Journal of Analytical Methods in Chemistry

Journal of Analytical Methods in Chemistry / 2016 / Article

Research Article | Open Access

Volume 2016 |Article ID 7627823 | https://doi.org/10.1155/2016/7627823

Yang Liu, Zhaoxia Liu, Huaxin Yang, Lan He, "Direct Comparison of 19F qNMR and 1H qNMR by Characterizing Atorvastatin Calcium Content", Journal of Analytical Methods in Chemistry, vol. 2016, Article ID 7627823, 5 pages, 2016. https://doi.org/10.1155/2016/7627823

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

Academic Editor: Gowda A. Nagana Gowda
Received29 Jun 2016
Revised03 Aug 2016
Accepted09 Aug 2016
Published01 Sep 2016

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 [13], natural products characterization [4, 5], and reference substances quality control [69]. 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.

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 bywhere 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).

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 .


19F qNMR1H qNMR

Linearity, 0.99990.9999
Precision ()
 RSD (%)0.490.82
Repeatability ()
 RSD (%)0.730.62
LOQ (mg/mL)1.341.02

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.


Number Atorvastatin calcium content (%)
19F qNMR1H qNMR

193.994.8
292.295.1
393.895.1
493.194.9
592.895.7
692.696.4

Mean93.195.3
RSD (%)0.730.62

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

  1. 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. View at: Publisher Site | Google Scholar
  2. 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. View at: Google Scholar
  3. 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. View at: Publisher Site | Google Scholar
  4. 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. View at: Publisher Site | Google Scholar
  5. 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. View at: Publisher Site | Google Scholar
  6. 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. View at: Publisher Site | Google Scholar
  7. 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. View at: Publisher Site | Google Scholar
  8. 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. View at: Publisher Site | Google Scholar
  9. 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. View at: Publisher Site | Google Scholar
  10. F. Fardus-Reid, J. Warren, and A. Le Gresley, “Validating heteronuclear 2D quantitative NMR,” Analytical Methods, vol. 8, no. 9, pp. 2013–2019, 2016. View at: Publisher Site | Google Scholar
  11. 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. View at: Publisher Site | Google Scholar
  12. 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. View at: Publisher Site | Google Scholar
  13. 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. View at: Publisher Site | Google Scholar
  14. 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. View at: Publisher Site | Google Scholar
  15. 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. View at: Publisher Site | Google Scholar
  16. 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. View at: Google Scholar
  17. 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. View at: Publisher Site | Google Scholar
  18. U. Holzgrabe, I. Wawer, and B. Diehl, NMR Spectroscopy in Pharmaceutical Analysis, Elsevier, Oxford, UK, 2008.
  19. 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. View at: Publisher Site | Google Scholar
  20. ICH, “Validation of analytical procedures and methodology,” in Proceedings of the International Conference on Harmonization (ICH '05), Geneva, Switzerland, 2005. View at: Google Scholar

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.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views931
Downloads590
Citations

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.