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The NTKApp


The NTKApp is a powerful, cloud based, fully integrated analytics platform. It improves the process and ability to interpret neurologically relevant immunoassay data while providing users a unified, cloud-based platform. The NTKApp consists of three interlinked apps. This allows users to upload, curate, analyze, and compare biomarker datasets and results from all over the world in a few simple clicks. Thanks to the NTKApp built-in virtual machine, users can import, shape, and run their own statistical analysis pipeline that can later be shared with the NTK community. The NTKApp is a new tool to exchange ideas, encourage valuable research, and support industry partnerships.



NTKCuration App

The NTKCuration App module offers user-friendly data upload. Biomarker data needs quality control and standardization before being used in the NTKAnalysis App. This automated data standardization process minimizes human error and allows comparability across datasets.

NTKAnalysis App

The NTKAnalysis App allows users to select a suite of powerful descriptive statistics to gain immediate insight into data. Outputs are available in publication-quality tables and interpretable graphical visualizations, which can be saved locally.

 NTKMeta-Analysis App

The NTKMeta-Analysis App allows users to compare biomarker data with other data across the community. The NTKMeta-Analysis App also sheds light on shared data, resources, and objectives, providing support for existing and new clinical use cases based on collective evidence. This enables the contextualization of results and the generation of new hypotheses and evidence.


Collaborative research in neurology is evolving. The NTK is an effort to generate high quality, reproducible, and comparable biomarker data. While NTK is all about community and collaboration, we understand the importance of data privacy. The NTK FAIRuser policy lets you decide what to share, when to share it, and with whom.


Five-part framework

Collaborative research will be instrumental in generating evidence to clarify the use of biomarkers in clinical trials and routine clinical practice. This should result in accelerated development of biomarkers for in vitro diagnostic tests that support clinical screening, diagnosis, and prognosis, pharmacodynamic responses tracking, and drug efficacy monitoring.

  1. Detects or confirms the presence of Alzheimer’s disease pathology (amyloid/tau/neurodegeneration framework)
  2. Predicts the likely course of disease in untreated individuals and identifies patients who are likely to have a faster rate of decline.
  3. Indicates that a biological response has occurred and changes in biomarker values often precede clinical outcome.
  4. Distinguishes between those who will respond or not respond to therapy.
  5. Surfaces subsets of response biomarkers that predict specific disease related clinical outcome and can serve as a surrogate for a clinical efficacy endpoint.


Data Standardization

Data uniformity and harmonization across studies is essential when analyzing and comparing research data and results.. The NTKCuration App simplifies the data standardization process by offering a user-friendly app providing an infrastructure aimed at facilitating data harmonization across studies in a transparent and time efficient way.

Analysis and Reporting

Creating detailed reports that describe statistical analyses and results can be a tedious process for researchers, as they often must use multiple tools to analyze, visualize and explain their research. The NTKAnalysis App helps generate scientific reports in one fully editable statistical analysis document by shifting the focus from analysis preparation to results interpretation. The NTKAnalsys App offers a suite of analysis modules that allow descriptive insights into data, inferential statistics and interactive graphical representations.


The interpretability of of meta-analysis results increases with the amount of available data. Building a global research community is imperative to gain knowledge of neurodegenerative diseases. The key to the success is to share results in a safe and standardized way. The NTKMeta-Analysis App offers a shared approach to research, where users can compare results in a few simple clicks, while protecting the ownership of their data.
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Roche Nagarro Aridhia