Introduction: Gabapentin is an anticonvulsant drug prescribed for the treatment of neuropathic pain and seizures as well as for many off-label uses. Gabapentin is prescribed in high doses relative to other therapeutic drugs and is eliminated in urine predominantly in its unchanged form, which often results in extremely high concentrations of this compound occurring in patient urine samples. When analyzed by LC-MS/MS, high concentrations of gabapentin can have significant analytical implications, particularly for the compound amphetamine. Interference between gabapentin and amphetamine has been well documented and can result in signal suppression, poor peak shape, and shifting retention times. Other analytical challenges include saturation of the mass spectrometry detector and column overload. In this work, we explored several strategies to mitigate the effects of high gabapentin concentrations in urine samples.

Objectives: The objective of this study was to capture the analytical challenges presented by high concentrations of gabapentin in urine samples when analyzed by LC-MS/MS and investigate different strategies to mitigate them.

Methods: Using a Shimadzu 8045 LC-MS/MS system in ESI+ mode, a method developed for the analysis of 60 drugs of abuse in urine was used to test two samples: one containing 0.1 μg/mL of both gabapentin and amphetamine, and one containing 250 μg/mL of gabapentin and 0.1 μg/mL of amphetamine. After data collection, the signal of amphetamine was compared in each sample to determine if interference from gabapentin was occurring. The method utilized a Raptor Biphenyl 50 x 2.1 mm, 2.7 μm column with a mobile phase A of water and mobile phase B of methanol, both acidified with 0.1% formic acid. The flow rate was 0.6 mL/min, the column temperature was 45°C, and the injection volume was 5 μL. Gradient elution was employed, with a total run time of nine minutes. Following analysis, different strategies were tested to see if the interference between gabapentin and amphetamine could be resolved. These strategies included using alternate column lengths and diameters, decreasing injection volume, deoptimizing the analyte transition, and testing different mobile phase additives.

Results: Under the original method conditions tested, amphetamine showed a diminished signal and shifted retention time when a high concentration of gabapentin was present. The method was redeveloped using the strategies described. It was determined that the best approach for reducing interference was to fully chromatographically resolve gabapentin and amphetamine and ensure that gabapentin was the first compound to elute. This was done by switching the additive in mobile phase A from 0.1% formic acid to 10 mM ammonium formate, which affected the elution order of early eluting compounds. Resolution was further improved by switching from a 50 x 2.1 mm column to a 100 x 2.1 mm column. Detector saturation and column overload were improved by deoptimizing the mass transition for gabapentin and reducing the injection volume from 5 μL to 2 μL. Significant carryover was observed due to the high analyte concentrations and was eliminated by adding a small amount of 2-propanol to mobile phase B. Performance of the other analytes in the method was evaluated to ensure that they were not negatively affected by the change in method parameters.

Discussion: Interference between gabapentin and amphetamine, chromatographic overload, and detector saturation were all observed when analyzed under the original method conditions. Altering the mobile phase composition, using an extended column length, deoptimizing the mass transition, and reducing the injection volume were all successful in mitigating these analytical challenges. The addition of 2-propanol to mobile phase B helped to reduce carryover by washing contaminants off the analytical column more efficiently. The redeveloped method can be used to effectively analyze 60 compounds in urine without interference between gabapentin and amphetamine.

Introduction: Screening for volatile inhalants of abuse, as well as analyzing blood alcohol content, is commonly performed in forensic toxicology laboratories using headspace gas chromatography with flame ionization detection (HS-GC-FID). The analyses are performed using dual columns with specialized stationary phases that optimally separate these volatile compounds. While separation profiles of standard blood alcohol screening compounds are usually well characterized by column manufacturers on these application-specific columns, elution profiles of inhalants may not be as readily available. In addition, providing example chromatograms with static run conditions may not suit laboratories that want to experiment with faster run times, column dimensions, carrier gases, etc.

These issues can be solved by using computer modeling software to predict retention times of compounds of interest on a various stationary phases. In addition to the ability of the web-based software to help select a column and provide an optimized separation of compounds of interest on a specific stationary phase, the software can also be used to make changes to analytical conditions and observe the effect on elution, making it a valuable tool for method development and optimization.

Objectives: The intent of this project is to present retention time models for inhalants of abuse and blood alcohol analytes of interest on four unique stationary phases using web-based modeling software and verifying the accuracy of the models against actual analyses. This will allow for optimized separations with faster separations in addition to the evaluation of different carrier gas types.

Methods: To build a database for computer modeling of chromatographic separations, the following fused silica capillary columns were installed into an Agilent 7890A GC with a 5975C MSD: Rtx-BAC1, Rtx-BAC2, Rtx-BAC Plus 1, and Rtx-BAC Plus 2. More than 70 volatile inhalants of abuse, including solvents, refrigerants, nitrites (aka “poppers”) and their metabolites were analyzed on each column using three different temperature-programmed run conditions. Two of the analyses were used to create a retention model based on thermodynamic indices of analytes, and the third analysis was used to verify accuracy against the theoretical model. Once the models were finalized, a web-based modeler was used to optimize separations on each column, decrease analysis times, translate to different column dimensions or carrier gases, and make user input adjustments to parameters, such as carrier gas flow rate and oven ramp rates.

Results: Confirmation runs were in agreement with the theoretical modeled analysis, demonstrating acceptable accuracy of the retention time models using all four columns. Selection of various compounds of interest in the software successfully generated optimized separations on each column, allowing the user to choose the column or column set that best fits their needs. The ability to optimize the method using different carrier gases, temperatures, column flows, different column dimensions and film thicknesses was clearly demonstrated.

Discussion: Computer modeling of retention times in GC is a valuable tool to aid in column phase selection and method development/optimization. The use of this software greatly reduces the time required for manual method development since input changes update the results instantaneously. With libraries of 70+ volatile compounds on four different phases, users can select or input compounds of interest and then calculate elution profiles on each column. The software will present the number of coelutions on each column, allowing the user to select the most appropriate column for their analysis.

Introduction: Oral fluid is becoming an increasingly popular matrix due to its ease of collection. While oral fluid is a relatively simple matrix to collect, the collection kits can cause issues downstream. Most kits consist of an applicator with attached sponge, a tube filled with 3 mL of buffer solution, and a cap. The sponge is used to collect 1 mL of oral fluid and is then placed in the buffer solution to ensure analyte stability and inhibit bacterial growth. The total volume of the solution for testing should be 4 mL (1 mL of oral fluid and 3 mL of buffer); however, it is often very difficult to recover the full 4 mL of solution. There are different techniques to manipulate the sponge and improve sample recovery. Some popular techniques include manual compression and centrifugation. The goal is to remove the full volume of liquid from the sponge to improve analyte recovery. In this work, these two techniques will be compared by examining volume recovery and analyte recovery.

Objectives: The primary objective of this work is to demonstrate the advantages of incorporating a centrifugation step to sample preparation and its impacts on volume and analyte recovery when performing analysis of drugs of abuse and (DoA) in oral fluids by LC-MS/MS.

Methods: An LC-MS/MS method was developed using a biphenyl analytical column. Mobile phase A consisted of 0.1% formic acid in water and mobile phase B consisted of 0.1% formic acid in methanol. A total of 31 commonly abused drugs were separated under gradient conditions with a total cycle time of seven minutes. Samples were prepared in synthetic oral fluid and combined with Quantisal buffer. Two sample recovery techniques were compared and tested in triplicate: manual compression and centrifugation. Samples were prepared using a salt-assisted liquid-liquid extraction (SALLE) with a saturated sodium chloride solution. Samples were then dried down under nitrogen and reconstituted in 90:10 mobile phase A: mobile phase B, before moving to the instrument for analysis.

Results: The two techniques were compared by examining total volume removed and analyte recovery. Volume recovery was tested by pouring the solution into a graduated cylinder and recording the total volume recovered using each technique. When using centrifugation, on average, an additional 200 μL were collected compared to the manual compression. Analyte recovery was compared by spiking a known concentration, 50 ng/mL, into each of the samples. These samples were evaluated using a calibration curve prepared by only using 1 mL of fortified synthetic oral fluid and 3 mL of buffer. The recovery and peak area of all analytes improved when using the centrifuge. Accuracy and precision of the techniques were also compared. At ±15% of target value, only four analytes fell withing this range when using the manual compression technique, compared to centrifugation, which had 21 analytes within range. This improved to 25 analytes when the acceptance criteria was increased to ±20% of the target where the manual compression was only at 12. When assessing precision, the centrifugation technique yielded lower %RSD values for 24 analytes as compared to manual compression. The use of extraction aides was also investigated and compared to these accuracy and precision results.

Discussion: In this work, two different techniques were compared to remove liquid from the sponge of the oral fluid collection kits. Through examining volume recovery and analyte recovery, it was clear that the centrifugation technique showed the best results for total volume recovered as well as increased analyte recovery when analyzed quantitatively. Centrifugation can add time to the method, but this work highlights the necessity of centrifugation when analyzing DoA in oral fluid.