Developing SERS Methods for Drug Detection

November 7, 2016

Surface-enhanced Raman scattering (SERS) has the capability of enhancing the signal from analytes present in low concentrations, and the detection of drugs present in human and other samples is an important application of this technique. Roy Goodacre is a Professor of Biological Chemistry in the School of Chemistry at the University of Manchester, and he and his group have been developing SERS methods for analyzing drugs in various solutions, including human biofluids, with the ultimate goal of monitoring dosing and drug therapy. He recently spoke to us about this work.

Surface-enhanced Raman scattering (SERS) has the capability of enhancing the signal from analytes present in low concentrations, and the detection of drugs present in human and other samples is an important application of this technique. Roy Goodacre is a Professor of Biological Chemistry in the School of Chemistry at the University of Manchester, and he and his group have been developing SERS methods for analyzing drugs in various solutions, including human biofluids, with the ultimate goal of monitoring dosing and drug therapy. He recently spoke to us about this work.

One of your recent publications discusses the quantitation of nicotine and its two major metabolites using colloid-based surface enhanced Raman scattering (SERS) with chemometrics (1). Can you please briefly describe this approach and discuss the significance of the study?

Raman spectroscopy is used to generate molecular-specific spectra from samples under analysis. These spectra provide detailed information about the molecule or molecules under investigation. However, it is quite a weak effect and has limited utility unless the signal is increased in some way. Over the last decade or so we have been developing SERS to enhance the signal from analytes that are present in low concentrations. One of the groups of molecules we are interested in are drugs-whether illicit or legal-with the aim of effecting identification and quantification of the drug. Most drug detection studies using SERS have so far been limited to measuring single drugs, and usually are further limited to the detection of the drug itself, rather than any drug metabolites that may be found when the drug is used and recovered from the blood or urine of someone who has taken it. So the main significance of the study is that we have been able to identify and quantify nicotine and its two major metabolites, cotinine and trans-3’-hydroxycotinine, in mixtures.

In this approach, we coupled Raman spectroscopy with silver nanoparticles for SERS and optimized the environment so that the three analytes could associate directly, or get close enough to the silver surface, so that SERS could occur. This coupling was needed because the SERS spectra of nicotine and its metabolites change as a function of the pH of the environment. This variation in the SERS spectra is all to do with the pKa of the molecules being different, so we ended up taking SERS spectra at three different pH values. After this step we then used some chemometrics based on partial least squares regression (PLSR) to correlate in a multivariate way the SERS spectra with the concentrations of the three target determinands. The whole process was validated and the results were great-we were very happy with the results, and they were published in a very good journal.

How is this technique an improvement over previous methods?

The main advantage was that the three analytes were measured simultaneously. This means there was no need for a separation step such as liquid chromatography. In addition, the instrument we used was relatively small and can be easily used for on-site analysis. Indeed, there are plenty of handheld Raman instruments now on the market that allow field-portable measurements in a kind of point-and-shoot analysis. We’ve reviewed the advantages of on-site analyses using Raman spectroscopy recently in a paper in Analytical Methods (2).

You and your group also used SERS to detect a legal synthetic derivative (MDAI) of a banned drug in solution (3). How does the limit of detection obtained using this method compare with those of other analytical methods for detecting the drug? How would the approach need to be modified so that it could be used for routine on-site drug testing?

That’s a great question and of course it’s necessary that for any new method to be adopted, the limit of detection (LOD) must be equivalent to or better than current methods, and of course the LOD must be below the typical drug levels seen in users.

The LOD we achieved for MDAI using SERS was 5.4 × 10−5 M. Even though this work is a year old there have been no reports of LOD using other methods, other than a rather insensitive technique we mentioned in the paper based on microcrystalline analysis that has an LOD of around 1 × 10−3 M. It’s likely that if a liquid chromatography–mass spectrometry (LC–MS) method were developed it would have similar detection limits, especially when MRM is used, because it uses specific scans for MS-MS analyses. Of course, LC–MS lacks portability.

For routine on-site drug testing, what is needed in addition to a handheld device are databases of SERS spectra that “unknown” white powders can be matched against for identification. These databases may then also include details of specific SERS peaks that are best for quantification. This approach is yet to be done for large numbers of drugs using SERS. There are people working in this area and there’s a very nice paper out by Steve Bell’s group in Analyst this year on infrared and Raman screening of many novel psychoactive substances (4).

A third study in your lab involved using the colloid-based SERS technique with a portable Raman system to analyze the opioid tramadol first in water and then in artificial urine (5). What challenges were overcome in this study? What are the potential benefits of this approach for clinical analysts?

The detection of tramadol was another piece of research that further demonstrates that SERS should have general utility for the analysis of drugs, admittedly in an artificial scenario where synthetic urine was used. We have just had accepted into Analytical Chemistry a paper in which we describe the development of SERS for the direct detection and quantification of propranolol (a beta-blocker) spiked into real-world samples of human serum, plasma, and urine at physiologically relevant concentrations (6). We are also close to detection and quantification of drugs and metabolites in real patient samples, and hope to have data to share with you soon, so please watch this space.

The benefit of these methods for clinical analysts will be the ability to perform at-patient analysis for speedy diagnostics. This approach would remove the need to send a sample off to a central testing lab when waiting for the answer could cost lives.

What are the next steps in your research with Raman spectroscopy?

Within this particular topic area our next steps are to develop SERS to a point where it could be used for routine analysis of drugs and their metabolites in human samples, which would mean that SERS could be used for monitoring drug dosing and therapy for precision medicine. For substance abuse then it would be possible to test an individual for longer-lived drug metabolites that may still be present in plasma or urine long after the drug of abuse has been cleared from the system.

This is only one of the areas we work in with Raman spectroscopy. We are also developing Raman for on-site food security, live cell imaging of eukaryotic cells, bacterial characterizations, and biopharmaceutical applications. If your readers are interested in those areas they can get a flavor of what else we do with Raman spectroscopy (and also MS-based metabolomics) on our group web site: http://www.biospec.net

References

  • O. Alharbi, Y. Xu, and R. Goodacre, Analyst139, 4820–4827 (2014).

  • D.I. Ellis, H. Muhamadali, S.A. Haughey, C.T. Elliott, and R. Goodacre, Analytical Methods7, 9401–9414 (2015).

  • S. Mabbott, O. Alharbi, K. Groves, and R. Goodacre, Analyst140, 4399–4406 (2015).

  • L.E. Jones, A. Stewart, K.L. Peters, M. McNaul, S.J. Speers, N.C. Fletcher, and S.E.J. Bell, Analyst141, 902–909 (2016).

  • O. Alharbi, Y. Xu, and R. Goodacre, Analyst140, 5965–5970 (2015).

  • A. Subaihi, L. Almanqur, H. Muhamadali, N. AlMasoud, D.I. Ellis, D.K. Trivedi, K.A. Hollywood, Y. Xu, and R. Goodacre, Analytical Chemistry, in press (2016). DOI: 10.1021/acs.analchem.6b02658