New, better and faster system to detect cannabis use in saliva

Cannabis is the most widely used illegal drug in Europe. It is estimated that around 8% of adults used cannabis in 2022. The widespread abuse of this substance has health consequences and is understood as a relevant social problem. A fundamental ally to control its use and avoid these health problems would be a rapid, simple and reliable analysis that uses an accessible, easily extracted and non-invasive fluid, such as saliva.

With the aim of speeding up this type of analysis and making it effective in smaller saliva samples, the FQM-215 – Affordable and Sustainable Sample Preparation group of the University of Córdoba (UCO) worked together with the GICAPC group of the University of Valencia, both in Spain, in the design of a new analysis technique that simplifies sample processing and makes it possible to determine the presence of THC (tetrahydrocannabinol) with just 0.25 milliliters of saliva.

To do this, a technique known as dispersive microextraction by sorption with a miniaturized stirring bar is used, which “consists of adding a material capable of extracting the analytes in the sample (in this case, tetrahydrocannabinol found in saliva) that has magnetic properties, such that when a very small magnet (the stirring bar) is introduced into the device containing the saliva, magnetic agitation is produced that causes a vortex to form, dispersing those particles that interact with the analytes present in the sample. When the agitation is stopped, the particles with the analytes are again attracted by the magnet,” explains UCO researcher Jaime Millán Santiago. In this way, the THC molecules in saliva could be extracted very quickly. “We reduce to 2 steps what would otherwise be 5,” says UCO professor Marisol Cárdenas.

After the sample preparation stage, comes the second step. “We transfer the miniaturized magnet coated with the particles that have trapped the THC that was in the sample and we transfer it to a needle, to which we apply a high voltage and add an organic solvent capable of breaking the interaction between the extracting material and the THC, generating an electrospray that is introduced into the mass spectrometer” explains the researcher. In just two steps and with a very small sample of saliva, the concentration of cannabis in saliva can be known in just a few minutes. This technology, which, as Professor Rafael Lucena explains, “could already be incorporated into routine laboratory analysis methods” stands out for its sensitivity, precision and accuracy.

Members of the research team from the University of Cordoba. From left to right: Rafael Lucena, Marisol Cardenas and Jaime Millan. (Photo: UCO)

This technology is possible thanks to the union of two innovations developed by the teams from Córdoba and Valencia. While the extraction and preparation of the sample has been designed by the University of Valencia, the analysis method has been developed by this team from the Department of Analytical Chemistry at the University of Córdoba. “We use stainless steel needles (cheap and easy to acquire) and we take advantage of the non-metallic part of the needle to attach the magnet with THC retained on the extracting material and, to immobilize it, we use another external magnet, thus allowing the solvent flow to pass and elute the analytes, which come out of the tip of the needle as a spray that enters the analysis instrument, where the THC concentration is determined” describes Jaime Millán, one of the creators of this method.

The research and development team, headed by Andreu L. López-Juan, from the Chemical Institute for Energy and the Environment (IQUEMA), affiliated with the University of Córdoba (UCO) in Spain, presents the technical details of its new system in the academic journal Analytical Chemistry, under the title “Coupling Miniaturized Stir Bar Sorptive Dispersive Microextraction to Needle-Based Electrospray Ionization Emitters for Mass Spectrometry: Determination of Tetrahydrocannabinol in Human Saliva as a Proof of Concept”. (Source: UCO)