Spatial Mass Spectrometry

MSI data are processed to generate ion distribution images and, where quantitative analysis is required, to create tissue concentration maps calibrated using reference standards. To measure absolute drug concentrations at tissue level, TNO offers the possibility to use microtracer labeled compounds.

By (spatial) mass spectrometry data, paired with AMS-based microtracer quantification, absolute drug metabolite concentrations can be assigned at the tissue level, with the spatial distribution pattern providing the mechanistic context that bulk tissue LC-MS/MS measurement cannot. The resulting dataset combines absolute quantification with spatial resolution in a single analytical workflow.

Because MSI is performed on the same tissue section from which histological stains and immunofluorescence can be obtained, the molecular distribution maps can be co-registered with morphological tissue context. This overlay directly correlates drug distribution with histological lesion boundaries, disease-relevant cell populations, or biomarker expression patterns.

Interpretation is strengthened through collaboration with our in-house pathologists and domain specialists, who help place the spatial molecular data in the right biological and disease context. Together, this provides the mechanistic interpretation layer that transforms distribution data into proof-of-mechanism evidence.

In atherosclerosis programmes, the therapeutic target is typically a specific cell population within a complex, spatially heterogeneous lesion. Whether a compound reaches the macrophage-rich necrotic core, the fibrous cap, or the medial smooth muscle layer is mechanistically decisive, and invisible to plasma pharmacokinetics.

MSI maps drug distribution within aortic root cross-sections, directly correlated with Oil Red O staining or immunofluorescence marking of plaque subpopulations, providing the spatial proof of target site penetration that regulatory and partnering audiences increasingly require.

In MASLD and MASH programmes, hepatic drug distribution varies across the lobular architecture. Portal zone hepatocytes, centrilobular regions and activated stellate cell populations may respond differently to the same nominal tissue exposure. MSI resolves compound distribution at lobular resolution and can simultaneously map endogenous lipid species and metabolic markers that confirm target pathway engagement.

Blood-brain barrier penetration is one of the most consequential and frequently undercharacterised properties in CNS drug development. Plasma exposure provides no information on regional brain distribution, and whole brain homogenate data misses the spatial heterogeneity that determines whether therapeutic concentrations are reached in the relevant structure.

MSI maps compound distribution across brain regions including cortex, hippocampus, striatum and cerebellum in the same section, distinguishing grey and white matter penetration and identifying any regional exclusion that would compromise target engagement.

Spatial mass spectrometry data are interpretable only in the context of the diseased tissue they describe. Our platform is applied within validated, well-characterised disease models including the TNO Ldlr-/-.Leiden mouse for MASLD and atherosclerosis, the APOE*3-Leiden and APOE*3-Leiden.huCETP models for cardiovascular indications, renal models and fibrosis models covering skin, lung, liver and kidney. The tissue phenotypes in these models are extensively characterized.

For biotech and pharma teams building the mechanistic case for an IND filing, a partnering discussion or a preclinical publication, the combination of tissue-level distribution data, proof of target site penetration, and pathway-level mechanistic readouts represents the kind of evidence package that advances a programme's credibility at a stage where credibility is still being established.

We build that package within a single integrated study, rather than requiring multiple contracted studies across multiple providers with the coordination overhead and data integration risk that entails.