In collaboration with the Maryland State Police (MSP), the National Institutes of Standards and Technology (NIST) is developing a novel, targeted GC-MS method for drug screening that shows enhanced separation of isomers and increased sensitivity compared with traditional methods.
Currently, the MSP use a combination of color tests and GC-FID (gas chromatography with flame ionization detection) to screen samples for the presence of opioids, cathinones and cannabinoids. But at the virtual Forensics@NIST 2020 conference on Friday, Edward Sisco, research chemist at NIST, detailed the new workflow the federal agency has helped create that has shown an increase in retention time difference between compounds of interest. This is true particularly for isomers, which Sisco says is especially important as that’s an area where general screening methods typically experience separation difficulty.
In addition to enhancing separation of isomers and increasing sensitivity, Sisco and team wanted to shorten runtimes—but only if that did not sacrifice resolution.
“Our focus was to maintain peak areas but also see how far we could stretch percent retention difference for the different compounds within reason,” Sisco explained during his live presentation. “We didn’t want to go to a 90-minute method if we didn’t have to, but we want to get sufficient resolution. Our goal for sufficient resolution was at least a 1% retention time difference between compounds of interest, especially the isomers.”
For the study, NIST collaborated with Cayman Chemical, who developed and batched custom test mixtures for each of the three classes of drugs. This helped ensure repeatability, as there was minimal sample variability.
The first portion of the study looked to identify the effect of different columns on test mixture response to see which would provide the best sensitivity. With all parameters fixed beside the column itself, results indicated there was no major benefit or drawback to any particular column. That being said, Agilent Technology’s DB-200 GC Column showed the most uniform approach.
Once the column was chosen, the researchers went through a series of studies to optimize all other settings before comparing the current screening method to the novel workflow.
For opioids, the targeted GC-MS method showed a 135% difference in retention time and 93% in percent relative standard deviation (%RSD), or reproducibility of retention time. For cannabinoids, the results were even more significant: 220% better separation with 537% increased reproducibility. Most significant however, was cathinones, which illustrated a 262% difference in retention time but 0% increase in reproducibility of retention time.
“In both [cathinones and cannabinoids], we have not had any compounds with less than 1% retention time difference that were not differentiable by significant differences in the mass spec,” said Sisco. “We were able to separate basically all the isomers. For opioids, there were 8 pairs we were unable to separate with less than 1% retention time difference.”
In the end, runtimes were shorter or the same for two of three classes of drugs analyzed. The team was able to complete a cathinones run in 8 minutes, which was shorter than before, and a cannabinoids run in 12 minutes, which was the same as the traditional method. When analyzing opioids, the method extended to 30 minutes, a longer runtime than the previous method; however, researchers attributed at least some of that to the expanded compound library they utilized to ensure the targeted method was showing viability.
Based on the study results, the NIST research team is currently building automated data analysis and reporting features. Their next step is to quantify a comparison between the current and novel workflows. To do this, the team is taking a subset of adjudicated cases from MSP that fit into the 3 drug classes. Drug chemists will then analyze the samples using either workflow to identify and compare benefits, evaluate the level of detail gained at each step and quantify the time taken for each step.
“We will also identify potential weaknesses in the novel workflow to bring it toward a higher rigor analysis at the end of the day,” Sisco said.