Advanced quantification of drugs and exposure to cells

MSI

« Does the active compound reach specific cells or tissue substructures and in what quantity? » are key questions to investigate the potential efficacy in drug discovery. In biomarker discovery, the need to identify which cells express which biomarker is also important to understand the mechanism of action of a disease. To investigate the co-localization between biomarkers and drugs, Pearson Correlation Coefficient (PCC) is usually used but is not sufficient to clearly describe the distribution and concentration levels in cells. We present here different ways to quantify drugs and biomarkers in particular sub-structure of the tissue using latest Multimaging software development.

1) Drug or biomarker localized with specific cells:

Label free Mass Spectrometry Imaging (MSI) has been developed and used by ImaBiotech to detect and quantify drugs or biomarkers in to organs for almost a decade. Nevertheless,when the question of target exposure in cells a rises this becomes more complicated to analyze. It is impossible to quantify the drug exposure when the number of regions to select manually becomes too large or when regions of interest are very small, such as blood vessels, immune cells and other specific cells.To over come this issue, ImaBiotech’s R&D team has developed a software and a workflow to overlay different imaging techniques, segment the region of interest.

ImaBiotech(ROI) in order to quantify the amount of drug or biomarker inside a cell or cell aggregate. This workflow allows to assess the “Target Exposure and Engagement” that reach the cells or tissues. This can be applied to various differentare as, for example in CNS to assess the BBB penetration or in Oncology to understand the drug to target ratio.

2) Combination of MSI and Microscopy Data Analysis

To quantify how drugs cross the BBB or anti cancer drugs reach specific cells, we present a new workflow in ImaBiotech’s Multimaging software to automatically identify, annotate and segment the image based on the density or concentration of biomarkers. Using either Immuno-Histochemistry (IHC) technique or Mass Spectrometry Imaging, Multimaging software annotates the blood vessels in tumor or brain tissues. As shown in Figure 1, the workflow combines both Immuno-staining and Mass Spectrometry Imaging to detect cells or biomarkers as well as the drugs. After performing the imaging with microscopy, Mass Spectrometry Imaging and Multimaging software, we can overlay the two images with accuracy, using calibration spot into the different images. Then, the software quantifies with accuracy the quantity of drug or biomarkers that a reexposed to the specific cells or blood vessels.

3) Blood Brain Barrier (BBB) Penetration and Permeability

  • Image Analysis
    Clozapine is an anti-psychotic medication that works by blocking receptors in the brain for several neurotransmitters (chemicals that nerves use to communicate with eachother) including dopamine type 4 receptors, serotonin type 2 receptors, norepinephrine receptors, acetylcholine receptors, and histamine receptors. Clozapine has been dosed to mouse model and detected over a 10 micron scoronal section of the brain using MALD Imaging at 20 microns spatial resolution (InFigure2). As shown in the picture,Clozapine crosses the BBB but remains difficult to quantify due to a larger number of blood vessels. It has been quantified in different region of the brain and the signal of the Heme (that is present in erythrocytes) has been used to segment the image of blood vessels using Multimaging software. We used the workflow described in Figure1 in order to obtain the concentration per region of the brain as well as the concentration in blood vessels.
  • Quantification in brain and blood
    After segmentation and quantification, we can report the Clozapine concentration to reach 5-35μg/g of brain tissue with accuracy after removal of the concentration of blood vessels(Figure3). We used the results to quantify the brain to blood ratio in every region of the brain such as the cortex, the Hipp ocampus and the Thalamus.

4) Drug exposure in tumors

  • Tissue Annotation
    Different questions arise in oncology about the drug penetration over the vasculature or about the exposure to specific cells in the Tumormicro-environment(TME). It has been crucial to answer this question to evaluate the pharmacokinetics as well as the efficacy. To evaluate the localization and the activity of an anti-cancer drug (Epacadostat) exposure to T26 colon tumor model, we used the same process using MSI with immuno-staining. The drug is known to target IDO1 Enzyme that suppresses immune response in tumor at high concentration. We investigated the localization of the drug over its target using MSI imaging of drug by MSI (Figure5) and immuno-staining for the target biomarker(Figure4). Multimaging has been used to select few region of interest regarding the density of staining(Figure4).The software uses Machine Learning approach to train the system to segment and annotate the different regions of the different samples (Figure1).Then, Multimaging software automatically quantifies how the drug is related to each region based on concentration or density of the staining.
  • Quantification in Tumors
    After segmentation of the sample, we obtained 3 different regions of low, medium and high density of IDO1. What’s interesting with this classification, we obtained three times more drug in the region of high density (region 1 in Figure 4). At the opposite, the lowest concentration 25µg/g of drug has been measured in low density region (region 3) of the targets. This shows that a correlation exist between the concentration of the drug and the concentration of the target.
  • What about homogeneity and coverage?
    The software can automatically quantify and represent the region of exposure of the drug in different substructures of the tumor as well as the homogeneity or the coverage. In Figure 4, we found that region 1, corresponds to the ,high density of the target IDO1, also has the highest concentration, with a large coverage of the pixels that corresponds to the drug (Figure 5). Almost 100% of the pixels of these regions have been exposed to the drug while only 50% of the pixels cover the low density region. With all these information, we can get not only the concentration per cell types or sub-structure but we can also obtain how the compound distributes into these particular regions.
We present here a new workflow with an updated version of Multimaging, fully compatible with high resolution microscopy with cell recognition and tissue annotation. These tools allow to measure drug and biomarker into cells that avoid misinterpretation of target exposure, pharmacokinetics and pharmacodynamics and conduct to a higher level of confidence.

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