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Biospective's APP/PS1 mouse model of Alzheimer’s disease develops progressive amyloid-beta pathology with a well-defined spatiotemporal pattern. This robust amyloid model demonstrates Aβ plaques, cerebral amyloid angiopathy (CAA), neurodegeneration, and neuroinflammation (including activated microglia & reactive astrocytes). Biospective offers this validated APP transgenic mouse as part of its preclinical CRO services, supporting efficacy testing and target engagement studies using translational endpoints.

While a range of APP transgenic mouse models of Alzheimer's disease with human amyloid-beta expression exist, they each have their respective strengths and weaknesses.  Our APP/PS1 transgenic mice are well-suited for preclinical studies to support drug development pipelines, including efficacy testing, mechanism-of-action studies, PK/PD, and target engagement. A comparison of the APP/PS1 model to the 5xFAD mouse model can be found in our Resource - 5xFAD Mice & APP/PS1 Mice - A Comparison of Amyloid-β Mice for Alzheimer's Drug Development.

In this model, we have rigorously validated pathologic changes in the brains of these mice, including Aβ-related pathology, activated microglia, reactive astrocytes, and the spatial relationships between plaques and the neuroinflammatory microenvironment. We are well resourced to handle large-scale studies to generate high-quality data for our global biotech and pharmaceutical partners.

Overview of the APP/PS1 Model of Alzheimer's Disease

An mouse model with APP and PS1 mutations that is well-suited for preclinical drug development.

At Biospective, we have validated the APP/PS1 (ARTE10) transgenic mouse model of Alzheimer's disease. These mice feature pathologic changes that mimic  of these key hallmarks of human disease, including:

  • Amyloid-beta (Aβ) plaques: Plaques begin to form in the anterior cerebral cortex at ~3 months-of-age and then progress with a time-dependent increase in burden and spatial extent.

  • Cerebrovascular amyloid: Aβ deposits in leptomeningeal vessels and deep arterioles.

  • Robust neuroinflammation: Pronounced activation of microglia and reactive astrocytes in the "neighborhood" of the plaques.

  • Predictable time course: The spatiotemporal progression of pathology is well understood and the readouts are reproducible.

These mice are readily available at Biospective at ages appropriate for preclinical therapeutic studies.

mIF of APP/PS1 showing amyloid plaques

Multiplex IF of the brain of a 9 month-old APP/PS1 mouse showing a high Aβ pathology burden.

Graph of progressive increase in amyloid-beta burden in APP/PS1 mice.

Time-dependent β-amyloid plaque formation in the frontal cortex of APP/PS1 mice.

Amyloid plaques & vascular amyloid in APP/PS1 mice.

Aβ plaques & cerebrovascular amyloid angiopathy (CAA) in 9 month-old APP/PS1 mice.

Astrocytes & microglia in APP/PS1 mice.

Microglia (Iba1; orange) and astrocytes (GFAP; violet) in the cerebral cortex of APP/PS1 mice.

A Novel Model of Alzheimer's Disease — Biospective's Amyloid-β and Tau Co-Pathology Mouse

An innovative mouse model based on AAV-driven expression of human tau in APP/PS1 mice.

A current limitation of many models of Alzheimer's disease is that they do not fully capture the spectrum of pathology that defines the human disease. To overcome this obstacle, our team at Biospective has developed and characterized a "co-pathology" model that combines transgenic (APP/PS1 mice) and AAV vector-based methodologies.

This co-pathology model features the Aβ pathology characteristic of the APP/PS1 mouse, as well as intracellular phosphorylated wild-type human tau. In addition, this mouse model develops marked neuroinflammation, neurodegeneration, and associated functional impairments, reflecting the complex pathological interactions relevant to human Alzheimer's disease.

Co-Pathology Model - amyloid & tau

Amyloid-beta (red) and phospho-tau (green) demonstrating the co-pathology in this novel Alzheimer's disease mouse model.

Co-Pathology Model - tau & microglia

Phosphorylated tau (AT8; green) & microglia (Iba1; orange) in the cerebral cortex of the Biospective's co-pathology mice.

Learn more about Biospective's novel Aβ & tau co-pathology model and its applications in Alzheimer's disease drug development.

MORE INFORMATION ON Aβ & TAU CO-PATHOLOGY MICE

Research Study — Spatiotemporal Evolution of Amyloid Plaques & Neuroinflammation in APP/PS1 Mice 

A detailed characterization of Aβ plaques and the "inflammatory microenvironment" in the APP/PS1 Alzheimer's disease mouse model. 

In this research study, the Biospective team has characterized the progression of pathology in the APP/PS1 amyloid-beta mouse model of AD. Mice were studied at 6, 9, and 12 months-of-age, and compared to control 6 month-old mice using our proprietary, automated image processing & analysis platform.

Animated workflow for Aβ plaque microenvironment analysis.

In this research study, we found: 

  • A progressive, highly significant, stepwise increase in the density of amyloid plaques in the different age groups.
  • A global increase in neuroinflammation, as quantified by microglia (Iba1) and astrocyte (GFAP) stain density, in a spatiotemporal pattern that follows the amyloid-beta pathology.
  • Advanced metrics that provide more sensitive measures of the disease state:
    • The density of activated microglia
    • The mean astrocyte hypertrophy score
    • The ratio of microglia-to-astrocytes in the plaque proximity
  • The higher sensitivity of these advanced metrics would mean that, in the context of a preclinical therapeutic efficacy study, a smaller effect could be detected using the same number of animals. In addition, these metrics would be particularly relevant for therapeutics that target microglia, astrocytes, microglia-astrocyte interactions, or the interaction of glial cells with Aβ plaques. 

Interactive Presentation of our Research Study

In the "Image Interactive" below, you can find results from our amyloid-beta plaque and inflammatory microenvironment analysis, including high-resolution Multiplex Immunofluorescence tissue sections of brains from the APP/PS1 mouse model and control mice.

How to use Our Interactive Viewer
Navigate through the “Image Story” via the left-hand panel or the on-screen arrows. You can pan around high-resolution microscopy images with your mouse, and zoom in/out using the scroll wheel or the +/- controls. The Control Panel (top-right) allows toggling of image channels and segmentation overlays. For the best experience, we recommend switching to full-screen mode. This Interactive Presentation enables you to explore the model’s neuropathology and associated functional deficits in detail, as if looking directly down the microscope.

Quantitative Amyloid Plaque Microenvironment Analysis in the APP/PS1 Mouse Model

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Authors: Lionel Breuillaud, Laurent Potvin-Trottier, Ashmala Naz, and Barry J. Bedell

Alzheimer’s disease is a progressive neurodegenerative disorder marked by the accumulation of misfolded amyloid-β (Aβ) aggregates and the formation of extracellular amyloid plaques. APP/PS1 transgenic mice are a well-established double-transgenic model that robustly develops early-onset amyloid pathology in adulthood. The APP/PS1 (ARTE10) mouse model co-expresses human APP (Swedish mutations) and PS1 (M146V mutation) under the Thy1 promoter.

In this study, 5 m brain sections from 6, 9, and 12 month-old ARTE10 mice and a 6 month-old WT controls (n=11, 13, 10, and 10, respectively) were processed with a multiplex immunofluorescence protocol for amyloid (OC), microglia (Iba-1), astrocytes (GFAP), and nuclei (DAPI). This approach enables simultaneous visualization and quantification of plaques, microglial and astrocytic morphology, and microenvironmental remodeling, offering an integrative view uniquely suited for preclinical drug evaluation. In this Interactive Presentation, we highlight key metrics quantified in this study:

  • Amyloid plaque density

  • Iba-1 and GFAP stain density

  • Activated microglia density

  • Astrocyte hypertrophy score

  • Density of glial cells as a function of distance from the plaque and plaque size

  • Ratio of microglia-to-astrocytes in the plaque proximity

Microglia and astrocytes are known to play a key role in neurogenerative disorders (Hulshof, 2022; Gao, 2023). Under stress conditions, these glial cells show drastic changes in their morphology (Savage, 2019; Patani, 2023). In addition, these cells play a key role in the remodeling of the plaque microenvironment (Mallach, 2024). Therefore, precise characterization of glial cells and their interaction with the plaque microenvironment could provide critical insight in a preclinical therapeutic efficacy study.

To navigate though this Image Story, you can use the arrows and/or the Table of Contents icon in the upper right corner of this panel.

Image explaining the functions of the different buttons of the navigator

You can also interact with the microscopy image in the Image Viewer on the right at any time to further explore this high-resolution data.

Amyloid Plaques are Present in 6 Month-Old APP/PS1 Mice

At 6 months-of-age, initial amyloid plaque deposition becomes detectable, with plaques emerging in specific brain regions, such as the cerebral cortex. At this stage, plaque burden remains relatively low and regionally restricted, representing an early phase of amyloid- pathology prior to widespread cortical and subcortical involvement.

Comparison of Amyloid Plaque density in Control (6 month) and ARTE 10 (6, 9, and 12 month) old mice

Amyloid plaque density in the piriform cortex and posterior cortex of wild-type (6 months-old; control) and ARTE10 mice at 6, 9, and 12 months-of-age. Data are presented as mean ± SEM. Statistical analyses were performed using Brown–Forsythe and Welch ANOVA, followed by Dunnett’s T3 multiple-comparisons test. * : p<0.05, ** : p<0.01, *** : p<0.001, **** : p<0.0001​.

Dramatic Increase in Amyloid Burden at 9 Months-of-Age

Between 6 and 9 months-of-age, there is a pronounced increase in both the number and size of amyloid plaques. Amyloidosis becomes prominent across multiple brain regions, including areas that previously exhibited minimal pathology, such as the entorhinal cortex and hippocampus. Plaques display greater morphological heterogeneity, with both dense-core and diffuse types emerging, reflecting the progressive maturation of amyloid- pathology. This stage marks a transition from early, regionally-restricted deposition to widespread cortical and subcortical involvement, accompanied by increased microglial and astrocytic responses in the surrounding tissue.

Comparison of Amyloid plaque density in entorhinal cortex and hippocampus region control (WT; 6 month) and ARTE 10 (6,9,12 month) old mice

Amyloid plaque density in the entorhinal cortex and hippocampus of wild-type (6 months; control) and ARTE10 mice at 6, 9, and 12 months-of-age. Data are presented as mean ± SEM. Statistical analyses were performed using Brown–Forsythe and Welch ANOVA, followed by Dunnett’s T3 multiple-comparisons test. * : p<0.05, ** : p<0.01, *** : p<0.001, **** : p<0.0001​.

Continued Progression at 12 Months-of-Age

From 9 to 12 months-of-age, amyloid accumulation continues, though the rate of increase is less pronounced than in earlier stages. Brain regions that were relatively spared at younger ages, such as the midbrain, now exhibit higher plaque densities. In the regions analyzed, plaque density showed an upward trend; however, the increases did not reach statistical significance, suggesting that amyloid deposition is approaching a plateau in these areas. This stage reflects the maturation and stabilization of amyloid- pathology, with ongoing local microglial and astrocytic responses in the vicinity of existing plaques.

Comparison of amyloid plaque density in the midbrain and thalamic regions of control (WT; 6 months) and ARTE10 mice at 6, 9, and 12 months of age.

Amyloid plaque density in the midbrain and thalamus of wild-type (6 months-old; control) and ARTE10 mice at 6, 9, and 12 months-of-age. Data are presented as mean ± SEM. Statistical analyses were performed using Brown–Forsythe and Welch ANOVA, followed by Dunnett’s T3 multiple-comparisons test. * : p<0.05, ** : p<0.01, *** : p<0.001, **** : p<0.0001​.

Absence of Plaques in Control WT Mice

In contrast, in wild-type (WT) animals, no amyloid plaque deposition is detected, and neuroinflammatory markers remain at baseline levels. Microglia show predominantly ramified morphologies and astrocytes show minimal reactivity, establishing a baseline reference for pathology-driven changes observed in the transgenic mice.

Progressive Microgliosis

The image depicts Iba-1–labeled microglia in a 9-month-old mouse. In this model, microgliosis closely follows the spatiotemporal progression of OC-positive amyloid pathology and can be quantitatively assessed through measurements of Iba-1 staining density.

Iba-1 Staining and Activated Microglia Density in the Anterior Cortex and Hippocampus of control (WT;6 month) and ARTE10 (6, 9, and 12 month) old Mice

Iba-1 stain density and activated microglia density in the anterior cortex and hippocampus of wild-type (6 month-old; control) and ARTE10 mice at 6, 9, and 12 months-of-age. Data are presented as mean ± SEM. Statistical analyses were performed using Brown–Forsythe and Welch ANOVA, followed by Dunnett’s T3 multiple-comparisons test. * : p<0.05, ** : p<0.01, *** : p<0.001, **** : p<0.0001​.

To derive a more sensitive metric of disease state, we applied our microglial morphology analysis pipeline to quantify the density of activated microglia. Detected microglial contours are color-coded based on morphological classification, with ramified microglia shown in green and activated microglia in purple. Only microglia with nuclei fully in-plane were included in the the detection step and analysis.

Quantification of activated microglial density revealed a similar pattern of progressive microgliosis, but with substantially greater statistical sensitivity than measurements based solely on Iba-1 staining density. Notably, the 6- to 9-month comparison reached statistical significance in the hippocampus and showed increased significance in the anterior cortex. In a preclinical therapeutic efficacy setting, this increased sensitivity could enable detection of smaller treatment effects without increasing cohort size.

To learn more about our microglia morphology analysis pipeline, please see our Innovation Presentation on microglia morphology.

Progressive Astrogliosis

Similarly, we quantified the astrogliosis by measuring the stain density of GFAP, as shown on this slide of from 9 month-old mouse. Astrogliosis also followed the temporal trend of the amyloid plaque density.

GFAP Staining Density and Astrocyte Hypertrophy in the Piriform and Posterior Cortex of Wild-Type and ARTE10 Mice

GFAP stain density and mean hypertrophy score in the piriform cortex and posterior cortex of wild-type (6 month-old; control) and ARTE10 mice at 6, 9, and 12 months-of-age. Data are presented as mean ± SEM. Statistical analyses were performed using Brown–Forsythe and Welch ANOVA, followed by Dunnett’s T3 multiple-comparisons test. * : p<0.05, ** : p<0.01, *** : p<0.001, **** : p<0.0001​.

We applied our pipeline for astrocyte detection and morphology analysis, this time measuring the mean hypertrophy score of astrocytes in each ROI. The contour of in-plane astrocytes is shown colored by their morphology: green for normal astrocytes and orange for reactive astrocytes.

Similar to the microglia analysis, the mean hypertrophy score showed a similar increase with age, but with higher statistical significance than GFAP stain density alone. For example, the early changes in the piriform cortex at 6 months-of-age became significant as compared to control.

For more information about our astrocyte morphology analysis, please see our Innovation Presentation on astrocyte morphology.

Microglia Accumulate Directly on Plaques, while Astrocytes are Most Distant

We next characterized the plaque-associated microenvironment by quantifying glial cell density as a function of distance from individual amyloid plaques. Spatial profiling was performed in 10 µm concentric increments extending outward from the plaque boundary. For clarity of visualization, only the outer boundary of the 20 µm periplaque microenvironment is displayed.

This analysis revealed a pronounced enrichment of activated microglia in direct contact with amyloid plaques. The accompanying heatmap illustrates activated microglial density as a function of distance from the plaque across experimental groups, with the color scale ranging from black (low density) to beige (high density). Activated microglia density was very high in direct plaque contact and low elsewhere, highlighting the highly localized nature of plaque-associated microglia.

Heatmap showing that the density of activated microglia is highly enriched directly on the plaque in the different age groups

Density of activated microglia as a function of distance to the plaque in APP/PS1 mice at 6, 9, and 12 months-of-age. The microglia are highly enriched in direct contact with the plaques.

Microglia Accumulate Directly on Plaques, while Astrocytes are Most Distant (continued)

In contrast, reactive astrocytes exhibited a more distal spatial distribution relative to amyloid plaques. Astrocytic density peaked within the 0–10 µm periplaque zone and remained elevated up to approximately 50 µm from the plaque boundary, indicating a broader response compared to activated microglia. Spatial distribution patterns were consistent across age groups; therefore, subsequent analyses were focused on the 9-month-old cohort as a representative stage of established pathology.

Heatmap showing the density of reactive astrocytes as a function of the distance to the plaque in the different age groups, showing that the astrocytes accumulate close to the plaques but are more distant than microglia

Density of reactive astrocytes as a function of the distance to the plaque in APP/PS1 mice at 6, 9, and 12 months-of-age.

Plaque Size as a Proxy for Plaque Age to Study Microenvironment Spatiotemporal Dynamics

To obtain a better understanding of the microenvironment spatiotemporal dynamics, we measured the plaque size and used it as a proxy for plaque age. The image shows plaques colored by size for visualization in a 12 month-old mouse: small plaques with an equivalent radius of less than 10 m, medium-sized plaques with an equivalent radius between 10 m and 20 m, and large plaques with an equivalent radius of more than 20 m. The equivalent radius of a plaque is defined as the radius of a plaque of the same area but perfectly circular. The histogram below shows the full distribution of plaque size across the different age groups.

Histogram of plaque size in the different age groups, showing a progressive increase in the number of plaques with age

Histogram of plaque size, in plaque equivalent radius, in the different age groups, showing an overall increase in the number of plaques over time.

Plaque Size as a Proxy for Plaque Age to Study Microenvironment Spatiotemporal Dynamics (continued)

We then quantified the glial cell density as a function of distance from the plaque and plaque size.

The heatmap below now shows the activated microglia density as a function of distance to the plaque and plaque size, or plaque equivalent radius. We can see that, once again, the microglia are highly enriched in direct contact with the plaques. The density rapidly increases in small plaques and plateau in medium-sized plaques.

Heatmap of activated microglia density as a function of the distance to the plaques and plaque size, showing that microglia can be found in small plaques and that the density plateaus in large plaques

Heatmap of the density of activated microglia as a function of the distance to the plaque (y-axis) and plaque size (x-axis, plaque equivalent radius) in 9 month-old APP/PS1 mice.

Now looking at the astrocytes, we see a very different dynamic. First, the reactive astrocytes are detected in slightly larger plaques than microglia. In addition, their numbers in contact with the plaque increase in the medium-sized plaques, but then decreased in the largest plaques.

Heatmap of reactive astrocytes density as a function of the distance to the plaques and plaque size, showing that microglia can be found in small plaques and that the density plateaus in large plaques

Heatmap of the density of reactive astrocytes as a function of the distance to the plaque (y-axis) and plaque size (x-axis, plaque equivalent radius) in 9 month-old APP/PS1 mice.

Microglia-to-Astrocyte Ratio as a Sensitive Metric of the Later Disease Stage

Because astrocytes and microglia have different behaviors in larger plaques, which are predominantly found in older groups, we hypothesized that a metric based on this phenomenon could help differentiate the 9 and 12 month-old groups.

We measured the ratio of microglia-to-astrocyte in the plaque proximity, and found that this ratio was higher in the 12 month-old group as compared to the other disease groups. In our study, this metric was the only one that showed a statistically significant difference between the 9 and 12 month-old groups.

While the other metrics, such as the amyloid- and GFAP stain density, generally trended higher in the 12 month-old group, none showed a statistically significant change between the two older groups.

Microglia-to-Astrocyte ratio in the vicinity of Amyloid plaques in ARTE10 mice across age

Ratio of microglia per astrocytes in the proximity of plaque (<10 μm from the plaque edge) in APP/PS1 mice at 6, 9, and 12 months-of-age. Data are presented as mean ± SEM. Statistical analyses were performed using Brown–Forsythe and Welch ANOVA, followed by Dunnett’s T3 multiple-comparisons test. * : p<0.05, ** : p<0.01, *** : p<0.001, **** : p<0.0001​.

This approach illustrates how quantifying astrocyte-microglia interactions can provide an informative metric of disease progression.

Summary

In conclusion, we have shown how our fully automated platform can quantify glial cell phenotypes and their spatial relationship to the plaque environment. Using this approach in the APP/PS1 mouse model of AD, we quantified different metrics, such as the activated microglia density, the astrocytes hypertrophy score, and the microglia-to-astrocyte ratio in the proximity of the plaque.

These complementary metrics demonstrated higher sensitivity than simple stain density measurements, revealing subtle spatial and morphological features of microglia and astrocytes that could be missed using standard approaches.

In a preclinical therapeutic efficacy study, this enhanced sensitivity would allow detection of smaller treatment effects without increasing cohort size. In addition, this comprehensive suite of metrics could be particularly insightful for evaluating therapeutics targeting microglial plaque engagement, microglia-astrocyte interactions, particular glial cell phenotypes, or other related mechanisms.

Please feel free to further explore the microscopy images in the viewer.

We would be happy to discuss this amyloid mouse model, its characterization, and our amyloid plaque microenvironment and neuroinflammation analyses if you would like to Contact Us.

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Image Interactive describing our amyloid plaque and neuroinflammatory microenvironment analysis, including high-resolution Multiplex Immunofluorescence brain tissue sections, from the APP/PS1 (ARTE10) mouse model and control mice.

Biospective's APP/PS1 Model Expertise and Services

Biospective is a global neuroscience CRO with extensive experience in Alzheimer's disease animal models.

Our team at Biospective has 15+ years of experience conducting studies in Alzheimer's disease models. As such, we have unique expertise in the best use of these mice in preclinical drug development. Some key advantages of partnering with Biospective for Alzheimer's disease model studies studies include:

  • Extensive Experience & Model Characterization: We have extensively characterized the APP/PS1 model through numerous studies. Our track record underscores our unique expertise with this AD model.

  • End-to-End Preclinical Services: Biospective provides integrated services from study design through execution and data analysis. Our capabilities include comprehensive in-life assessments (behavioral testing, motor function assays, etc.), neuroimaging (MRI, CT), bioanalysis (fluid biomarkers, IHC & multiplex immunofluorescence), and expert data interpretation. This one-stop approach ensures consistency and accelerates timelines.

  • Translational Biomarkers & Readouts: We incorporate translational endpoints that bridge preclinical findings to clinical outcomes. Our immunoassay capabilities include quantitative measures of neurofilament light chain (NfL), inflammatory cytokines, AB40/42, phosphorylated tau, and GFAP in mouse CSF, plasma, and brain homogenates. We also have core strengths in preclinical imaging, including in vivo MRI, PET/CT, and SPECT/CT for structural, functional, metabolic, and molecular imaging biomarkers. These readouts enhance the translatability of study results to human trials.

  • Global Collaboration & Flexibility: We are a global preclinical neuroscience CRO serving biotech and pharmaceutical clients internationally. Our scientists collaborate closely with sponsors to tailor studies to specific therapeutic mechanisms or targets. We can accommodate custom endpoints or novel treatment paradigms. We also offer flexibility in study design to meet your program’s needs. Importantly, we prioritize scientific rigor, reproducibility, and open communication throughout the partnership.

By leveraging our core strengths, we are able to efficiently generate pharma-grade data from this model for small proof-of-concept projects as well as large, later-stage preclinical development studies.

Contact us to learn more about our characterization of this APP/PS1 model, our validated measures, and our Alzheimer Disease Models CRO services.

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Tau Fibril Spreading Models (FTD & AD)

FAQs

At what age are β-amyloid plaques initially seen?

β-amyloid plaques are initially found in the frontal cortex at ~3 month-of-age in these transgenic APP mice.

What type of neuroinflammation is seen in the APP PS1 transgenic mouse model?

We observe a very interesting spatiotemporal pattern of microgliosis (including activated microglia) and astrogliosis in this model. We have performed a detailed analysis in this Alzheimer disease model, which can be found in our Presentation - Amyloid-β & the Inflammatory Microenvironment in an APP/PS1 Mouse Model of Alzheimer's Disease.

Is cerebral amyloid angiopathy (CAA) seen in the APP PS1 mice?

We see extensive β-amyloid vascular pathology in this Alzheimer disease transgenic mouse model. Amyloid staining can readily be observed in the leptomeningeal and deeper parenchymal blood vessels.

What promoter is used for transgene expression in the β-amyloid mice?

The mutant human APP and PSEN1 (PS1) transgenes are expressed under control of the Thy-1 promoter.

What areas of the brain show β-amyloid plaques in the β-amyloid transgenic mouse model?

Plaques are initially found in the frontal cortex and subiculum. As the mice age, there is a well-defined spatiotemporal pattern of β-amyloid pathology with extensive plaque burden in many brain regions, including the hippocampus and thalamus. We have performed a thorough characterization of these transgenic mice from 3 to 15 months-of-age.

Related Content

Up-to-date information on Alzheimer's Disease and best practices related to the evaluation of therapeutic agents in AD animal models.

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