TY - JOUR
AU - Baymeeva, Natalia V
AB - Abstract A quantitative method was developed to support therapeutic drug monitoring of eight antipsychotic drugs: chlorpromazine, haloperidol, zuclopenthixol, clozapine, risperidone, quetiapine, aripiprazole or olanzapine and some active metabolites (dehydroaripiprazole, N-desmethylclozapine and 9-hydroxyrisperidone) in human serum. Separation of the compounds was achieved using a Zorbax SB-C18 (150 mm × 4.6 mm, 5 μm) column and mass-spectrometric detection in multiple reaction monitoring mode. Human blood samples were collected in vacutainer tubes and the analytes were extracted with methyl-tert-butyl ether. The lower limits of quantitation were equal 0.5–1 ng/mL for all analytes. The method was applied with success to serum samples from schizophrenic patients undergoing polypharmacy with two or more different antipsychotic drugs. Precision data, accuracy results were satisfactory, and no interference from other psychotropic drugs was found. Hence, the method is suitable for the TDM of the analytes in psychotic patients’ serum. Introduction Therapeutic drug monitoring (TDM) is an important test in clinics because the quantification of the drug level in the blood during therapy helps to estimate whether the current medicine prescription is appropriate for the patient. Antipsychotic drugs (APs) belong to the drugs that require TDM to control their concentrations in plasma/serum and to adjust the dosing regimen not only to suppress the psychotic activity but also to minimize the side effects (1, 2). Additionally, a significant part of psychiatric patients is treated with more than one AP drug in the routine practice to boost their respective efficacy. Thus, it is necessary to develop a rapid and reliable assay that is suitable for determination of multiple APs in a single run. APs have been determined in biological matrices by numerous methods: immunochemical, electromigration or electrophoretic and chromatographic methods, which provide high detection sensitivity and determination of several analytes (3, 4). Immunochemical methods, in comparison with chromatographic methods, do not allow simultaneous determination of a drug and its metabolites. Another disadvantage is the cross-reaction: the determination of not only the native molecule, but also all metabolites containing the antigen (5). That leads to overestimated results. Besides, antibodies too many analytes are not commercially available. Gas chromatography is limited by the thermolability of the compounds; often require chemical derivatization that increases the time of analysis (6). Due to the high sensitivity, selectivity, speed and cost effectiveness of multiple reaction monitoring (MRM) mode, liquid chromatography coupled to mass spectrometer (LC–MS) has become the mainstay in analysis of complex biological samples. In the clinical field, many liquid chromatographic–tandem mass spectrometry (LC–MS-MS) assays have been developed for TDM (7, 8). This approach allows the highly specific serum level measurement of many drugs and thereby improves the quality of TDM. In the present study, we extended our previously validated assay (9) to a common assay for the quantification of eight APs (chlorpromazine, haloperidol, zuclopenthixol, clozapine, risperidone, quetiapine, aripiprazole or olanzapine) and some their active metabolites (dehydroaripiprazole, N-desmethylclozapine and 9-hydroxyrisperidone) in human serum. The choice of AP was stipulated by their usage frequency in the hospital. The methodology used to measure APs and their metabolites is based on simple one-step liquid–liquid extraction (LLE) into methyl-tert-butyl ether (MTBE). Anastrozole was selected as the internal standard (IS), because its chromatographic behavior and extraction efficiency were similar to those of analytes (10). Experimental Chemicals and materials Methanol was from Fisher Scientific (USA) and acetonitrile from Lab-Scan (Poland). Formic acid was purchased from Sigma-Aldrich (St. Louis, MO, USA). Chlorpromazine (CPZ), haloperidol (HAL), zuclopenthixol (ZUC), clozapine (CLO), risperidone (RIS), quetiapine (QTP), aripiprazole (ARI), olanzapine (OLA), N-desmethylclozapine (also named as norclozapine, NOR) and 9-hydroxyrisperidone (also known as paliperidone, PAL) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Aripiprazole (ARI) and dehydroaripiprazole (DHA) were from Santa Cruz Biotechnology Inc. (USA). Anastrozole was obtained from Akrihin (Russia). Deionized water was prepared from distilled water using Simplicity UV System (Millipore, USA). All other chemicals and solvents were of analytical grade and used as received. Biological samples Human blood was obtained from the Mental Health Research Center (Moscow, Russia) from patients diagnosed with schizophrenia. The protocol of the study obtained an approval by the local ethics committee of MHRC: Protocol No. 2 from 27 January 2015. All participants gave the informed consent before taking part in the study. Blood samples were collected just before drug administration (trough levels). The drug levels were measured at five half-lives of APs elimination to ensure steady-state concentration. Calibration standards Standard stock solutions of each analyte at 1 mg/mL were prepared by dissolving the adequate amount of pure analyte in methanol and stored for a maximum of 6 months (with the exception of OLA) at −20°C. Stock solution of OLA was prepared monthly. From these stock solutions, appropriate spiking solutions containing all analytes were prepared in methanol just before adding into serum samples. Stock solution of IS was prepared at 1 mg/mL in methanol. Spiked serum samples were prepared by mixing 25 μL of appropriate stock solutions and 25 μL IS with 450 μL of intact serum to obtain the following analytes concentration levels. Calibration standards for analytes CLO, NOR, QTP, ARI, DHA, CPZ were used of the following concentration: 1, 5, 12.5, 25, 50, 100, 250, 500, 1000 ng/mL, quality control (QC) were equal 3, 300, 800 ng/mL. For another group, namely ZUC, RIS, PAL, HAL, OLA, the concentration standards’ levels were of the following concentrations: 0.5, 1, 1.25, 2.5, 5, 10, 25, 50, 100 ng/mL, QC were equal 1.5, 30, 80 ng/mL. Spiked serum samples were stored at −20°C. Sample preparation A simple LLE procedure was used to extract the analytes and the IS from human serum. All frozen patient samples, calibration standards and QC samples were thawed and allowed to equilibrate at room temperature prior to analysis. The samples were vortexed to mix for 10 s prior to spiking. A 450 μL aliquot of human serum sample was mixed with 25 μL of the IS working solution (500 ng/mL) and 25 μL methanol for TDM sample (or spiking solution for the calibration standards and QC samples). Sodium hydroxide (50 μL of a 1 N solution saturated with ammonium sulfate) was added to all serum samples. After vortexing for 10 s, a 2.5 mL aliquot of MTBE was added. The samples were shaken for 10 min using reciprocal shaker IKA HS 260 basic (Germany) and then centrifuged for 5 min at 4000 rpm on centrifuge Ceylon-16 (Russia). Afterwards the samples were placed in the refrigerator at −80°C. The unfrozen organic layer was transferred to a glass tube and evaporated at 40°C under a gentle stream of nitrogen. The dried extract was reconstituted with 200 μL of the mobile phase A and a 5 μL aliquot of it was injected into the LC–MS-MS system. Instrumentation and chromatography The LC–MS-MS system consisted of an Agilent 1200 series binary pump, an auto sampler connected to Agilent 6410–2 K Triple Quad LC–MS (Agilent Technologies, USA) using a electrospray ionization source. Chromatography was performed on a Zorbax SB-C18 column (particle size 5 mm, 150 mm × 4.6 mm ID, Agilent, USA), using a mobile phase consisted of mixture: acetonitrile −0.2% water solution of formic acid. The gradient profile was: 25% B for 1 min, 25–60% B until 3 min, then 60–90% B for 1 min, then 60–100% B for 1 min, then 100–25% B for 2 min and 25% B until end of run. The total run time was 11 min at flow rate 0.6 mL/min. The mass detector was operated at unit resolution in the positive MRM (+MRM) mode using the transitions of the protonated molecules of AP and IS (Table I). The column temperature was kept at 25°C. Injection volume was 5 μL. MS conditions were as follows: capillary voltage = 4 kV, temperature of desolation gas = 300°C, drying gas = 7 L/min (N2), nebulizer pressure is 30 psi. For quantitative analysis, MRM mode was used with a dwell time of 50 msec for each transition. MRM transitions for all analytes are given in Table I. Table I. The LC–MS-MS Conditions for Simultaneous AP Determination Drug MRM The retention times (min) Сollision energy (V) Fragmentore (V) Dwell time (ms) ARI 448,2→285,2 6,87 30 100 50 DHA 446,2→285,2 6,79 30 135 50 Anastrozole (IS) 294,2 →225,1 7,45 30 100 50 CLO 327,2→270,0 6,13 30 150 50 NOR 313,2→192,0 5,04 30 140 50 CPZ 319,1→86,1 7,14 15 112 50 HAL 376,2→165,0 6,79 20 135 50 OLA 313,0→256,0 2,65 25 95 50 PAL 427,3→207,2 6,01 30 135 50 RIS 411,3→191,1 5,98 35 135 50 QTP 384,2→253,1 6,43 20 135 50 ZUC 401,2→231,0 6,98 40 135 50 Drug MRM The retention times (min) Сollision energy (V) Fragmentore (V) Dwell time (ms) ARI 448,2→285,2 6,87 30 100 50 DHA 446,2→285,2 6,79 30 135 50 Anastrozole (IS) 294,2 →225,1 7,45 30 100 50 CLO 327,2→270,0 6,13 30 150 50 NOR 313,2→192,0 5,04 30 140 50 CPZ 319,1→86,1 7,14 15 112 50 HAL 376,2→165,0 6,79 20 135 50 OLA 313,0→256,0 2,65 25 95 50 PAL 427,3→207,2 6,01 30 135 50 RIS 411,3→191,1 5,98 35 135 50 QTP 384,2→253,1 6,43 20 135 50 ZUC 401,2→231,0 6,98 40 135 50 Table I. The LC–MS-MS Conditions for Simultaneous AP Determination Drug MRM The retention times (min) Сollision energy (V) Fragmentore (V) Dwell time (ms) ARI 448,2→285,2 6,87 30 100 50 DHA 446,2→285,2 6,79 30 135 50 Anastrozole (IS) 294,2 →225,1 7,45 30 100 50 CLO 327,2→270,0 6,13 30 150 50 NOR 313,2→192,0 5,04 30 140 50 CPZ 319,1→86,1 7,14 15 112 50 HAL 376,2→165,0 6,79 20 135 50 OLA 313,0→256,0 2,65 25 95 50 PAL 427,3→207,2 6,01 30 135 50 RIS 411,3→191,1 5,98 35 135 50 QTP 384,2→253,1 6,43 20 135 50 ZUC 401,2→231,0 6,98 40 135 50 Drug MRM The retention times (min) Сollision energy (V) Fragmentore (V) Dwell time (ms) ARI 448,2→285,2 6,87 30 100 50 DHA 446,2→285,2 6,79 30 135 50 Anastrozole (IS) 294,2 →225,1 7,45 30 100 50 CLO 327,2→270,0 6,13 30 150 50 NOR 313,2→192,0 5,04 30 140 50 CPZ 319,1→86,1 7,14 15 112 50 HAL 376,2→165,0 6,79 20 135 50 OLA 313,0→256,0 2,65 25 95 50 PAL 427,3→207,2 6,01 30 135 50 RIS 411,3→191,1 5,98 35 135 50 QTP 384,2→253,1 6,43 20 135 50 ZUC 401,2→231,0 6,98 40 135 50 Method Validation The method validation assays were carried out according to the currently accepted US Food and Drug Administration (FDA) and guidelines described in the papers (11, 12). The method’s specificity was tested by screening six different batches of healthy human blank serum. Each blank sample was tested for interference using the proposed extraction procedure and chromatographic/spectroscopic conditions and compared with those obtained with an aqueous solution of the analyte at a concentration near to the lower limit of quantitation (LLOQ). The matrix effect on the ionization of analytes was evaluated by comparing the peak area of analytes dissolved in blank sample (the final solution of blank serum after extraction and reconstitution) with that ones dissolved in mobile phase. Three different concentration levels of each AP were evaluated by analyzing five samples at appropriate level. If the ratio <85 or >115%, an exogenous matrix effect was implied. Linearity was tested for the range of concentrations pointed above. In addition, a blank serum sample were also analyzed to confirm absence of interferences, these sample was not used to construct the calibration function. The standard calibration curves were constructed using the peak area ratios of AP and IS vs. AP nominal concentrations. The intra-day precision and accuracy of the assay was measured by analyzing five spiked samples of APs at each QC level. The inter-day precision and accuracy was determined over 3 consecutive days by analyzing 15 QC samples. The acceptance criteria for precision and accuracy deviation values should be within 15% of the actual values. The extraction yield (or absolute recovery) of each AP was determined by comparing the mean peak area of extracted low, medium and high quality control samples to the mean peak area of methanol standards with the same concentrations. For sensitivity determination, the LLOQ was defined as the lowest concentration in the calibration curve at which both precision and accuracy were ≤20%, and signal/noise (S/N) > 10. The 0.5–1 ng/mL concentrations were investigated as the lower limit of quantification. Reproducibility and precision were also determined. To evaluate stability on repeat analysis of samples, freeze thaw stability was determined for three concentrations of every AP in serum. QC serum samples were tested after three freeze (−20°C) and thaw (room temperature) cycles. Results Method development Different organic solvents, ethyl-acetate, MTBE, chloroform, hexane, pentane, diethyl ether were evaluated for extraction solvents. Finally, MTBE was found to be optimal, because it is able to produce a clean chromatogram for a blank serum sample and yielded the highest recovery for the analytes by a LLE method. The use of sodium hydroxide during sample preparation raises the percentage of extraction of NOR and HAL. It’s more preferable to use LLE instead protein precipitation because this method produces a cleaner extract. It was shown that the presence of interfering compounds at a higher concentration could increase the viscosity and the surface tension of the droplets, which change the efficiency of their formation and evaporation. The changes in liquid phase could result in the alteration of the amount of charged ions in the gas phase (13). Serum standard’s mass-chromatogram (extracted ion current) of the different APs is shown in Figure 1, demonstrating the absence of interfering endogenous substances and acceptable separation of all compounds. Figure 1. View largeDownload slide Chromatograms of serum standards spiked with 12.5 ng/mL of each AP. Figure 1. View largeDownload slide Chromatograms of serum standards spiked with 12.5 ng/mL of each AP. All peaks were symmetrical and well shaped. The retention times are indicated in Table I. The time of analysis was 11 min. No specific signal peak was observed in serum samples from patients not treated with the investigated drugs. In serum samples of patients who had been treated with the investigated drugs, no additional interfering peaks were found and the peak shape was identical to the calibrators with an equally low background signal. Extracted ion chromatograms for all analytes over the 11-min analysis time are shown in Figure 2. Figure 2. View largeDownload slide Extracted ion chromatograms for eight APs and three metabolites in the extract of serum fortified with 30 ng/mL of each substance. Anastrozole used as IS (25 ng/mL). Figure 2. View largeDownload slide Extracted ion chromatograms for eight APs and three metabolites in the extract of serum fortified with 30 ng/mL of each substance. Anastrozole used as IS (25 ng/mL). The calibration curves in Table II showed good linear response (R2 > 0.99) over suitable calibration ranges for all analytes. MassHunter B.01.04. (Agilent, USA) as statistical software was used to generate linear regression equations for all calibration curves. A 1/X2-weighting scheme was used for each day of the validation and analysis for the analytes. Table II showed the slope and intercept of the calibration curves used in the validation study. The LLOQ, defined as the lowest concentration of analyte with an accuracy within 20% and a precision <20%, was 0.5–1 ng/mL for determination of all of the analytes (Table III). The LLOQ for serum samples was below the therapeutic ranges of the different drugs (Table II). Table II. Calibration Data for Simultaneous AP Determination Drug Regression equation Calibration range (ng/mL) R2 Therapeutic range (ng/mL) ARI Y = 0.008*Х + 1.1*10−4 1–1,000 0.992 100–500* DHA Y = 0.013*X − 0.04 1–1,000 0.998 – CPZ Y = 0.038*X + 0.12 1–1,000 0.998 30–300 CLO Y = 0.0071*X + 0.05 1–1,000 0.999 350–600 NOR Y = 0.006*X + 0.12 1–1,000 0.998 – HAL Y = 0.004*X − 0.16 0.5–50 0.998 2–17 OLA Y = 0.007*X − 0.04 0.5–100 0.998 20–80 RIS Y = 0.08*X + 0.16 0.5–100 0.998 20–60* PAL Y = 0.06*X + 0.06 0.5–100 0.998 20–60** QTP Y = 0.002*X + 0.13 1–1,000 0.996 10–600 ZUC Y = 0.004*X + 0.001 0.5–100 0.994 5–100 Drug Regression equation Calibration range (ng/mL) R2 Therapeutic range (ng/mL) ARI Y = 0.008*Х + 1.1*10−4 1–1,000 0.992 100–500* DHA Y = 0.013*X − 0.04 1–1,000 0.998 – CPZ Y = 0.038*X + 0.12 1–1,000 0.998 30–300 CLO Y = 0.0071*X + 0.05 1–1,000 0.999 350–600 NOR Y = 0.006*X + 0.12 1–1,000 0.998 – HAL Y = 0.004*X − 0.16 0.5–50 0.998 2–17 OLA Y = 0.007*X − 0.04 0.5–100 0.998 20–80 RIS Y = 0.08*X + 0.16 0.5–100 0.998 20–60* PAL Y = 0.06*X + 0.06 0.5–100 0.998 20–60** QTP Y = 0.002*X + 0.13 1–1,000 0.996 10–600 ZUC Y = 0.004*X + 0.001 0.5–100 0.994 5–100 Y—the ratio of the peak areas of APs to the peak area of the internal standard; X—AP concentration, ng/mL. *Including active metabolite. **When used as separate drug. Table II. Calibration Data for Simultaneous AP Determination Drug Regression equation Calibration range (ng/mL) R2 Therapeutic range (ng/mL) ARI Y = 0.008*Х + 1.1*10−4 1–1,000 0.992 100–500* DHA Y = 0.013*X − 0.04 1–1,000 0.998 – CPZ Y = 0.038*X + 0.12 1–1,000 0.998 30–300 CLO Y = 0.0071*X + 0.05 1–1,000 0.999 350–600 NOR Y = 0.006*X + 0.12 1–1,000 0.998 – HAL Y = 0.004*X − 0.16 0.5–50 0.998 2–17 OLA Y = 0.007*X − 0.04 0.5–100 0.998 20–80 RIS Y = 0.08*X + 0.16 0.5–100 0.998 20–60* PAL Y = 0.06*X + 0.06 0.5–100 0.998 20–60** QTP Y = 0.002*X + 0.13 1–1,000 0.996 10–600 ZUC Y = 0.004*X + 0.001 0.5–100 0.994 5–100 Drug Regression equation Calibration range (ng/mL) R2 Therapeutic range (ng/mL) ARI Y = 0.008*Х + 1.1*10−4 1–1,000 0.992 100–500* DHA Y = 0.013*X − 0.04 1–1,000 0.998 – CPZ Y = 0.038*X + 0.12 1–1,000 0.998 30–300 CLO Y = 0.0071*X + 0.05 1–1,000 0.999 350–600 NOR Y = 0.006*X + 0.12 1–1,000 0.998 – HAL Y = 0.004*X − 0.16 0.5–50 0.998 2–17 OLA Y = 0.007*X − 0.04 0.5–100 0.998 20–80 RIS Y = 0.08*X + 0.16 0.5–100 0.998 20–60* PAL Y = 0.06*X + 0.06 0.5–100 0.998 20–60** QTP Y = 0.002*X + 0.13 1–1,000 0.996 10–600 ZUC Y = 0.004*X + 0.001 0.5–100 0.994 5–100 Y—the ratio of the peak areas of APs to the peak area of the internal standard; X—AP concentration, ng/mL. *Including active metabolite. **When used as separate drug. Table III. Recoveries and Matrix Effects of the AP Drugs Drug Concentration (ng/mL) ME (%) Recovery (%) ARI 3 92.5 65.4 300 99.3 67.3 800 94.6 62.1 DHA 3 80.1 74.3 300 81.4 75.6 800 84.7 75.1 CPZ 3 90.1 89.6 300 89.5 86.5 800 85.4 81.2 CLO 3 92.4 67.1 300 98.3 69.2 800 99.2 70.5 NOR 3 91.2 61.7 300 95.8 60.0 800 90.2 66.3 HAL 1.5 78.2 70.3 30 80.1 73.0 80 79.1 72.4 OLA 1.5 85.4 70.4 30 87.5 71.5 80 91.2 76.1 RIS 1.5 72.3 72.6 30 75.3 70.7 80 78.4 71.4 PAL 1.5 75.1 68.2 30 79.9 66.4 80 78.7 68.2 QTP 3 61.3 50.7 300 67.1 51.2 800 61.2 52.7 ZUC 1.5 67.2 51.2 30 68.4 56.9 80 63.2 61.2 IS 25 81.7 75.4 Drug Concentration (ng/mL) ME (%) Recovery (%) ARI 3 92.5 65.4 300 99.3 67.3 800 94.6 62.1 DHA 3 80.1 74.3 300 81.4 75.6 800 84.7 75.1 CPZ 3 90.1 89.6 300 89.5 86.5 800 85.4 81.2 CLO 3 92.4 67.1 300 98.3 69.2 800 99.2 70.5 NOR 3 91.2 61.7 300 95.8 60.0 800 90.2 66.3 HAL 1.5 78.2 70.3 30 80.1 73.0 80 79.1 72.4 OLA 1.5 85.4 70.4 30 87.5 71.5 80 91.2 76.1 RIS 1.5 72.3 72.6 30 75.3 70.7 80 78.4 71.4 PAL 1.5 75.1 68.2 30 79.9 66.4 80 78.7 68.2 QTP 3 61.3 50.7 300 67.1 51.2 800 61.2 52.7 ZUC 1.5 67.2 51.2 30 68.4 56.9 80 63.2 61.2 IS 25 81.7 75.4 Table III. Recoveries and Matrix Effects of the AP Drugs Drug Concentration (ng/mL) ME (%) Recovery (%) ARI 3 92.5 65.4 300 99.3 67.3 800 94.6 62.1 DHA 3 80.1 74.3 300 81.4 75.6 800 84.7 75.1 CPZ 3 90.1 89.6 300 89.5 86.5 800 85.4 81.2 CLO 3 92.4 67.1 300 98.3 69.2 800 99.2 70.5 NOR 3 91.2 61.7 300 95.8 60.0 800 90.2 66.3 HAL 1.5 78.2 70.3 30 80.1 73.0 80 79.1 72.4 OLA 1.5 85.4 70.4 30 87.5 71.5 80 91.2 76.1 RIS 1.5 72.3 72.6 30 75.3 70.7 80 78.4 71.4 PAL 1.5 75.1 68.2 30 79.9 66.4 80 78.7 68.2 QTP 3 61.3 50.7 300 67.1 51.2 800 61.2 52.7 ZUC 1.5 67.2 51.2 30 68.4 56.9 80 63.2 61.2 IS 25 81.7 75.4 Drug Concentration (ng/mL) ME (%) Recovery (%) ARI 3 92.5 65.4 300 99.3 67.3 800 94.6 62.1 DHA 3 80.1 74.3 300 81.4 75.6 800 84.7 75.1 CPZ 3 90.1 89.6 300 89.5 86.5 800 85.4 81.2 CLO 3 92.4 67.1 300 98.3 69.2 800 99.2 70.5 NOR 3 91.2 61.7 300 95.8 60.0 800 90.2 66.3 HAL 1.5 78.2 70.3 30 80.1 73.0 80 79.1 72.4 OLA 1.5 85.4 70.4 30 87.5 71.5 80 91.2 76.1 RIS 1.5 72.3 72.6 30 75.3 70.7 80 78.4 71.4 PAL 1.5 75.1 68.2 30 79.9 66.4 80 78.7 68.2 QTP 3 61.3 50.7 300 67.1 51.2 800 61.2 52.7 ZUC 1.5 67.2 51.2 30 68.4 56.9 80 63.2 61.2 IS 25 81.7 75.4 Method validation The method was validated for linearity, recovery, accuracy, precision and selectivity. The validation data of all analytes proved that the extraction procedures and the analytical method were precise and accurate in the calibration range of each compound. The mean recovery rates of the extraction procedures were between 50 and 87% (Table III). To obtain an overview of the variation in ion-suppression effects, the final extracts of 20 randomly selected blank serum samples, were fortified to three levels of 10 each AP in the original sample with the investigated substances and then analyzed by LC–MS-MS in attenuated order together with pure standards. In terms of matrix effects, the ratios of the peak responses for APs were from 55 to 99%. The results indicated that coeluting endogenous substances inhibited the ionization of each AP in different manner, and yet the ion suppression from human serum matrix was consistent for this analytical method and would not interfere with the measurement of compounds. Although we observed some ion suppression, the matrix effect was acceptable because it did not affect the precision and accuracy (14). The intra-day and inter-day precision (CV, n =5) for APs were satisfactory at the three concentrations studied. According FDA guide low QCs were within three times the LLOQ, and high QC was approaching the high end of the calibration curve (80% of upper LOQ). Data on precision and accuracy are summarized in Table IV. Table IV. Accuracy and Precision of the Assay for Determination of APs in Serum (n = 5) Intra-assay Inter-assay Added to serum (ng/mL) Measured concentration Accuracy (%) Precision, CV Measured concentration Accuracy (%) Precision CV ARI  3 3.1 101.9 5.1 2.9 98.2 11.1  300 309.9 103.3 4.7 295.0 98.4 3.6  800 790.4 98.8 3.3 793.0 99.1 2.1 DHA  3 2.9 99.0 8.9 2.84 94.7 8.7  300 276.3 92.1 5.6 287.7 95.9 4.5  800 751.1 93.9 5.0 794.5 99.3 1.6 CPZ  3 2.96 98.8 4.8 2.78 92.7 10.3  300 292.5 97.5 6.27 287.49 95.83 5.8  800 751.1 93.9 5.02 798.69 99.8 1.6 CLO  3 2.8 94.8 13.6 3.1 98.3 9.3  300 306.6 102.2 11.5 303.6 101.2 4.8  800 832.5 104.1 3.6 811.4 101.4 5.7 NOR  3 2.8 91.8 14.1 2.9 95.3 7.6  300 311.3 103.8 5.7 296.9 98.9 4.9  800 771.9 96.5 0.04 785.1 98.1 6.3 HAL  1.5 1.46 97.5 15.1 1.42 95.1 12.9  30 12.4 99.4 4.4 12.1 96.4 8.6  80 31.4 104.8 8.7 32.3 107.5 14.1 OLA  1.5 1.6 103.1 10.8 1.5 97.2 11.3  30 30.9 103.02 14.3 29.2 97.3 11.9  80 81.1 101.3 10.8 80.3 100.4 11.7 RIS  1.5 1.45 96.8 12.0 1.42 94.7 11,8  30 30.5 101.8 6.7 29.9 99.69 13.1  80 84.8 106.0 6.2 75.9 94.9 8.70 PAL  1.5 1.55 103.6 6.8 1.44 96.5 10.2  30 31.2 103.9 9.4 28.9 96.6 13.2  80 77.9 97.4 7.4 75.4 94.3 7.5 QTP  3 2.8 93.8 13.1 2.8 93.4 13.2  300 270.8 90.3 4.8 276.4 92.1 10.5  800 796.7 99.6 7.8 805.3 100.7 6.9 ZUC  1.5 1.46 97.1 9.9 1.45 96.9 11.2  30 30.6 101.9 4.2 27.4 91.5 9.2  80 76.1 95.1 7.2 77.9 97.4 7.9 Intra-assay Inter-assay Added to serum (ng/mL) Measured concentration Accuracy (%) Precision, CV Measured concentration Accuracy (%) Precision CV ARI  3 3.1 101.9 5.1 2.9 98.2 11.1  300 309.9 103.3 4.7 295.0 98.4 3.6  800 790.4 98.8 3.3 793.0 99.1 2.1 DHA  3 2.9 99.0 8.9 2.84 94.7 8.7  300 276.3 92.1 5.6 287.7 95.9 4.5  800 751.1 93.9 5.0 794.5 99.3 1.6 CPZ  3 2.96 98.8 4.8 2.78 92.7 10.3  300 292.5 97.5 6.27 287.49 95.83 5.8  800 751.1 93.9 5.02 798.69 99.8 1.6 CLO  3 2.8 94.8 13.6 3.1 98.3 9.3  300 306.6 102.2 11.5 303.6 101.2 4.8  800 832.5 104.1 3.6 811.4 101.4 5.7 NOR  3 2.8 91.8 14.1 2.9 95.3 7.6  300 311.3 103.8 5.7 296.9 98.9 4.9  800 771.9 96.5 0.04 785.1 98.1 6.3 HAL  1.5 1.46 97.5 15.1 1.42 95.1 12.9  30 12.4 99.4 4.4 12.1 96.4 8.6  80 31.4 104.8 8.7 32.3 107.5 14.1 OLA  1.5 1.6 103.1 10.8 1.5 97.2 11.3  30 30.9 103.02 14.3 29.2 97.3 11.9  80 81.1 101.3 10.8 80.3 100.4 11.7 RIS  1.5 1.45 96.8 12.0 1.42 94.7 11,8  30 30.5 101.8 6.7 29.9 99.69 13.1  80 84.8 106.0 6.2 75.9 94.9 8.70 PAL  1.5 1.55 103.6 6.8 1.44 96.5 10.2  30 31.2 103.9 9.4 28.9 96.6 13.2  80 77.9 97.4 7.4 75.4 94.3 7.5 QTP  3 2.8 93.8 13.1 2.8 93.4 13.2  300 270.8 90.3 4.8 276.4 92.1 10.5  800 796.7 99.6 7.8 805.3 100.7 6.9 ZUC  1.5 1.46 97.1 9.9 1.45 96.9 11.2  30 30.6 101.9 4.2 27.4 91.5 9.2  80 76.1 95.1 7.2 77.9 97.4 7.9 Table IV. Accuracy and Precision of the Assay for Determination of APs in Serum (n = 5) Intra-assay Inter-assay Added to serum (ng/mL) Measured concentration Accuracy (%) Precision, CV Measured concentration Accuracy (%) Precision CV ARI  3 3.1 101.9 5.1 2.9 98.2 11.1  300 309.9 103.3 4.7 295.0 98.4 3.6  800 790.4 98.8 3.3 793.0 99.1 2.1 DHA  3 2.9 99.0 8.9 2.84 94.7 8.7  300 276.3 92.1 5.6 287.7 95.9 4.5  800 751.1 93.9 5.0 794.5 99.3 1.6 CPZ  3 2.96 98.8 4.8 2.78 92.7 10.3  300 292.5 97.5 6.27 287.49 95.83 5.8  800 751.1 93.9 5.02 798.69 99.8 1.6 CLO  3 2.8 94.8 13.6 3.1 98.3 9.3  300 306.6 102.2 11.5 303.6 101.2 4.8  800 832.5 104.1 3.6 811.4 101.4 5.7 NOR  3 2.8 91.8 14.1 2.9 95.3 7.6  300 311.3 103.8 5.7 296.9 98.9 4.9  800 771.9 96.5 0.04 785.1 98.1 6.3 HAL  1.5 1.46 97.5 15.1 1.42 95.1 12.9  30 12.4 99.4 4.4 12.1 96.4 8.6  80 31.4 104.8 8.7 32.3 107.5 14.1 OLA  1.5 1.6 103.1 10.8 1.5 97.2 11.3  30 30.9 103.02 14.3 29.2 97.3 11.9  80 81.1 101.3 10.8 80.3 100.4 11.7 RIS  1.5 1.45 96.8 12.0 1.42 94.7 11,8  30 30.5 101.8 6.7 29.9 99.69 13.1  80 84.8 106.0 6.2 75.9 94.9 8.70 PAL  1.5 1.55 103.6 6.8 1.44 96.5 10.2  30 31.2 103.9 9.4 28.9 96.6 13.2  80 77.9 97.4 7.4 75.4 94.3 7.5 QTP  3 2.8 93.8 13.1 2.8 93.4 13.2  300 270.8 90.3 4.8 276.4 92.1 10.5  800 796.7 99.6 7.8 805.3 100.7 6.9 ZUC  1.5 1.46 97.1 9.9 1.45 96.9 11.2  30 30.6 101.9 4.2 27.4 91.5 9.2  80 76.1 95.1 7.2 77.9 97.4 7.9 Intra-assay Inter-assay Added to serum (ng/mL) Measured concentration Accuracy (%) Precision, CV Measured concentration Accuracy (%) Precision CV ARI  3 3.1 101.9 5.1 2.9 98.2 11.1  300 309.9 103.3 4.7 295.0 98.4 3.6  800 790.4 98.8 3.3 793.0 99.1 2.1 DHA  3 2.9 99.0 8.9 2.84 94.7 8.7  300 276.3 92.1 5.6 287.7 95.9 4.5  800 751.1 93.9 5.0 794.5 99.3 1.6 CPZ  3 2.96 98.8 4.8 2.78 92.7 10.3  300 292.5 97.5 6.27 287.49 95.83 5.8  800 751.1 93.9 5.02 798.69 99.8 1.6 CLO  3 2.8 94.8 13.6 3.1 98.3 9.3  300 306.6 102.2 11.5 303.6 101.2 4.8  800 832.5 104.1 3.6 811.4 101.4 5.7 NOR  3 2.8 91.8 14.1 2.9 95.3 7.6  300 311.3 103.8 5.7 296.9 98.9 4.9  800 771.9 96.5 0.04 785.1 98.1 6.3 HAL  1.5 1.46 97.5 15.1 1.42 95.1 12.9  30 12.4 99.4 4.4 12.1 96.4 8.6  80 31.4 104.8 8.7 32.3 107.5 14.1 OLA  1.5 1.6 103.1 10.8 1.5 97.2 11.3  30 30.9 103.02 14.3 29.2 97.3 11.9  80 81.1 101.3 10.8 80.3 100.4 11.7 RIS  1.5 1.45 96.8 12.0 1.42 94.7 11,8  30 30.5 101.8 6.7 29.9 99.69 13.1  80 84.8 106.0 6.2 75.9 94.9 8.70 PAL  1.5 1.55 103.6 6.8 1.44 96.5 10.2  30 31.2 103.9 9.4 28.9 96.6 13.2  80 77.9 97.4 7.4 75.4 94.3 7.5 QTP  3 2.8 93.8 13.1 2.8 93.4 13.2  300 270.8 90.3 4.8 276.4 92.1 10.5  800 796.7 99.6 7.8 805.3 100.7 6.9 ZUC  1.5 1.46 97.1 9.9 1.45 96.9 11.2  30 30.6 101.9 4.2 27.4 91.5 9.2  80 76.1 95.1 7.2 77.9 97.4 7.9 Therapeutic drug monitoring The applicability of the method was proven in our laboratory by analyzing more than 300 samples in 93 patients during the last year. Overall, 50.75% of levels were in the expected therapeutic ranges. Low levels were observed in 27.86%, of which 1.1% were undetectable levels (<1 ng/mL). High levels occurred in 21.39%, of which 3.9% were considered potentially toxic. High levels occurred more frequently amongst patients receiving RIS while low levels occurred more frequently amongst patients receiving CLO. A representative chromatogram of extracted serum sample of the psychotic patient is shown in Figure 3, pointing the absence of interfering endogenous substances and good separation of all compounds in the respective mass chromatogram. Figure 3. View largeDownload slide An example of mass chromatograms of real patient samples contained CPZ (131 ng/mL), CLO (1,398 ng/mL), NOR (22 ng/mL), ARI (402 ng/mL), DHA (45 ng/mL) and the IS (25 ng/mL). Figure 3. View largeDownload slide An example of mass chromatograms of real patient samples contained CPZ (131 ng/mL), CLO (1,398 ng/mL), NOR (22 ng/mL), ARI (402 ng/mL), DHA (45 ng/mL) and the IS (25 ng/mL). Discussion AP drugs are extensively metabolized by cytochrome P450 enzymes. Some APs are converted to active metabolites which can contribute to the therapeutic or side effects of the parent drug. This is true for both ARI and RIS, but is not the case for CLO. The overall pharmacological effects of risperidone depend on the sum of serum concentrations of RIS and its 9-OH-RIS metabolite (total active moiety), so monitoring serum concentrations of the parent compound (RIS) alone can lead to erroneous interpretations (3). It should be mentioned that 9-OH-RIS (paliperidon) is now marketed as an AP as well. DHA is the main metabolite of ARI and as was repotted (15) possesses the antipsychotic activity similar to that of ARI. At steady state, ~30% of the serum ARI concentration is represented by the major active metabolite DHA. TDM of the sum of ARI + DHA concentrations has a limited value in the clinical use of ARI, but it may be useful in assuring adherence and optimizing the response in individuals. Lowering NOR levels in this way while maintaining therapeutic CLO levels increases the CLO/NOR ratio; the potential benefits include both an increase in efficacy and a reduction of number of side effects as sedation, weight gain, metabolic disturbances, and neutropenia. The optimal ratio of CLO to NOR has not yet been defined, nevertheless a ratio equal two or more implies that saturation of clozapine metabolism has been reached (16). Several papers described the LC–MS-MS method AP determination using isotopically labeled internal standards (SILIS) (17, 18). For this purpose, it is necessary to obtain or synthesize an analogue of the analyte with a different isotopic composition from the investigating analyte. The use of SILIS is the good approach to minimizing the influence of matrix effects on the accuracy and precision of a quantitative method, which is of particular importance when using ESI-MS. Unfortunately, the acquisition more than 10 SILIS for one LC–MS run is too expensive to academic laboratories. In addition, the labeling should be on a stable part of the molecule and the degree of labeling should not change due to back exchange occurring during the analysis. Unanticipated exchanges can occur, for example via tautomerization mechanisms, and this aspect should always be checked experimentally. Nevertheless, it may be prudent to scrutinize the selection of internal standards to ensure that certain commonly prescribed drugs and/or self-medication drugs (e.g., antipyretics, pain relievers and anti-inflammatory drugs) are avoided in the internal standard selection process (19). Gopinath et al. (20) reported using duloxetine as IS for the simultaneous quantitation of fluoxetine and olanzapine. Unfortunately the applicability of such an assay for patient samples may be problematic because duloxetine may also be coprescribed with either of the two drugs. On the other hand Choonga et al. (21) quiet right used remoxipride as IS in their AP determination method because the drug was withdrawn due to toxicity events. To our opinion using anticancer drug anastrozole as IS is a good choice for AP determination. The likelihood of being detected in the blood of psychiatric patients is low. On the other hand, it has similar extraction properties with detectable analytes. The use of 11 deuterated standards will make the method not cost-effective for use in ordinary psychiatric clinics. Using LC–MS-MS on a triple quadrupole, chromatographic separation is usually needed when metabolites can isotopically contribute to the parent drug. This is the case for ARI and DHA. DHA could interfere with ARI in m/z 448.2–285.2 reactions while they are coeluting. An attempt to achieve full separation between ARI and DHA employing a longer LC gradient ~30 min dramatically elongated the total time of run. The resolving of this problem in multi component run is difficult but unnecessary for TDM because therapeutic range for ARI includes active metabolite (Table II). Conclusion The described LC–MS-MS method provides a simple and fast procedure for the determination of eight currently used AP drugs in human serum. For a monitoring service aiming to cover a large panel of psychotropic drugs, the opportunity of simultaneous quantification is very attractive in terms of practical aspect and labor time. The method proved to be linear and accurate as well as acceptable for relevant ion suppression effects. Due to the highly specific detection method, the procedure was very sustained to interference from metabolites and other drugs. Our LLOQ was always below the lower therapeutic range and therefore the method presented was sensitive enough for TDM of the AP drugs (Table II). We hope the method can be especially useful for moderate budget labs and help to obtain patient results within a short turnaround time. References 1 Eliasson , E. , Lindh , J.D. , Malmström , R.E. , Beck , O. , Dahl , M.D. ; Therapeutic drug monitoring for tomorrow ; European Journal of Clinical Pharmacology , ( 2013 ); 69 : 25 – 32 . Google Scholar CrossRef Search ADS PubMed 2 Law , S. , Haddad , P.M. , Chaudhry , I.B. , Husain , N. , Drake , J.R. , Flanagan , R.J. , et al. . ; Antipsychotic therapeutic drug monitoring: psychiatrists’ attitudes and factors predicting likely future use ; Therapeutic Advances in Psychopharmacology , ( 2015 ); 5 : 214 – 223 . Google Scholar CrossRef Search ADS PubMed 3 Grundmann , M. , Kacirova , I. , Urinovska , R. ; Therapeutic drug monitoring of atypical antipsychotic drugs ; Acta Pharmaceutica , ( 2014 ); 64 : 387 – 401 . Google Scholar CrossRef Search ADS PubMed 4 Baimeeva , N.V. , Miroshnichenko , I.I. ; Analytical methods for the determination of atypical neuroleptics ; Pharmaceutical Chemistry Journal , ( 2016 ); 50 : 339 – 345 . Google Scholar CrossRef Search ADS 5 Brandhorst , G. , Oellerich , M. , Maine , G. , Taylor , P. , Veen , G. , Wallemacq , P. ; Liquid chromatography-tandem mass spectrometry or automated immunoassays: what are the future trends in therapeutic drug monitoring? ; Clinical Chemistry , ( 2012 ); 58 : 821 – 825 . Google Scholar CrossRef Search ADS PubMed 6 Logarinho , F. , Rosado , T. , Lourenc , C. , Barroso , M. , Araujo , A.R.T.S. , Gallardo , E. ; Determination of antipsychotic drugs in hospital and waste water treatment plant samples by gas chromatography/tandem mass spectrometry ; Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences , ( 2016 ); 1038 : 127 – 135 . Google Scholar CrossRef Search ADS 7 Song , M. , Xu , X. , Hang , T. , Wen , A. , Yang , L. ; Development of an LC-MS/MS method for the simultaneous quantification of aripiprazole and dehydroaripiprazole in human serum ; Analytical Biochemistry , ( 2009 ); 385 : 270 – 277 . Google Scholar CrossRef Search ADS PubMed 8 Ming , D.S. , Heathcote , J. ; Therapeutic drug monitoring of clozapine and norclozapine in human serum using ultra-performance liquid chromatography-tandem mass spectrometry ; Journal of Analytical Toxicology , ( 2009 ); 33 : 198 – 203 . Google Scholar CrossRef Search ADS PubMed 9 Baymeeva , N.V. , Bondarenko , E.V. , Potanin , S.S. , Miroshnichenko , I.I. ; Quantitative determination of aripiprazole, risperidone and their active metabolites in human serum by high-performance liquid chromatographic–tandem mass spectrometric in human serum ; Drug Development & Registration , ( 2014 ); 3 : 32 – 37 . 10 Miroshnichenko , I.I. , Yurchenko , N.I. , Platova , A.I. ; Quantitative determination of anastrozole by LC–MS-MS ; Chemical Pharmaceutical Journal , ( 2013 ); 47 : 122 – 125 . Google Scholar CrossRef Search ADS 11 Rao , R.N. , Prasad , K.G. , Naidu , C.G. , Saida , S. , Agwane , S.B. ; Development of a validated LC-MS/MS method for determination of doxofylline on rat dried bloodspots and urine: application to pharmacokinetics ; Journal of Pharmaceutical and Biomedical Analysis , ( 2013 ); 78–79 : 211 – 216 . Google Scholar CrossRef Search ADS PubMed 12 Diao , X. , Ma , Z. , Lei , P. , Zhong , D. , Zhang , Y. , Chen , X. ; Enantioselective determination of 3-n-butylphthalide (NBP) in human plasma by liquid chromatography on a teicoplanin-based chiral column coupled with tandem mass spectrometry ; Journal of Chromatography B, Analytical Technologies in the Biomedical and Life Sciences , ( 2013 ); 939 : 67 – 72 . Google Scholar CrossRef Search ADS PubMed 13 Zhou , W. , Yang , S. , Wang , P.G. ; Matrix effects and application of matrix effect factor ; Bioanalysis , ( 2017 ); 23 : 1839 – 1844 . Google Scholar CrossRef Search ADS 14 Matuszewski , B.K. , Constanzer , M.L. , Chavez‐Eng , C.M. ; Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLC‐MS/MS ; Analytical Chemistry , ( 2003 ); 75 : 3019 – 3030 . Google Scholar CrossRef Search ADS PubMed 15 Kang , M.J. , Song , W.H. , Shim , B.H. , Oh , S.Y. , Lee , H.Y. , Ghung , E.Y. , et al. . ; Pharmacologically active metabolites of currently marketed drugs: potential resources for new drug discovery and development ; Yakugaku Zasshi , ( 2010 ); 130 : 1325 – 1337 . Google Scholar CrossRef Search ADS PubMed 16 Legare , N. , Gregoire , C.A. , De Benedicts , L. , Dumais , A. ; Increasing the clozapine: norclozapine ratio with co-administration of fluvoxamine to enhance efficacy and minimize side effects of clozapine therapy ; Medical Hypotheses , ( 2013 ); 80 : 689 – 691 . Google Scholar CrossRef Search ADS PubMed 17 Schellekens , R.C.A. , Stellaard , F. , Woerdenbag , H.J. , Frijlink , H.W. , Kosterink , J.G.W. ; Applications of stable isotopes in clinical pharmacology ; British Journal of Clinical Pharmacology , ( 2011 ); 72 : 879 – 897 . Google Scholar CrossRef Search ADS PubMed 18 Srinivas , N.R. ; Should commonly prescribed drugs be avoided as internal standard choices in new assays for clinical samples? ; Bioanalysis , ( 2016 ); 8 : 607 – 610 . Google Scholar CrossRef Search ADS PubMed 19 Hasselstrom , J. ; Quantification of antidepressants and antipsychotics in human serum by precipitation and ultra high pressure liquid chromatography–tandem mass spectrometry ; Journal of Chromatography B, Analytical Technologies in the Biomedical and Life Sciences , ( 2011 ); 879 : 123 – 128 . Google Scholar CrossRef Search ADS PubMed 20 Gopinath , S. , Kumar , R.S. , Alexander , S. , Danabal , P. ; Development of a rapid and sensitive SPE-LC–MS/MS method for the simultaneous estimation of fluoxetine and olanzapine in human plasma ; Biomedical Chromatography , ( 2012 ); 26 : 1077 – 1082 . Google Scholar CrossRef Search ADS PubMed 21 Choonga , E. , Rudazb , S. , Kottelat , A. , Guillarme , D. , Veutheyb , J.-L. , Eapa , C.B. ; Therapeutic drug monitoring of seven psychotropic drugs and four metabolites in human plasma by HPLC–MS ; Journal of Pharmaceutical and Biomedical Analysis , ( 2009 ); 50 : 1000 – 1008 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
TI - Simultaneous Determination of Antipsychotic Drugs and Their Active Metabolites by LC–MS-MS and its Application to Therapeutic Drug Monitoring
JF - Journal of Chromatographic Science
DO - 10.1093/chromsci/bmy024
DA - 2018-04-07
UR - https://www.deepdyve.com/lp/oxford-university-press/simultaneous-determination-of-antipsychotic-drugs-and-their-active-bC3cLQGPr0
SP - 1
EP - 517
VL - Advance Article
IS - 6
DP - DeepDyve
ER -