Journal of Analytical Methods in Chemistry
Volume 2016 (2016), Article ID 7627823, 5 pages
http://dx.doi.org/10.1155/2016/7627823

Research Article

Direct Comparison of ¹⁹F qNMR and ¹H qNMR by Characterizing Atorvastatin Calcium Content

Yang Liu, Zhaoxia Liu, Huaxin Yang, and Lan He

National Institutes for Food and Drug Control, Beijing 100050, China

Received 29 June 2016; Revised 3 August 2016; Accepted 9 August 2016

Academic Editor: Gowda A. Nagana Gowda

Copyright © 2016 Yang Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Quantitative nuclear magnetic resonance (qNMR) is a powerful tool in measuring drug content because of its high speed, sensitivity, and precision. Most of the reports were based on proton qNMR (¹H qNMR) and only a few fluorine qNMR (¹⁹F qNMR) were reported. No research has been conducted to directly compare the advantage and disadvantage between these two methods. In the present study, both ¹⁹F and ¹H qNMR were performed to characterize the content of atorvastatin calcium with the same internal standard. Linearity, precision, and results from two methods were compared. Results showed that ¹⁹F qNMR has similar precision and sensitivity to ¹H qNMR. Both methods generate similar results compared to mass balance method. Major advantage from ¹⁹F qNMR is that the analyte signal is with less or no interference from impurities. ¹⁹F qNMR is an excellent approach to quantify fluorine-containing analytes.

1. Introduction

Quantitative nuclear magnetic resonance (qNMR) has been widely utilized in pharmaceutical analysis [1–3], natural products characterization [4, 5], and reference substances quality control [6–9]. This technique has several advantages including fast sample preparation, no necessity for reference material, and generating both structure information and quantification result in one experiment. Currently, most of the qNMR reported are proton qNMR (¹H qNMR). For some analytes, choosing a suitable internal standard (IS) is often challenging since the response signals in ¹H NMR are generally from 0 to 15 and signal overlapping occurs easily. When an analyte is mixed with various excipients in medicines or different metabolites in body fluids, the deployment of ¹H qNMR might be impossible due to severe signals overlapping. Some groups reported the application of heteronuclear 2D qNMR techniques which can avoid the signal overlapping mentioned previously [10, 11]. But these 2D qNMR are time consuming (more than two hours) and the results are easily affected by T2 and coupling constant which are generally not a crucial parameter in 1D qNMR [10].

¹⁹F NMR has been utilized in characterizing fluorine-containing pharmaceutical and metabolites in complicated matrices [12, 13] since drug excipients or body fluids barely contain fluorine and do not interfere with analytes. One major advantage of ¹⁹F NMR is that signals in ¹⁹F NMR barely overlap due to its broad response range (ca. δ −200 to 100) which makes the selection of IS in ¹⁹F qNMR much easier than in ¹H qNMR. Several groups have reported the deployment of ¹⁹F qNMR in characterizing pharmaceutical [14, 15], metabolites [16], and biooils [17].

Both ¹H and ¹⁹F qNMR have their advantages and drawbacks. Although ¹H qNMR is potentially applicable to any analyte containing proton, the application of this method is limited when analytes are in complicated matrices. And the selection of IS should be careful to avoid interference with the analyte. On the contrary, interference from matrices or IS seldom happens in ¹⁹F qNMR.

There is no direct comparison of ¹⁹F qNMR and ¹H qNMR such as signal sensitivity, linearity, and RSD. To fully understand the applicable conditions of these two methods, we chose 4,4′-difluorodiphenylmethanone which has both hydrogen and fluorine atoms as an IS to analyze the content of atorvastatin calcium with both ¹⁹F and ¹H qNMR (Figure 1). Directly comparing results from the same analyte and IS by different qNMR experiments can avoid the influence of sample purity. Besides, the method validation data from both ¹⁹F and ¹H qNMR were also compared.

Figure 1: Structures of atorvastatin calcium and 4,4′-difluorodiphenylmethanone.

2. Materials and Methods

2.1. Materials and Analyte Preparations

4,4′-Difluorodiphenylmethanone was purchased from TCI Chemicals (>99.0%, Shanghai, China); atorvastatin calcium was from Ranbaxy Laboratories (94.7%, Gurgaon, India); and DMSO- was from Sigma (99.9%, St. Louis, USA). All chemicals were used as received.

4,4′-Difluorodiphenylmethanone and atorvastatin calcium were dissolved in DMSO- to produce a concentration of about 25 mmol/mL and 8 mmol/mL, respectively.

2.2. Instrument Conditions

All of the ¹⁹F and ¹H experiments were acquired at 298 K using a Bruker Ascend 500 M spectrometer with a BBO probe at 470.61 MHz and 500.15 MHz, respectively. For ¹⁹F qNMR, the experiments were under the following parameters: 90° pulse angle, center offset (O1P) = −110 ppm, spectral width (SW) = 100 ppm, 128 K data points, 16 scans, and relaxation time  s. For ¹H-qNMR, the following parameters were applied: 30° pulse angle, O1P = 6.15 ppm, 64 K data points, 16 scans, and relaxation time  s.

2.3. Processing Parameters

Data was processed on TopSpin 2.1 software with 0.3 Hz exponential apodization applied to FID. Manual phase correction and signal integrations were performed corresponding to the IS signals and analyte signals. ¹⁹F NMR shift was adjusted with CF₃COOH(δ −76.2) and ¹H NMR shift was referenced to tetramethylsilane.

2.4. Content Calculation Formula

The content of analyte was calculated by

where and are the signal response of the analyte and IS, and are the number of spin atoms (fluorine in ¹⁹F and proton in ¹H qNMR) in the analyte and IS, is the molecular weight of analyte (1155.4 g/mol), is the molecular weight of IS (218.2 g/mol), and are the mass of the analyte and IS, and is the purity of the IS.

3. Result and Discussion

3.1. Optimization of Experiment Parameters

Relaxation time () is an essential parameter in qNMR experiments. should be more than 5 times of longitudinal relaxation () to make sure more than 99% of nuclei return to their equilibrium status [18]. in ¹⁹F and ¹H qNMR experiments were determined by an inversion recovery method. of the analyte signals in ¹⁹F and ¹H experiments were found to be 0.86 s and 2.18 s, respectively. of the IS in ¹⁹F and ¹H experiments were 1.80 s and 2.97 s. So in both ¹⁹F and ¹H qNMR experiments were set as 15 s to make sure the full relaxation is achieved before next repulsion.

Transmitter offset (O1P) and spectral width (SW) are another two important parameters in qNMR experiments. In ¹H qNMR experiments, default O1P (6.175 ppm) and SW (20 ppm) settings worked well. On the contrary, O1P and SW in ¹⁹F qNMR experiments must be manually modified. When default O1P (−100 ppm) and SW (241 ppm) were used, the spectrum is difficult to perform phase and baseline correction. In this study, the signals of analyte and IS appeared at δ −111.9 and −104.4, respectively. So O1P was set at the center of two signals δ −108. Meanwhile, it is reported that response signals should not locate at the edge of a spectrum to avoid distortion [19]. Here, SW was set at 60 ppm to fulfill the requirement.

3.2. Selection of Analyte Signals and IS Signals

In ¹H qNMR experiments, the multiple signals of the analyte are distributed from around δ 1.0 to 8.0. Signals at δ 7.5 and 7.4 from the analyte and IS, respectively (Figure 2), were chosen for content calculation. Meanwhile, wide response range in a ¹⁹F qNMR spectrum makes the selection of IS easy and straightforward. Signals overlapping in a ¹⁹F qNMR experiment rarely occur. Generally, any fluorine-containing compound with high purity which does not react with the analyte is eligible as an IS in ¹⁹F qNMR experiment. Here, 4,4′-difluorodiphenylmethanone was utilized (Figure 3).

Figure 2: ¹H qNMR spectrum of atorvastatin calcium (A) and internal standard (B).

Figure 3: ¹⁹F qNMR spectrum of atorvastatin calcium (A) and internal standard (B).

3.3. Method Validation

3.3.1. Linearity and Range

¹⁹F and ¹H qNMR methods were validated (Table 1). The linearity of both methods was measured by using the solutions prepared by dissolving desired amount of analyte and IS in one tube. The ratio of calculated analyte mass to added analyte mass was fitted to a linear curve. The correction coefficient showed that both ¹⁹F and ¹H methods had good linearity within 3.21–20.34 mg/mL concentration ranges with .

Table 1: Method validation of ¹⁹F and ¹H qNMR measurements.

¹⁹F qNMR
¹H qNMR

Linearity,
0.9999
0.9999

Precision ()

    RSD (%)
0.49
0.82

Repeatability ()

    RSD (%)
0.73
0.62

LOQ (mg/mL)
1.34
1.02

3.3.2. Precision, Repeatability, and Stability

Precision tests were carried out by testing the same solution six times. The repeatability experiments were achieved by characterizing six independent solutions containing both analyte and IS. The RSD of precision and repeatability indicates the good accuracy of the both methods. The stability of solutions was assessed by analyzing one analyte at 1, 2, 4, 6, and 8 hours intervals. The results indicated that both atorvastatin calcium and IS are stable after 8 hours in solution.

3.3.3. Limit Of Quantification (LOQ)

LOQ are calculated as 10σ/ where σ is the standard deviation (SD) of the intercepts and means the slope of linearity curve [20]. It was found that the LOQ in ¹⁹F qNMR is similar to that from ¹H qNMR.

3.4. Comparison Results from ¹H and ¹⁹F qNMR (Table 2)

Mean of six results from independent solutions was calculated. The content of atorvastatin calcium is 93.1% from ¹⁹F qNMR and 95.3% from ¹H qNMR. Both results are consistent with that from mass balance method (94.7%). The major reason that lowers the purity values is water content in analytes. Both ¹⁹F and ¹H qNMR can generate accurate results in determining the content of atorvastatin calcium.

Table 2: Content of atorvastatin calcium calculated from ¹⁹F and ¹H qNMR measurements.

Number
 Atorvastatin calcium content (%)

¹⁹F qNMR
¹H qNMR

1
93.9
94.8

2
92.2
95.1

3
93.8
95.1

4
93.1
94.9

5
92.8
95.7

6
92.6
96.4

Mean
93.1
95.3

RSD (%)
0.73
0.62

4. Conclusions

For the first time, ¹⁹F and ¹H qNMR were performed and directly compared with the same analyte and IS. Method validation data showed that ¹⁹F qNMR has similar accuracy, sensitivity, and reproducibility to ¹H qNMR. The quantitative results from the two methods are comparable to that from mass balance measurement. ¹⁹F qNMR is valuable in quantitatively analyzing fluorine-containing analytes which are codissolved with excipients, body fluids, or various metabolites. ¹⁹F qNMR can be widely applied in early drug research and development as well as clinical trials.

Competing Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

The authors gratefully acknowledge the financial support from the Significant New Drugs Creation, Special Science and Technology Major (2015ZX09303001) and the Youth Development Research Foundation of National Institutes for Food and Drug Control (no. 2014A6).

References

G. K. Webster and S. Kumar, “Expanding the analytical toolbox: pharmaceutical application of quantitative NMR,” Analytical Chemistry, vol. 86, no. 23, pp. 11474–11480, 2014.

G. F. Pauli, S.-N. Chen, C. Simmler et al., “Importance of purity evaluation and the potential of quantitative ¹H NMR as a purity assay,” Journal of Medicinal Chemistry, vol. 57, no. 22, pp. 9220–9231, 2014.

U. Holzgrabe and M. Malet-Martino, “Analytical challenges in drug counterfeiting and falsification—the NMR approach,” Journal of Pharmaceutical and Biomedical Analysis, vol. 55, no. 4, pp. 679–687, 2011.

L. P. Santos Pimenta, M. Schilthuizen, R. Verpoorte, and Y. H. Choi, “Quantitative analysis of amygdalin and prunasin in Prunus serotina Ehrh. using ¹H-NMR spectroscopy,” Phytochemical Analysis, vol. 25, no. 2, pp. 122–126, 2014.

C. Simmler, J. G. Napolitano, J. B. McAlpine, S.-N. Chen, and G. F. Pauli, “Universal quantitative NMR analysis of complex natural samples,” Current Opinion in Biotechnology, vol. 25, pp. 51–59, 2014.

T. Rundlöf, I. McEwen, M. Johansson, and T. Arvidsson, “Use and qualification of primary and secondary standards employed in quantitative 1H NMR spectroscopy of pharmaceuticals,” Journal of Pharmaceutical and Biomedical Analysis, vol. 93, pp. 111–117, 2014.

M. Weber, C. Hellriegel, A. Rück, R. Sauermoser, and J. Wüthrich, “Using high-performance quantitative NMR (HP-qNMR) for certifying traceable and highly accurate purity values of organic reference materials with uncertainties <0.1%,” Accreditation and Quality Assurance, vol. 18, no. 2, pp. 91–98, 2013.

S. Bekiroglu, O. Myrberg, K. Östman et al., “Validation of a quantitative NMR method for suspected counterfeit products exemplified on determination of benzethonium chloride in grapefruit seed extracts,” Journal of Pharmaceutical and Biomedical Analysis, vol. 47, no. 4-5, pp. 958–961, 2008.

S. Shen, X. Yang, and Y. Shi, “Application of quantitative NMR for purity determination of standard ACE inhibitors,” Journal of Pharmaceutical and Biomedical Analysis, vol. 114, pp. 190–199, 2015.

F. Fardus-Reid, J. Warren, and A. Le Gresley, “Validating heteronuclear 2D quantitative NMR,” Analytical Methods, vol. 8, no. 9, pp. 2013–2019, 2016.

K. F. Hu, W. M. Westler, and J. L. Markley, “Simultaneous quantification and identification of individual chemicals in metabolite mixtures by two-dimensional extrapolated time-zero ¹H−¹³C HSQC (HSQC₀),” Journal of the American Chemical Society, vol. 133, no. 6, pp. 1662–1665, 2011.

M. Srinivas, L. J. Cruz, F. Bonetto, A. Heerschap, C. G. Figdor, and I. J. M. de Vries, “Customizable, multi-functional fluorocarbon nanoparticles for quantitative in vivo imaging using 19F MRI and optical imaging,” Biomaterials, vol. 31, no. 27, pp. 7070–7077, 2010.

R. Martino, V. Gilard, F. Desmoulin, and M. Malet-Martino, “Interest of fluorine-19 nuclear magnetic resonance spectroscopy in the detection, identification and quantification of metabolites of anticancer and antifungal fluoropyrimidine drugs in human biofluids,” Chemotherapy, vol. 52, no. 5, pp. 215–219, 2006.

F.-F. Zhang, M.-H. Jiang, L.-L. Sun et al., “Quantitative analysis of sitagliptin using the ¹⁹F-NMR method: a universal technique for fluorinated compound detection,” The Analyst, vol. 140, no. 1, pp. 280–286, 2015.

N. M. Do, M. A. Olivier, J. J. Salisbury, and C. B. Wager, “Application of quantitative ¹⁹F and ¹H NMR for reaction monitoring and in situ yield determinations for an early stage pharmaceutical candidate,” Analytical Chemistry, vol. 83, no. 22, pp. 8766–8771, 2011.

R. Martino, V. Gilard, and M. Malet-Martino, “Fluorine-19 or phosphorus-31 NMR spectroscopy: a powerful technique for biofluid metabolic studies and pharmaceutical formulation analysis of fluorinated or phosphorylated drugs,” in NMR Spectroscopy in Pharmaceutical Analysis, Elsevier, Oxford, UK, 2008.

F. Huang, S. Pan, Y. Pu, H. Ben, and A. J. Ragauskas, “¹⁹F NMR spectroscopy for the quantitative analysis of carbonyl groups in bio-oils,” RSC Advances, vol. 4, no. 34, pp. 17743–17747, 2014.

U. Holzgrabe, I. Wawer, and B. Diehl, NMR Spectroscopy in Pharmaceutical Analysis, Elsevier, Oxford, UK, 2008.

G. F. Pauli, B. U. Jaki, and D. C. Lankin, “Quantitative ¹H NMR: development and potential of a method for natural products analysis,” Journal of Natural Products, vol. 68, no. 1, pp. 133–149, 2005.

ICH, “Validation of analytical procedures and methodology,” in Proceedings of the International Conference on Harmonization (ICH '05), Geneva, Switzerland, 2005.