissolved by 0.2 M formic acid in the 95%

methanol; applied voltage: +25 kV; temperature: 25 ºC; injection: +8 kV for 0.8 min. P: posaconazole; IS: internal standard (itraconazole). ... 166

Figure 5.3 Effect of formic acid concentration in BGE on peak intensity and resolution of posaconazole and IS in FASS system. Stacking conditions:

sample, 1000 ng/mL posaconazole dissolved by 0.2 M formic acid in the 95% methanol. Other conditions are the same as those described in Fig.

5.2. ... 167

Figure 5.4 Influence of sample matrix formic acid concentration on peak intensity and theoretical plate of posaconazole in FASS system. Stacking conditions: BGE, 1.25 M formic acid; sample, 1000 ng/mL posaconazole dissolved by different formic acid concentration in the 95% methanol.

Other conditions are the same as those described in Fig. 5.2. ... 168

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Figure 5.5 Effect of methanol percentage in sample matrix on peak intensity in FASS system. Stacking conditions: BGE, 1.25 M formic acid; sample, 1000 ng/mL posaconazole dissolved by 0.2 M formic acid concentration in the different methanol percentage. Other conditions are the same as those described in Fig. 5.2. ... 169

Figure 5.6 CE electropherograms of (A) nonspiked blank human plasma and human plasma spiked with (B) 30 ng/mL (LOQ) and (C) 1000 ng/mL posaconazole. Stacking conditions are the same as those described in Fig.

2.2. P: posaconazole; IS: internal standard (itraconazole)... 170

Figure 5.7 CE electropherogram of human plasma provided by the National Taiwan University Hospital. Stacking conditions are the same as those described in Fig. 2.2. P: posaconazole; IS: internal standard (itraconazole). ... 171

Figure 6.1 The effect of PCR cycle number on DNA fragment patterns in CE chromatograms with different genotypes. (A) CYP2D6*1/*1 (GG); (B) CYP2D6*1/*10 (AG); (C) CYP2D6*10/*10 (AA). ... 211

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Figure 6.2 The simulation pattern of the commonly observed genotypes in the Asian population ... 212

Figure 6.3 Representative CE chromatograms (containing the calculated area percentage of the DNA fragments) (A), simulated DNA patterns (B), and DNA sequencing results (C) for patients identified as CYP2D6*1/*1, CYP2D6*1/*5, CYP2D6*1/*10, CYP2D6*5/*10, and CYP2D6*10/*10.

... 213

Figure 6.4 The area percentage of ARI and DARI in the HPLC chromatograms obtained from 25 patients. ... 214

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Chapter 1 Introduction

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1.1. Analytical platforms for bio-pharmaceutical analysis

During the last decades, personalized medicine has got more attentions due to the fast development in medical science. Gene testing and therapeutic drug monitoring are two of the most well characterized approaches for personalized medicine. To provide sufficient lab data for medication adjustment, effective, efficient and economic bio- pharmaceutical analysis methods are required.

The most frequently used techniques to quantify drug and biomarker concentration include capillary electrophoresis (CE), gas chromatography–mass spectrometry (GC-MS), and liquid chromatography- mass spectrometry (LC-MS). Two main challenges for bio-pharmaceutical analysis include high sample complexity and low analyte concentration, accordingly methods for bioanalysis should provide high selectivity and sensitivity. CE shows advantages of high resolution, high analysis rate, and low sample and reagent consumption. However, its’ sensitivity was poorer than LC due to the small inner diameter of the capillary and the small injection amount. The applications of on-line concentration techniques or using detectors with better sensitivity were two main approaches to improve the detection limit. GC-MS and LC-MS platforms can provide excellent sensitivity and selectivity. However, the derivatization steps were generally required in GC-MS analysis which limits its’

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applications in bio-pharmaceutical analysis. Compared to GC-MS, LC-MS shows advantages in its’ easier sample pretreatment. Nerveless, complicated sample matrix generally caused serious matrix effect which in turn resulted in large quantification errors when applying to bio-pharmaceutical analysis.

For genotype testing, several techniques have been employed. One is the separation based methods such as LC and CE. Traditional gel electrophoresis provides high through-put analysis; however, it could not provide accurate quantification. CE has the advantages of decreasing sample and buffer consumption and ease of automation.

Besides, the quantification accuracy is better for CE when compared with traditional gel electrophoresis. The sensor based methods such as the biosensors and microarray methods largely increases the analysis rate. These methods use probes coated small microarray chip for hybridization with target DNA sequence, and they could be used for high through-put screening of single nucleotide polymorphisms (SNPs) or copy number variations (CNVs). However, the analytical costs of these methods are relatively high.

The PCR based methods, for instance, real-time PCR and restriction fragment length polymorphism method can provide accurate results, but the restriction enzymes or commercial kits increase the expense of these methods.

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CE is considered as a green chemistry technique and LC-MS is one of the most widely used techniques for bioanalysis. This thesis used CE and LC-MS to develop bio-pharmaceutical analysis methods. The basic theory of both instruments and problems to be resolved in bioanalysis are depicted in the next section.

1.2. Liquid chromatography-electrospray ionization mass spectrometry

(LC-ESI-MS)

Liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) is a versatile analytical tool and has been applied to many fields such as bioanalysis, and environmental science during the past decade. [1-5] Higher sensitivity and selectivity make LC-MS became a powerful qualitative and quantitative technique for complicated clinical samples.

1.2.1. Matrix effects (MEs)

Matrix effects (MEs) is one of the important factors that seriously deteriorate the quantitative accuracy of LC-ESI-MS. When analyzing complicated biological samples,

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MEs will give rise to the response changes that can be divided into ion suppression and ion enhancement.

The exact mechanisms of MEs are not yet fully understood. The ionization processes of LC-ESI-MS involve solution phase and gas phase, and the MEs would exert an impact in both phases. [6] In the liquid phase, co-eluting compounds affect compound ionization mainly through four mechanisms. The first mechanism is the competition for the available charges and the access to the droplet surface between analyte and co-eluting compounds in the liquid phase. [7-9] The second mechanism is the existence of co-eluting salts and charged compounds that deteriorate the signal intensity by influence the conductivity and the surface tension of the droplets. [10] The third mechanism arise from the formation of solid analyte inclusion particles with nonvolatile materials, and the nonvolatile materials caused ionization suppression is chemical structure independent. [11] The last mechanism affecting MEs is ion pair formation between analyte and co-eluting compounds. When mobile phase additives or co-eluting compounds have complementary charges, they will act as the ion-pairing reagents with analyte ions and neutralize charged analyte. [12-14] The mechanisms responsible for MEs happened in the gas phase are various. The analyte can be transferred into the gas phase as a charge form, or clustered with other co-eluting

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molecules. The neutralization of charged analytes and clusters with other co-eluting molecules will interrupt charge transfer or decrease the amount of charged analytes and changes the signal responses. [6, 12, 15]

Several approaches can reduce the influence of MEs, such as sample injection amounts reduction, samples dilution, sample clean-up procedure, and improving LC separation. [6, 16] These approaches are suffering from reducing sensitivity or increasing analytical time. The use of the ionization sources that are less affected by MEs such as atmospheric pressure chemical ionization (APCI) and atmospheric pressure photo ionization (APPI) is another approach to decrease MEs. However, sensitivity will be sacrificed in some cases and other ionization sources may not be available in some laboratories.

1.2.2. Calibration of MEs

The general approach to access the MEs is by comparing the signal intensities of analytes between matrix spiked sample and standard solution. Post-column infusion (PCI) of analytes is another well-known method to evaluate the MEs at each time point.

When performing this method, target analytes were infused by the PCI approach, while

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analyte-free sample matrix was injected into the analytical column. The MEs at each time point can be calculated through the entire runtime with this approach.

Stahnke et al. had established a matrix effect calibration method for analyzing pesticides in 20 plant matrixes using PCI of a monitor substance. [17] However, each sample must be analyzed twice when performing their method with PCI (with or without post-column infusing these target analytes) to calculate the MEs at each retention time. Moreover, in some cases, it is difficult to obtain real blank matrix.

Internal standard (IS) method has been widely applied to calibrate matrix effect.

An appropriate IS may be a structural analogue or chemicals with similar physicochemical properties with target analyte. However, because of the different retention times of target analytes and ISs, different coeluting compounds may be encountered, leading to poorly corrected results. A stable isotopically labeled internal standard (SIL-IS) that coelutes with the analyte can overcome this problem and is considered to be an ideal internal standard. Since SIL-IS shows almost identical physicochemical properties as target analyte, it considered as the gold standard to calibrate MEs.

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1.3. Capillary electrophoresis (CE)

CE is an efficient separation technique available for the analysis of both large and small molecules. The use of CE for the detection of biological analytes can be traced to1960s. CE has the advantages of high resolution, high analysis rate, automation and low cost, which make it as a powerful tool for clinical analysis. It is considered as a green chemistry technique because the organic solvent consumption of this method is very low. Based on different separation mechanisms, there are several separation modes in CE for analyzing different types of analytes. Among the various separation modes, capillary zone electrophoresis (CZE), micellar electrokinetic chromatography (MEKC), capillary gel electrophoresis (CGC), isotachophoresis, capillary isoelectric focusing (cIEF), and capillary electrochromatography (CEC) are the most widely used modes. In the second part of this thesis, we apply MEKC mode and CGE modes for bio-pharmaceutical analysis.

1.3.1. Capillary zone electrophoresis (CZE)

CZE had been widely used for analyzing biological samples. [18-23] Thru CZE separation, the analytes can then be separated by their electrophoretic mobilities, where analytes with higher electrophoretic mobilities will move quicker towards the electrodes.

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The electrophoretic mobilities of analytes were mainly dependent on the different charge states of analytes, back ground solution (BGS) viscosity, and the ion radius.

Under the same field strength condition, charged analytes can be separated when their electrophoretic mobilities are different. However, neutral analytes can’t be separated by CZE because they will all migrate with the electroosmotic flow.

1.3.2. Micellar electrokinetic chromatography (MEKC)

In 1985, Terabe et. al initiated MEKC separation mode in CE. The fundamental principle of MEKC is the partition of analytes into the micelles, and the micelles can provide mobility for these analytes. [24-26] The micelles were formed by the surfactants, which possess a hydrophilic head and a hydrophobic tail. In order to form micelles, the surfactant concentration in the BGS should higher than the critical micelle concentration (CMC). Through MEKC approach, analytes can be separated based on the difference in their lipophilicity. Therefore, MEKC can separate both neutral and charged molecules through the addition of micelles in the BGE which widened the analytical scope for CE analysis.

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1.3.3. Capillary gel electrophoresis (CGE)

CGE performs gel electrophoresis on the CE platform. [27-29] CGE has been recognized as a powerful separation technique for large molecules such as

oligonucleotides and proteins. Because the electrophoretic mobility of oligonucleotides and proteins doesn’t change with the length of oligonucleotides, the sieving matrix was

employed for improving separation. The crosslinked or noncrosslinked sieving matrixes form the well-defined pore or dynamic pore structure are widely used for oligonucleotides and proteins separation. The noncrosslinked linear polymer networks provide much higher flexibility and comparatively low viscosity than the crosslinked gels. [30-35] Consequently, the noncrosslinked linear polymer provides a more simple and convenient way for performing capillary gel electrophoresis.

1.3.4. On-line concentration techniques

Although CE has many advantages, the poor sensitivity is its major limitation.

Accordingly, when using this method to quantify drugs and their metabolites in blood samples, the sensitivity is not always sufficient. Two general approaches have been adopted to improve the detection sensitivity. One uses more sensitive detectors such as

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fluorescence, electrochemical or mass spectrometry detector, and the other employs on-line concentration strategies.

1.3.4.1. Sweeping

Sweeping is the phenomenon of “the picking and accumulating process” of analytes by the pseudostationary phase. [36-39] The sweeping phenomenon occurs through the interaction of the pseudostationary phase in the back ground electrolyte and the analyte in the sample zone without the addition of pseudostationary phase. During the separation process, the pseudostationary phase pass through the sample zone and the analytes in the sample zone start to partition into the pseudostationary phase and accumulated. The affinity between analyte and pseudostationary phase plays an important when applying sweeping technique. Generally, the higher affinity gives better concentrating effect.

1.3.4.2. Field amplified sample stacking (FASS)

FASS achieved sample stacking by preparing charged analytes in a diluted sample matrix that the conductivity of the sample matrix is much lower than that of the back

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ground electrolyte (BGE). [40-43] When the voltage was applied, the field strength in the sample matrix is higher than the BGE, which results in analyte stacking at the boundary between sample matrix and BGE. Through this approach, the signal intensity was achieved 1000-folds increase for analyzing amidarone and desethylamiodarone.

[41]

1.4. Research aim and organization of this thesis

Personalized medicine is the trend in medical care. This thesis aims to establish effective and economic bio-pharmaceutical analysis methods to facilitate personalized medicine. We used CE and LC-MS as our analytical techniques. Two of the main challenges in bio-pharmaceutical analysis include high sample complexity and low analyte concentration. LC-ESI-MS is a very sensitive technique, but the high sample complexity of bio-samples causes serious MEs which results in quantification errors. In the first part of this thesis, we aimed to establish effective and economic approaches to resolve MEs caused quantification errors. Postcolumn infusion strategy has been introduced for many years, and this method shows advantages in being more economic compared with SIL-IS method. Although this method has been introduced for many

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years, very few studies investigated on using it to improve quantification accuracy in bio-pharmaceutical analysis.

Another challenge in the bio-pharmaceutical analysis is the low concentration of target analytes. Although sensitivity is generally not an issue when using LC-MS for measurement, LC-MS is a relative expensive instrument. CE is a green chemistry technique and provides advantages in low instrumental cost. However, the detection sensitivity limits its’ applications on bio-pharmaceutical analysis. In the second part of this thesis, we aimed to resolve the intrinsic limitations in CE and expand the using of this green chemistry technique on clinical measurement. We applied on-line concentration methods to improve the detection sensitivity of CE. We also used CE for genotype determination. In order to simultaneous determination of several genotypes, we established equations to simulate the DNA patterns of samples with various genotypes.

This thesis composed of 7 chapters. The first part using PCI-IS to correct MEs in LC-ESI-MS starts from chapter 2 to 4. Chapter 2 initiated the concept of using a postcolumn-infused internal standard for correcting the matrix effects of biospecimens in LC-ESI-MS. Chapter 3 and Chapter 4 additionally added the concept of matrix normalization factors (MNFs) to PCI-IS to expand the scope of PCI-IS in various

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situations. Chapter 3 emphasized on quantification of target analytes in various biofluids using the PCI-IS and MNF combination approach in LC-ESI-MS. Chapter 4 focused on resolving the problems of quantification of endogenous metabolites in LC-ESI-MS. The second part using CE for clinical measurement starts from chapter 5 to 6. Chapter 5 focused on using on-line sample preconcentration technique to resolve sensitivity problem of CE and Chapter 6 extended the application scope of CE for genotyping of drug metabolism gene. Finally, we gave our conclusion and perspective of the whole study in Chapter 7.

1.5. References:

[1] H.H. Maurer, Multi-analyte procedures for screening for and quantification of drugs in blood, plasma, or serum by liquid chromatography-single stage or tandem mass spectrometry (LC-MS or LC-MS/MS) relevant to clinical and forensic toxicology. Clin Biochem, 38 (2005) 310-318.

[2] F.T. Peters, D. Remane, Aspects of matrix effects in applications of liquid chromatography-mass spectrometry to forensic and clinical toxicology--a review.

Analytical and Bioanalytical Chemistry, 403 (2012) 2155-2172.

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[3] H.H. Maurer, Current role of liquid chromatography-mass spectrometry in clinical and forensic toxicology. Analytical and Bioanalytical Chemistry, 388 (2007) 1315-1325.

[4] W.M.A. Niessen, P. Manini, R. Andreoli, Matrix effects in quantitative pesticide analysis using liquid chromatography-mass spectrometry. Mass Spectrometry Reviews, 25 (2006) 881-899.

[5] R. Dams, M.A. Huestis, W.E. Lambert, C.M. Murphy, Matrix effect in bio-analysis of illicit drugs with LC-MS/MS: Influence of ionization type, sample preparation, and biofluid. Journal of the American Society for Mass Spectrometry, 14 (2003) 1290-1294.

[6] H. Trufelli, P. Palma, G. Famiglini, A. Cappiello, An Overview of Matrix Effects in Liquid Chromatography-Mass Spectrometry. Mass Spectrometry Reviews, 30 (2011) 491-509.

[7] S. Souverain, S. Rudaz, J.L. Veuthey, Matrix effect in LC-ESI-MS and LC-APCI-MS with off-line and on-line extraction procedures. Journal of Chromatography A, 1058 (2004) 61-66.

[8] H.R. Liang, R.L. Foltz, M. Meng, P. Bennett, Ionization enhancement in atmospheric pressure chemical ionization and suppression in electrospray ionization between target drugs and stable-isotope-labeled internal standards in quantitative liquid

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chromatography/tandem mass spectrometry. Rapid Commun Mass Spectrom, 17 (2003) 2815-2821.

[9] C. Muller, P. Schafer, M. Stortzel, S. Vogt, W. Weinmann, Ion suppression effects in liquid chromatography-electrospray-ionisation transport-region collision induced dissociation mass spectrometry with different serum extraction methods for systematic toxicological analysis with mass spectra libraries. Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences, 773 (2002) 47-52.

[10] F. Beaudry, P. Vachon, Electrospray ionization suppression, a physical or a chemical phenomenon? Biomedical Chromatography, 20 (2006) 200-205.

[11] R. King, R. Bonfiglio, C. Fernandez-Metzler, C. Miller-Stein, T. Olah, Mechanistic investigation of ionization suppression in electrospray ionization. Journal of the American Society for Mass Spectrometry, 11 (2000) 942-950.

[12] S.A. Gustavsson, J. Samskog, K.E. Markides, B. Langstrom, Studies of signal suppression in liquid chromatography-electrospray ionization mass spectrometry using volatile ion-pairing reagents. Journal of Chromatography A, 937 (2001) 41-47.

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[13] J. Eshraghi, S.K. Chowdhury, Factors Affecting Electrospray-Ionization of Effluents Containing Trifluoroacetic-Acid for High-Performance Liquid Chromatography/Mass Spectrometry. Analytical Chemistry, 65 (1993) 3528-3533.

[14] S.L. Zhou, K.D. Cook, A mechanistic study of electrospray mass spectrometry:

Charge gradients within electrospray droplets and their influence on ion response.

Journal of the American Society for Mass Spectrometry, 12 (2001) 206-214.

[15] L. Tang, P. Kebarle, Dependence of Ion Intensity in Electrospray Mass-Spectrometry on the Concentration of the Analytes in the Electrosprayed Solution.

Analytical Chemistry, 65 (1993) 3654-3668.

[16] A. Van Eeckhaut, K. Lanckmans, S. Sarre, I. Smolders, Y. Michotte, Validation of bioanalytical LC-MS/MS assays: evaluation of matrix effects. J Chromatogr B Analyt Technol Biomed Life Sci, 877 (2009) 2198-2207.

[17] H. Stahnke, T. Reemtsma, L. Alder, Compensation of Matrix Effects by Postcolumn Infusion of a Monitor Substance in Multiresidue Analysis with LC-MS/MS.

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[18] E.M. Ban, D. Kim, E.A. Yoo, Y.S. Yoo, Separation and determination of neuropeptides in human plasma by capillary zone electrophoresis. Analytical Sciences, 13 (1997) 489-492.

[19] R. Arias, R.M. Jimenez, R.M. Alonso, M. Telez, I. Arrieta, P. Flores, E.

Ortiz-Lastra, Determination of the beta-blocker atenolol in plasma by capillary zone electrophoresis. Journal of Chromatography A, 916 (2001) 297-304.

[20] C. Coors, H.G. Schulz, F. Stache, Development and Validation of a Bioanalytical Method for the Quantification of Diltiazem and Desacetyldiltiazem in Plasma by Capillary Zone Electrophoresis. Journal of Chromatography A, 717 (1995) 235-243.

[21] H.J.E.M. Reeuwijk, U.R. Tjaden, J. van der Greef, Development and validation of a bioanalytical assay for (E)-5-(2-bromovinyl)-2 '-deoxyuridine in plasma by capillary zone electrophoresis. Journal of Chromatography B, 726 (1999) 269-276.

[22] M. Karazniewicz-Lada, F. Glowka, G. Oszkinis, Capillary Zone Electrophoresis method for determination of (+)-S clopidogrel carboxylic acid metabolite in human plasma and urine designed for biopharmaceutic studies. Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences, 878 (2010) 1013-1018.

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[23] J. Luksa, D. Josic, Determination of Cimetidine in Human Plasma by Free Capillary Zone Electrophoresis. Journal of Chromatography B-Biomedical Applications, 667 (1995) 321-327.

[24] J.P. Quirino, S. Terabe, Exceeding 5000-fold concentration of dilute analytes in micellar electrokinetic chromatography. Science, 282 (1998) 465-468.

[25] K. Otsuka, S. Terabe, T. Ando, Electrokinetic Chromatography with Micellar Solutions - Separation of Phenylthiohydantoin-Amino Acids. Journal of Chromatography, 332 (1985) 219-226.

[26] S. Terabe, K. Otsuka, T. Ando, Electrokinetic Chromatography with Micellar Solution and Open-Tubular Capillary. Analytical Chemistry, 57 (1985) 834-841.

[27] Grossbac.U, Acrylamide Gel Electrophoresis in Capillary Columns. Biochimica Et Biophysica Acta, 107 (1965) 180-&.

[28] C. Losticky, T. Bednarik, A Modification of Capillary Start for Zonal Electrophoresis in Agar Gel. Chemicke Listy, 62 (1968) 845-&.

[29] M.A. Danilovskii, Investigation of the Constitutive Proteins of Brain Structures by Electrophoresis in a Continuous Polyacrylamide-Gel Gradient in Capillary Tubes.

Bulletin of Experimental Biology and Medicine, 86 (1978) 1544-1547.

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[30] A. Guttman, J. Horvath, N. Cooke, Influence of Temperature on the Sieving Effect of Different Polymer Matrices in Capillary Sds Gel-Electrophoresis of Proteins.

[31] K. Tsuji, Evaluation of Sodium Dodecyl-Sulfate Non-Acrylamide, Polymer Gel-Filled Capillary Electrophoresis for Molecular-Size Separation of Recombinant Bovine Somatotropin. Journal of Chromatography A, 652 (1993) 139-147.

[32] K. Tsuji, Sodium Dodecyl-Sulfate Polyacrylamide Gel-Filled and Replaceable Polymer-Filled Capillary Electrophoresis for Molecular-Mass Determination of Proteins of Pharmaceutical Interest. Journal of Chromatography B-Biomedical Applications, 662 (1994) 291-299.

[33] R. Sonoda, H. Nishi, K. Noda, Capillary gel electrophoresis of oligonucleotides using polymer solutions. Chromatographia, 48 (1998) 569-575.

[34] A. Guttman, Gel and polymer-solution mediated separation of Biopolymers by capillary electrophoresis. Journal of Chromatographic Science, 41 (2003) 449-459.

[35] X.T. Song, L. Li, H.F. Chan, N.H. Fang, J.C. Ren, Highly efficient size separation of CdTe quantum dots by capillary gel electrophoresis using polymer solution as sieving medium. Electrophoresis, 27 (2006) 1341-1346.

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[36] J.P. Quirino, S. Terabe, P. Bocek, Sweeping of neutral analytes in electrokinetic chromatography with high-salt-containing matrixes. Analytical Chemistry, 72 (2000) 1934-1940.

[37] J.P. Quirino, S. Terabe, Approaching a million-fold sensitivity increase in capillary electrophoresis with direct ultraviolet detection: Cation-selective exhaustive injection and sweeping. Analytical Chemistry, 72 (2000) 1023-1030.

[38] J.P. Quirino, S. Terabe, Sweeping of analyte zones in electrokinetic chromatography. Analytical Chemistry, 71 (1999) 1638-1644.

[39] L.P. Quirino, S. Terabe, K. Otsuka, J.B. Vincent, G. Vigh, Sample concentration by sample stacking and sweeping using a microemulsion and a single-isomer sulfated beta-cyclodextrin as pseudostationary phases in electrokinetic chromatography. Journal of Chromatography A, 838 (1999) 3-10.

[40] Z.Y. Liu, P. Sam, S.R. Sirimanne, P.C. Mcclure, J. Grainger, D.G. Patterson, Field-Amplified Sample Stacking in Micellar Electrokinetic Chromatography for on-Column Sample Concentration of Neutral Molecules. Journal of Chromatography A, 673 (1994) 125-132.

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[41] C.X. Zhang, W. Thormann, Head-column field-amplified sample stacking in binary system capillary electrophoresis: A robust approach providing over 1000-fold sensitivity enhancement. Analytical Chemistry, 68 (1996) 2523-2532.

[42] D. Martinez, F. Borrull, M. Calull, Sample stacking using field-amplified sample injection in capillary zone electrophoresis in the analysis of phenolic compounds.

Journal of Chromatography A, 788 (1997) 185-193.

[43] J.Z. Song, H.F. Chen, S.J. Tian, Z.P. Sun, Determination of metformin in plasma by capillary electrophoresis using field-amplified sample stacking technique. Journal of Chromatography B, 708 (1998) 277-283.

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Chapter 2 Using a Postcolumn-Infused Internal Standard for Correcting

the Matrix Effects of Urine Specimens in LC-ESI-MS

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2.1. Introduction

Over the past decade liquid chromatography-electrospray ionization mass spectrometry (LC-ESI-MS) has become a versatile analytical tool. The high sensitivity and selectivity of LC-MS render it a powerful tool for analyzing complicated samples.

Chromatographic separation and sample preparation are often minimized to meet the demands of high-throughput analysis.[1] Matrix effects (MEs) are a major problem affecting the quantitative accuracy of the analysis of complicated samples, especially in fast analysis with little separation. Compounds that coelute during LC may cause ion enhancement or ion suppression in ESI and may thus result in quantification errors.[2, 3]

Because MEs can seriously impact the limit of detection, limit of quantification, linearity, accuracy, and precision, they have been recently discussed in several review articles.[4, 5]

Urine specimens are one of the most frequently encountered biological fluids in the bioanalytical lab. One of the main challenges in the quantification of chemicals in urine specimens originates from the great diversity of urine concentrations between individuals. Urine concentration is significantly affected by an individual’s diet, water uptake and also the time at which the sample is taken. The large differences in

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individual urine concentrations result in high variations in matrix effects encountered in different urine specimens. Several approaches have been proposed to reduce MEs, such as diluting samples, employing sample purification procedures, and improving LC separation.[2, 5] These approaches suffer from reduced sensitivity or increased analytical time. Another approach for decreasing MEs is the use of ionization techniques that are less affected by MEs, such as atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI).[6, 7] However, sensitivity may be sacrificed, and alternative ionization sources may not always be available. Internal standards (ISs) are regularly used to correct the signal alteration arising from MEs. Structural analogues of the target analyte are generally selected as internal standards because they possess similar physicochemical properties to the target analyte. However, because of the different retention times of target analytes and ISs, different coeluting compounds may be encountered, leading to poorly corrected results.

A stable isotopically labeled internal standard (SIL-IS) that coelutes with the analyte can overcome this problem and is considered to be an ideal internal standard.[8] Even though SIL-ISs have been used extensively, it have been noticed that SIL-IS may have different retention times than the target analyte due to the deuterium isotope effect.[7, 9, 10] Other problems, such as the isotopic purity of the SIL-IS and cross-talk between

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MS/MS channels, should also be noted.[11] Most importantly, SIL-ISs are generally expensive and may not be commercially available. Thus, a more economical and effective method is required for overcoming MEs.

Postcolumn introduction of an internal standard in LC-MS/MS has been originally proposed by Bernard et al. to correct quantitative errors associated with matrix signal suppression.[12, 13] Stahnke et al. later modified this method for analyzing pesticides.

Each sample must be analyzed twice when applying their method (with or without post-column infusing these target analytes) to calculate the MEs at each retention time.[14] In addition, direct using the target analytes to calculate MEs may face problems if true blank extract is unavailable.

Benzodiazepines are a class of CNS-depressants that are frequently used to treat sleeping disorders, anxiety, increased muscle tone and epilepsy.[15] However, these drugs have been increasingly abused and have caused drug-facilitated sexual assault and traffic accidents over the past few years.[15-17] Therefore, BZD drugs are currently categorized as controlled drugs in many countries. In this study we propose a postcolumn-infused internal standard (PCI-IS) method for correcting the MEs of urine specimens in LC-ESI-MS. We selected BZD drugs as our test chemicals, and the cut-off concentrations of these BZD drug in urine are 300 ng mL^-1 according to the regulations

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reported by the Ministry of Health and Welfare, Republic of China. The MEs of urine specimens were corrected by dividing the target analyte signal intensity by the PCI-IS signal intensity. The most important parameters for improving quantification accuracy were investigated. The performance of the PCI-IS method was compared with the traditional IS and SIL-IS methods. Then, the quantification accuracy of PCI-IS correction was determined by spiking 6 BZD drugs into 25 real human urine samples for evaluating the applicability of the PCI-IS method.

2.2. Experimental

2.2.1. Chemicals

Nitrazepam, flurazepam, diazepam, estazolam, temazepam, flunitrazepam, flunitrazepam-d7, and nordiazepam were purchased from Cerilliant (Round Rock, Texas, USA). Hexakis(1H,1H,3H-perfluoropropoxy)phosphazene (HKP) was purchased from Apollo Chemical (Graham, NC). Acetonitrile (ACN) was obtained from J.T. Baker (Phillipsburg, NJ). MS-grade methanol was purchased from Scharlau Chemie (Sentmenat, Barcelona, Spain). Tetrakis(decyl)ammonium bromide (TKDA), tetramethylammonium iodide (TMA), and formic acid solution were purchased from

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Sigma (St. Louis, MO, USA). All reagents and solvents were of either analytical or chromatographic grade.

2.2.2. Sample preparation

Protein was precipitated by mixing 40 L of a urine sample with 160 L of

methanol. The deproteinized sample was centrifuged at 10,000 g for 15 min, and the supernatant was then filtered through a 0.22-m PP membrane (RC-4, Sartorius,

Göttingen, Germany) before UPLC-ESI-MS analysis. To prepare the urine used to construct test models, pooled urine samples were diluted with deionized water to generate 20, 40, 60, 80, and 100% urine solutions. All of the BZD drugs were spiked at 10, 50, 150, 250, 500 ng mL^-1.

The 25 real urine samples used to test the quantification accuracy of the developed adjustment method were collected from 4 healthy volunteers at different time points.

2.2.3. UHPLC-ESI-MS system

LC analyses were performed using an Agilent 1290 UHPLC system equipped with a binary solvent pump, an autosampler, a sample reservoir, and a column oven (Agilent

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Technologies, Waldbronn, Germany). Postcolumn infusions were accomplished with an Agilent 1260 quaternary solvent pump. The mass spectrometric analysis was performed using an Agilent 6460 triple quadrupole system (Agilent Technologies, Waldbronn, Germany). A Kinetex C18 2.1×50 mm (2.6 μm) column (Phenomenex, Torrance, USA) was employed for separations.

The mobile phase consisted of 0.1% aqueous formic acid (solvent A) and 0.1%

formic acid in ACN (solvent B). A 0.3 mL min^-1 linear gradient elution was used: 0-2 min, 20-95% B; 2-3 min, 95% B; and 3-4.5 min, column re-equilibration with 20% B.

The sample reservoir and column oven were maintained at 4 °C and 40 °C, respectively.

The injection volume was 5 L. Positive electrospray ionization mode was utilized with

the following parameters: a 325 °C dry gas temperature, a 7 L min^-1dry gas flow rate, a 45 psi nebulizer pressure, a 325 °C sheath gas temperature, an 11 L min^-1 sheath gas flow rate, a 3500 V capillary voltage, and a 500 V nozzle voltage. MS acquisition was executed in multiple reaction monitoring (MRM) mode. The transitions for HKP, TKDA,

TMA, flurazepam, flunitrazepam-d7, flunitrazepam, temazepam, estazolam, diazepam, nitrazepam, and nordiazepam were m/z 922.0→790.1, 578.7→310.3, 74.1→59.1, 388.2→134, 321.1→246.1, 314.1→183, 301.1→106, 295.1→205.1, 285.1→193, 282.1→152, and 271.1→140, respectively.

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PCI-ISs were dissolved in ACN at 100 ng mL^-1 and introduced into the ESI interface at a 0.1 mL min^-1flow rate.

2.2.4. PCI-IS method

The PCI-IS method used a postcolumn infusion strategy to correct MEs in ESI-MS (Figure 2.1). The MEs at each time point were measured using a postcolumn-infused internal standard (PCI-IS). Using the PCI-IS response changes, the degree of ion suppression (or ion enhancement) at each time point allowed MEs to be calculated. The basic concept of the PCI-IS method is described by Eq. 1.

^𝑅_𝑅^{𝑎𝑛𝑎𝑙𝑦𝑡𝑒,𝑥}

𝑃𝐶𝐼−𝐼𝑆,𝑥 = ^𝐴_𝐴^{𝑎𝑛𝑎𝑙𝑦𝑡𝑒,𝑥}^∗𝐶^{𝑎𝑛𝑎𝑙𝑦𝑡𝑒,𝑥}

𝑃𝐶𝐼−𝐼𝑆,𝑥∗𝐶_{𝑃𝐶𝐼−𝐼𝑆,𝑥} (Eq. 1)

Where A represents the ability of the analyte to generate signals, which is determined by the physicochemical properties (e.g., pKa, proton affinity, hydrophobicity, and hydrophilicity) of the analyte. A is influenced by the surrounding ionization conditions (e.g., mobile phase viscosity, surface tension, and nonvolatile components in the coeluent). Ranalyte,x and RPCI-IS,x represent the responses of the analyte and the PCI-IS at time point x. C represents the concentration.

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When Eq. 1 was applied, CPCI-IS,x was held constant. If a suitable PCI-IS is selected to ensure similar Aanalyte,x and APCI-IS,x, the analyte to PCI-IS response ratios should be proportional to the analyte concentration (Eq.2):

^𝑅_𝑅^{𝑎𝑛𝑎𝑙𝑦𝑡𝑒,𝑥}

𝑃𝐶𝐼−𝐼𝑆,𝑥 ∝ (𝐶_{𝑎𝑛𝑎𝑙𝑦𝑡𝑒,𝑥}) (Eq. 2) We used Eq. 2 to adjust the analyte signal intensity and calculate the analyte concentration in LC-ESI-MS. For each chromatogram, the analyte to PCI-IS signal intensity ratio at each time point was utilized to generate a new corrected chromatogram.

All of the data obtained using the Agilent triple quadrupole was converted into the comma separated values (csv) format and processed with Microsoft Excel 2007 (Albuquerque, NE). The information in the csv file included mass transition, retention time, and signal intensity.

The MRM acquisition rate was set to 1 spectra s^-1. The PCI-IS method assumed that the response ratio of the target analyte to PCI-IS was proportional to the target analyte concentration. The analyte signal intensities at each time point in the chromatogram were divided by the PCI-IS responses at the identical retention times, and the ratios were used to generate the new adjusted chromatogram.

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2.2.5. Precision and accuracy tests

To validate the established PCI-IS method, 25 real urine samples spiked with known amounts of 6 BZD drugs were analyzed. Flunitrazepam, estazolam, diazepam, nitrazepam were tested at low, medium, and high concentrations of 10, 150, 500 ng mL^-1, respectively. Flurazepam and temazepam were tested at low, medium, and high concentrations of 50, 150, 500 ng mL^-1, respectively. The accuracies were tested four times. The intra- and inter-day precisions were tested four times a day for 3 days and expressed as their relative standard deviations (RSD).

2.3. Results

2.3.1. Using PCI-IS to correct MEs in urine

Before using the PCI-IS method to calibrate matrix effects, the concentration of and infusion rate of the PCI-IS were optimized. To obtain optimal correction results, enough PCI-IS should be infused to prevent the system from being unstable, but too much PCI-IS will give rise to ion suppression. The repeatability and analyte signal intensity of the PCI-IS system were determined. Finally, the flow rate of the postcolumn

開發具高靈敏度毛細管電泳及基質校正之串聯式液相層析質譜分析方法於生醫檢體應用

國立臺灣大學醫學院藥學研究所 博士論文

Graduate Institute of Pharmaceutical Science College of Medicine

National Taiwan University Doctoral Dissertation

開發具高靈敏度毛細管電泳及基質校正之串聯式液相 層析質譜分析方法於生醫檢體應用

Development of matrix effects corrected liquid

chromatography-mass spectrometry and sensitive capillary electrophoresis methods for bio-pharmaceutical

applications

廖曉偉 Hsiao-Wei Liao

指導教授：郭錦樺 博士 Advisor: Ching-Hua Kuo, Ph.D.

中華民國 103 年 2 月

Feb 2014

致 謝

中文摘要

Abstract

Contents

Table contents

Figure contents

Chapter 1

Introduction

Chapter 2

Using a Postcolumn-Infused Internal Standard for Correcting

the Matrix Effects of Urine Specimens in LC-ESI-MS

國立臺灣大學醫學院藥學研究所博士論文

開發具高靈敏度毛細管電泳及基質校正之串聯式液相層析質譜分析方法於生醫檢體應用

指導教授：郭錦樺博士 Advisor: Ching-Hua Kuo, Ph.D.

致謝