Application of quantitative 1H NMR for the calibration of protoberberine alkaloid reference standards

Journal of Pharmaceutical and Biomedical Analysis 90 (2014) 92–97

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Application of quantitative 1 H NMR for the calibration of protoberberine alkaloid reference standards Yan Wu a , Yi He b,∗ , Wenyi He a , Yumei Zhang b , Jing Lu b , Zhong Dai b , Shuangcheng Ma b , Ruichao Lin b a State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China b National Institutes for Food and Drug Control, Tiantan Xili 2, Beijing 100050, China

a r t i c l e

i n f o

Article history: Received 8 August 2013 Received in revised form 11 November 2013 Accepted 13 November 2013 Available online 21 November 2013 Keywords: Quantitative NMR Protoberberine alkaloid Reference standard Berberine hydrochloride Palmatine hydrochloride Tetrahydropalmatine Phellodendrine hydrochloride

a b s t r a c t Quantitative nuclear magnetic resonance spectroscopy (qNMR) has been developed into an important tool in the drug analysis, biomacromolecule detection, and metabolism study. Compared with mass balance method, qNMR method bears some advantages in the calibration of reference standard (RS): it determines the absolute amount of a sample; other chemical compound and its certified reference material (CRM) can be used as internal standard (IS) to obtain the purity of the sample. Protoberberine alkaloids have many biological activities and have been used as reference standards for the control of many herbal drugs. In present study, the qNMR methods were developed for the calibration of berberine hydrochloride, palmatine hydrochloride, tetrahydropalmatine, and phellodendrine hydrochloride with potassium hydrogen phthalate as IS. Method validation was carried out according to the guidelines for the method validation of Chinese Pharmacopoeia. The results of qNMR were compared with those of mass balance method and the differences between the results of two methods were acceptable based on the analysis of estimated measurement uncertainties. Therefore, qNMR is an effective and reliable analysis method for the calibration of RS and can be used as a good complementarity to the mass balance method. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Nuclear magnetic resonance spectroscopy (NMR), as a very important analytical method, has been routinely used by chemists for the structure identification of organic compounds. During the past few decades, numerous applications of quantitative NMR (qNMR) have been reported [1–3]. Compared to general quantification methods such as chromatographic techniques, qNMR method has various advantages [2–5]: (i) the resonance signal of qNMR is directly proportional to the number of resonant nuclei, which make it possible to detect analyte by using other chemical compounds as internal standard (IS); (ii) the chemical shift is related to the molecular structure, which ensures the selectivity of qNMR method; (iii) sample preparation is easy, fast, and without derivatization. The disadvantage of qNMR method is regarded as its low sensitivity. However, it has been improved by the popularization of high-magnetic field NMR instruments. Nowadays qNMR has been developed into an important tool in the drug analysis [5,6], biomacromolecule detection [7,8], and metabolism study [9]. It

∗ Corresponding author. Tel.: +86 10 67095376; fax: +86 10 67023650. E-mail address: [email protected] (Y. He). 0731-7085/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jpba.2013.11.018

has been embodied in the appendices of some pharmacopoeias [10–12]. In drug analysis, reference standard (RS) plays an important role which ensures the implementation of quality measurements including instrument calibration, method validation, and estimation of measurement uncertainty. RS of natural product (RSNP) is also an essential fundamental in the quality control of herbal drug. Mostly, RSNPs are prepared from natural sources by column chromatography. The main impurities of the RSNPs are the closely related compound that co-eluted in the column chromatography and hard to be removed from the RSNPs [13]. On the other hand, many RSNPs such as saponins have no conjugated system and cannot be detected by ultraviolet (UV) detector in high performance liquid chromatography (HPLC). Because HPLC is commonly used in the preparation and calibration of RSNPs, much attention has been paid to the isolation and detection of those impurities. Different to the retention time of chromatographic method, the chemical shift of qNMR gives an indication of the chemical environment of individual nuclei. The impurities could be identified and quantified by the signals with different chemical shift. Furthermore, certified reference material (CRM) with small uncertainty of the certified value can be used as IS in qNMR, which makes the obtained purity values traceable to the CRM and reduces the calibration uncertainty. Thus,

Y. Wu et al. / Journal of Pharmaceutical and Biomedical Analysis 90 (2014) 92–97

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Fig. 1. Structure of protoberberine alkaloids and IS.

the specificity and precision of qNMR can meet the requirements for the calibration of RSNP [13,14]. Many chemical classes of RSNPs could be obtained from market, such as alkaloid, saponin, terpene, steroid, flavone, coumarin, and lignanoid. Protoberberine alkaloids, belonging to a large class of isoquinoline alkaloids, are a very extensive sub-group of secondary metabolites. It has been isolated from the plants of Berberidaceae, Ranunculaceae, Rutaceae, Papaveraceae, Annonaceae, and Menispermaceae [15,16]. Protoberberine alkaloids have biological activities of analgesia, antiarrhythmia, antihemorrhage, hypotensive, antiinflammation, antitumor, antiulcer, and smooth muscle relaxation [15–17]. Protoberberine alkaloids are widely used as RSs for the quality control of herb drugs. As well known, protoberberine alkaloids, berberine hydrochloride (BER), palmatine hydrochloride (PAL), tetrahydropalmatine (THP), and phellodendrine hydrochloride (PHE) (Fig. 1) are listed as RSs in the Chinese pharmacopoeia (2010 version) for the control of Berberidis Radix, Mahoniae Caulis, Coptidis Rhizoma, Phellodendri chinensis Cortex, Phellodendri amurensis Cortex, Corydalis decumbentis Rhizoma, Fibraurea Caulis, and Corydalis Rhizoma [18].qNMR has been applied in the quantitative determination of protoberberine alkaloids in Coptidis Rhizoma [5,19,20], Phellodendri Cortex [21], and traditional Chinese medicine prescriptions [19,21]. qNMR has also been applied to the detection of the purities of berberine, palmatine, and coptisine reagents including 4 batches of reference standards [20]. The established method can be used for the calibration of related RSs. However, in Hasada’s paper, the method validation was not carried out and its measurement uncertainties were not reported [20]. In this paper, the qNMR methods were developed for the calibration of BER, PAL, THP, and PHE. Method validation was carried out in terms of linearity, precision, repeatability, specificity, limits of quantification (LOQ), stability, and robustness. The purities obtained by qNMR were compared with those of mass balance method.Moreover, the

uncertainties of qNMR methods were also evaluated. As a result, qNMR allows a rapid calibration of protoberberine alkaloid RS, and could be a good complementarity to the mass balance method. 2. Materials and methods 2.1. Sample and chemicals The RS candidate materials of BER, PAL, and PHE were purified from the extracts of Berberidis Radix, Coptidis Rhizoma, or Phellodendri chinensis Cortex. THP was semi-synthesised from palmatine. Methanol-d4 (D, 99.8%) was purchased from Cambridge Isotope Laboratories, Inc. (Tewksbury, MA, USA). CRM potassium hydrogen phthalate (PHP, Fig. 1) was obtained from National Institute of Metrology (Beijing, China) with a certified value of 100 ± 0.02% (k = 2). The CRM was dried in 105 ◦ C for 2 h before being used. 2.2. Preparation of IS and sample solution A quantity of PHP was dissolved in methanol-d4 to produce the IS solution with a concentration of about 1.4 mg/mL. The sample solution was prepared by dissolving about 10 mg of sample in 2 mL of IS solution. 2.3. qNMR analysis All NMR spectra were measured on Varian VNS-600 spectrometer (Varian, San Francisco, CA, USA) operating at 600 MHz for proton (1 H) resonance frequency equipped with a 5 mm I.D. high-field switchable broadband NMR probe using 5 mm sample tubes (5 mm diameter, 7 in length, Wilmed LabGlass, Vineland, NJ, USA). The software of VnmrJ 3.2A (Agilent Technologies, Santa Clara, CA, USA) was used for the data acquisition, and MestReNova 6.1.1 (Mestrelab

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Y. Wu et al. / Journal of Pharmaceutical and Biomedical Analysis 90 (2014) 92–97

Table 1 1 H NMR chemical shifts (ı in ppm, J in Hz) of protoberberine alkaloids (CD3 OD).

1 4 5 6 8 9 11 12 13 13a 2-OR 3-OR 9-OMe 10-OMe N–Me

BER

PAL

THP

PHE

7.64 (s) 6.95 (s) 3.25 (t, J = 6.6) 4.92 (t, J = 6.6) 9.76 (s) – 8.10 (d, J = 9.0) 7.99 (d, J = 9.0) 8.68 (s) – 6.10 (s) – 4.20 (s) 4.10 (s) –

7.65 (s) 7.04 (s) 3.30 (t, J = 6.0) 4.93 (t, J = 6.0) 9.75 (s) – 8.10 (d, J = 9.0) 8.00 (d, J = 9.0) 8.78 (s) – 3.99 (s) 3.94 (s) 4.20 (s) 4.10 (s) –

6.87 (s) 6.71 (s) 3.09(m), 2.72(m) 3.22(m), 2.72(m) 4.21 (d, J = 15.6), 3.53 (d, J = 15.6) – 6.90 (d, J = 8.4) 6.94 (d, J = 8.4) 3.45(dd, J = 3.6, 15.6), 2.72(m) 3.59(dd, J = 3.6, 12.0) 3.80 (s) 3.82 (s) 3.83 (s) 3.83 (s) –

6.70 (s) 6.86 (s) 3.22 (m) 3.82 (m), 3.50(m) 4.76 (d, J = 15.0), 4.59 (d, J = 15.0) 6.75 (s) – 6.65 (s) 3.04 (dd, J = 11.2, 18.0), 3.35 (m) 4.68 (dd, J = 6.0, 11.2) – – 3.21 (s) 3.84 (s) 3.85 (s)

Research S.L., Santiago de Compostela, Spain) was used for the data processing. The experiment temperature was controlled at 25 ◦ C (298.15 K). The measurements were carried out with the following parameters: pulse angles of 30◦ , 32 k data points (corresponding to an acquisition time of 2.0 s at a spectral width of 9615 Hz), gain of 48 dB, and relaxation delay of 25 s. Fourier transformation was done after zero filling the data to 64 k time domain points. Prior to Fourier transformation, the FIDs were multiplied by an exponential window function with a line broadening of 0.2 Hz in all NMR experiments. During the data processing, phase and baseline corrections were done manually, and the signals were also integrated manually. Chemical shift was referenced to the solvent signal of methanol-d4 . Each sample was measured 3 times, and the purities were calculated with the mean of the parallel detection results. The internal standard method was used in present study. The purity of analyte Px is calculated under the following formula [22]: Px =

Ix Nis Mx mis P Iis Nx Mis mx is

(1)

where Ix and Iis correspond to the integrated signal area of a (typical) NMR line of the analyte and the IS, respectively; Nx and Nis are the numbers of spins of the analyte and the IS; Mx and Mis are the molar masses of the analyte and the IS; mx is the weighed mass of the investigated sample, and mis is the total mass of IS in 2 mL of IS solution; Pis is the purity of the IS. 2.4. Measurement uncertainty of the qNMR method The combined measurement uncertainty of qNMR can be calculated under the modified Malz’s formula [22]. uc (Px ) = Px



u(Ix /Iis ) Ix /Iis

2 +

 u(M ) 2 x

Mx

+

 u(M ) 2 is

Mis

+

 u(m ) 2 x

mx

+

In the formula, u(Ix /Iis ) is the uncertainty of qNMR measurement; u(Mx ) and u(Mis ) are the uncertainties of molar masses of the analyte and the IS, respectively; u(mx ) and u(mis ) are the uncertainties of the weighing of the analyte and the IS; u(Pis ) is the uncertainty of the purity of IS; u(vx ) and u(vis ) are the uncertainties of volumes of sample and IS solution.

100% under the following formula [11]: Content% = (1 − impurity%) (1 − water% − volatile material% − ash%) × 100%

(3)

The content of organic impurities was determined by an HPLC method in accordance with the Chinese Pharmacopoeia [18]. The content of inorganic impurities was obtained by ash determination [18]. Water content and residual solvents were determined by Karl Fischer titration and thermogravimetric analysis methods [10]. 3. Results and discussion 3.1. Selection of the monitored signals for the quantification An ideal IS for qNMR would be readily available in a highly pure form, inexpensive, stable, and soluble in the NMR solvents [1]. In our study, the CRM of PHP was selected as IS for its high purity and chemical stability. The 1 H NMR spectrum of PHP showed proton signals of ortho-substituted benzene ring [ı 8.15 (2H, m, H-2, 5) and 7.53 (2H, m, H-3, 4)] [23]. The signals of H-3, 4 were used as the monitored signals of IS in present study because of its good separation from the analytes signals. Similar to the quantification signals of IS, the monitored signals of analyte should fit the following requirements: (i) the signal should not overlap with other signals; (ii) its chemical shift should be close to the chemical shift of IS signals to reduce the influences of phase and baseline corrections; (iii) the singlet signal is preferred over doublets or multiplet in order to achieve a better signal-to-noise ratio. The 1 H NMR chemical shifts of the analytes

 u(m ) 2 is

mis

+

 u(P ) 2 is

Pis

+

 u(v ) 2 x

vx

+

 u(v ) 2 is

vis

(2)

were shown in Table 1 [14,24,25] and the 1 H NMR spectra for analytes with IS were shown in Fig. 2. According to those requirements, the quantification signals were selected as follows: H-1 [ı 7.64 (1H, s)] of BER, H-1 [ı 7.65 (1H, s)] of PAL, H-4 [ı 6.71 (1H, s)] of THP, and H-4 [ı 6.86 (1H, s)] of PHE. 3.2. Determination of relaxation time

2.5. Mass balance method The contents of the RS candidate materials were also evaluated with the mass balance method which was calculated by subtracting the sum of impurities (organic, inorganic, water, and solvents) from

The value of relaxation delay is very important for qNMR, which should be at least five times of the longest relaxation time T1 in order to measure 99% of the equilibrium magnetization [4]. The relaxation time T1 was determined experimentally by an inversion

Y. Wu et al. / Journal of Pharmaceutical and Biomedical Analysis 90 (2014) 92–97

Fig. 2.

1

H NMR spectra for protoberberine alkaloids with internal standard.

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Y. Wu et al. / Journal of Pharmaceutical and Biomedical Analysis 90 (2014) 92–97

Table 2 The T1 values of monitored protons.

IS BER PAL THP PHE

Table 4 Uncertainty budgets for the established qNMR method (%).

Proton

T1 (s)

H-3, 4 H-1 H-1 H-4 H-4

3.560 1.750 0.959 1.535 1.407

Table 3 Method validation parameters of qNMR. Compound Linearity Linear range (mg) r2 LOQ (mg/mL) Precision (%, n = 6) Intra-day precision Inter-day precision Precision (n = 6) RSD (%)

BER

PAL

THP

PHE

15.2–1.24 0.9998 0.15

14.9–0.64 0.9999 0.19

11.2–1.03 0.9990 0.15

14.1–5.06 0.9993 0.19

0.75 0.53

0.16 0.37

0.13 0.09

0.18 0.30

0.67

0.51

0.88

0.79

u(Ix /Iis ) u(Mx ) u(Mis ) u(mx ) u(mis ) u(Pis ) u(vx ) u(vis ) U combined U extended

BER

PAL

THP

PHE

0.67 0.008 0.005 0.46 0.13 0.01 0.43 0.069 0.93 1.87

0.51 0.009 0.005 0.46 0.13 0.01 0.43 0.069 0.83 1.65

0.88 0.008 0.005 0.46 0.13 0.01 0.43 0.069 1.09 2.19

0.79 0.009 0.005 0.46 0.13 0.01 0.43 0.069 1.02 2.05

Table 5 Results of the qNMR method and mass balance method (%).

qNMR Mass balance Difference

BER (batch 1)

BER (batch2)

PAL

THP

PHE

83.8 86.8 3.0

85.7 86.7 1.0

83.7 86.1 2.4

99.1 99.9 0.8

92.4 93.9 1.5

3.4. Measurement uncertainty recovery experiment for all the monitored protons of the targeted compounds and IS (Table 2). The longest relaxation time found was 3.560 s for the H-3, 4 of IS. Based on the data of T1 , the relaxation delay was set at 25 s to ensure the accurate quantification.

3.3. Validation of qNMR method The performance of the qNMR method was validated according to the guidelines for validation of analytical methods of Chinese Pharmacopoeia [18]. The linearity test solutions for related compounds were prepared by dissolving different amount of sample and diluting to the required concentrations with IS solution. Linearity curves were drawn for the amount of analyte in mg (X) vs. the area ratio of selected analyte signal to the selected IS signal (Y). The intra-day and inter-day precisions of the qNMR method were evaluated by performing 6 replicate assays of a same sample solution in one day or twice a day on three consecutive days. The method repeatabilities were evaluated by analyzing 6 independently prepared sample solutions. Because the main purpose of this study was quantification of protoberberine alkaloid RS, we focused on LOQ rather than limits of detection. LOQ can be calculated with the formula: LOQ = 10/S (: the standard deviation of y-intercept, S: the slope of the calibration curve) [5], or it can be determined by the definition of the LOQ for a signal/noise = 10 [2]. The latter one was used in this paper. The same sample solution was determined every 10 h in 50 h after preparation to access the solution stabilities. The RSDs of the parallel detections were 0.29% for BER, 0.42% for PAL, 0.08% for THP, and 0.19% for PHE respectively, confirming that sample solutions were stable up to 50 h. 1 H–1 H COSY spectra of the mixture of analytes and IS were used to obtain the specificity of the method. No interference was observed between the monitored and other signals. Method validation results are summarized in Table 3 and demonstrate that the established qNMR method meets the requirements for quantification. Acquisition parameters may affect quality of qNMR analysis greatly [22]. In order to evaluation the robustness of the qNMR method, the influences of pulse angle and acquisition time on the analysis results of BER were examined with the same sample solution. The purities were 84.3%, 83.9%, and 83.7% obtained by pulse angle 30◦ , 45◦ , and 90◦ , and 84.3%, 84.3%, and 84.1% by relaxation delay 15, 25, and 35 seconds, respectively. The quantitative results illustrated the robustness of the method.

Table 4 illustrates the complete uncertainty budget for the established qNMR method. The extended measurement uncertainties are ranged from 1.65% to 2.19% with a confidence interval of 95% (k = 2). The results are larger than the previously reported data which ranged from 1.36 to 1.96% [26]. The main sources of uncertainty were qNMR measurement, sample weight, and the volume of sample solution in our study. Because of the different ratios of the NMR signals to molecule weight between sample and IS, the sample solution was prepared by dissolving the sample in 2 mL of IS solution. This operational procedure led to the additional uncertainties of volumes and enlarged the extended measurement uncertainties of our study. The uncertainty could be reduced by weighing more amount of sample and using more volume of deuterated NMR solvent to dissolve the sample and IS at the same time. 3.5. Analysis results of qNMR and mass balance method Table 5 shows the analysis results of 5 batches of protoberberine alkaloids determined by qNMR and mass balance methods. The obtained purity values of BER, PAL, and PHE were less than 95%. Crystallization water was the main parameter affecting the purity values of those RS candidate materials based on the results of Karl Fischer titration and thermogravimetric analysis. Water contents obtained by mass balance were 12.6% for BER (batch 1), 12.9% for BER (batch 2), 12.1% for PAL, 0.0% for THP, 5.7% for PHE. The differences between the results of 3 batches of RS candidate materials were less than the corresponding extended measurement uncertainties of the established qNMR method. However, a batch of BER showed the difference of 3.0% and a batch of PAL showed 2.4%. The extended measurement uncertainty of mass balance method was about 2% with the highest value of 2.75% [26]. The differences between the analysis results of qNMR and mass balance methods are acceptable when the extended measurement uncertainties of those methods are considered. On the other hand, the analysis results of qNMR were smaller than their corresponding results of mass balance. Although those differences could be explained by the measurement uncertainty, systematic error might exist. The mass balance method is based on the knowledge of impurity. Some unknown impurity may not be considered during RS calibration with mass balance method. The existence of those unknown impurities is one of the possible reasons which lead to the difference between those results.

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