Diagnosis of Agglomeration and Crystallinity of Active Pharmaceutical Ingredients in Over the Counter Headache Medication by Electrospray Laser Desorption Ionization Mass Spectrometry Imaging

Agglomeration of active pharmaceutical ingredients (API) in tablets can lead to decreased bioavailability in some enabling formulations. In a previous study, we determined that crystalline APIs can be detected as agglomeration in tablets formulated with amorphous acetaminophen tablets. Multiple method advancements are presented to better resolve agglomeration caused by crystallinity in standard tablets. In this study, we also evaluate three “budget” over-the-counter headache medications (subsequently labeled as brands A, B, and C) for agglomeration of the three APIs in the formulation: Acetaminophen, aspirin, and caffeine. Electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) was used to diagnose agglomeration in the tablets by creating molecular images and observing the spatial distributions of the APIs. Brand A had virtually no agglomeration or clustering of the active ingredients. Brand B had extensive clustering of aspirin and caffeine, but acetaminophen was observed in near equal abundance across the tablet. Brand C also had extensive clustering of aspirin and caffeine, and minor clustering of acetaminophen. These results show that agglomeration with active ingredients in over-the-counter tablets can be simultaneously detected using ELDI-MS imaging.

Rapid diagnosis of drug agglomeration and crystallinity in pharmaceutical preparations by electrospray laser desorption ionization mass spectrometry imaging

In this study we evaluate the applicability of electrospray laser desorption ionization mass spectrometry imaging (ELDI-MSI) to interrogate tablet formulations for the spatial distributions of ingredients. Tablet formulations with varying amounts of crystalline acetaminophen (the active pharmaceutical ingredient, API) were analyzed to determine if crystallinity could be evaluated via ELDI-MSI. ELDI-MSI concurrently imaged the (API, binders, and surfactants. The spatial distributions of amorphous API were very similar to that of the surfactants and different from that of crystalline API. The higher the crystallinity in the tablet formulation, the more agglomeration of the active ingredient was observed by ELDI-MSI. This study shows the capability of ELDI-MSI to diagnose agglomeration and crystallinity content in pharmaceutical preparations with little to no sample preparation. The ability to concurrently image APIs with other components provides valuable information as to their form in the tablet.

Light-Dependent Changes in the Spatial Localization of Metabolites in Solenostemon scutellarioides (Coleus Henna) Visualized by Matrix-Free Atmospheric Pressure Electrospray Laser Desorption Ionization Mass Spectrometry Imaging

The visualization of foliage color in plants provides immediate insight into some of the compounds that exist in the leaf. However, many non-colored compounds are also present; their cellular distributions are not readily identifiable optically. In this study we evaluate the applicability of mass spectrometry imaging (MSI) via electrospray laser desorption ionization (ELDI) to reveal the spatial distribution of metabolites. ELDI-MSI is a matrix free, atmospheric pressure ionization method that utilizes a UV laser coupled with supplemental ionization by electrospray. We specifically applied ELDI-MSI to determine the spatial distribution of metabolites in Coleus Henna half leaves that were grown with half-sections either fully illuminated or shaded. We monitored dynamic changes in the spatial distribution of metabolites in response to the change of illumination every 7 days for a 28 day period. A novel source-sink relationship was observed between the 2 halves of the experimental leaf. Furthermore, Coleus Henna leaves present visually recognizable sectors associated with the differential accumulation of flavonoids. Thus, we correlated the effect of differential illumination and presence or absence of flavonoids with metabolic changes revealed by the accumulation of carbohydrates, amino acids, and organic acids. The results show the potential of ELDI-MSI to provide spatial information for a variety of plant metabolites with little sample preparation.