Pharmaceutical R&D

We are actively building Nexus workflows for all key pharmaceutical applications of MSI technology. Moreover, these workflows can be customized to dovetail perfectly with your analytical protocols, including various technology combinations. Our solutions are built to scale to massive throughput and petabytes of data storage, while adhering to your corporate security measures.
All of these workflows inherit our platform's fundamental features:

Bespoke bioinformatics

We provide fit-for-purpose tools and workflows for common pharmaceutical studies involving MS imaging, including quantitation and untargeted analyses. Moreover, we are focusing on multimodal analysis, enabling you to leverage other imaging technologies as well as LC-MS.


Construct calibration curves based on various types of analytical data, including dilution series and mimetic models. Automatically assess expected statistical properties of your calibration curves, e.g., linearity, goodness-of-fit or metrics of your choosing. Easily perform statistical comparisons within and between groups of samples after quantitation.

Differential expression analysis

Uncover meaningful differences in endogenous molecules between groups of samples (e.g., treated vs. control). Our differential expression workflows enable efficient anatomical stratification prior to statistical analysis to remove the confounding effects of tissue composition.

Multimodal analysis

Our tools aim to support the joint analysis of MSI with other imaging data, such as microscopy (fully supported), Raman spectroscopy and spatial transcriptomics, as well as staple methods like LC-MS.

Boost Your Operational Efficiency

Maintaining high throughput while delivering best-in-class results is a key aspect of running high quality labs. Our dedicated data workflows provide a digital backbone to distribute and track tasks among your team members, while also providing built-in, data-driven QC for your analyses.


Leverage workflows that capture all necessary actions within an analysis, along with who can perform them, to efficiently distribute and track tasks. Problems can be signalled via notifications.

Personalized dashboards

Each member of your team has access to personalized dashboards that enable them to identify actionable tasks based on their expertise and responsibilities.

Built-in, data-driven QC

The Nexus platform provides built-in, data-driven QC for key steps in your workflows to enable you to automatically detect an array of potential issues, thereby enhancing your overall quality.
Maximum efficiency

Turnkey IT solutions

The Nexus platform is a turnkey solution covering the digital lifecycle of your experimental data and its associated metadata, as well as analysis procedures up to holistic reports. Nexus provides a scalable system with virtually unlimited data storage and on-demand computational capacity capable of terabyte-scale analyses. Focus on your core business while we handle the IT concerns.
IT infrastructure

Scalable by design

Our platform is backed by high performance cloud computing infrastructure, allowing seamless scaling to petabytes of data storage and analyses covering terabytes of data, without complex configurations on your behalf.

Best-in-class security

All data stored within the Nexus platform is secured according to current best practices. Our security system is regularly audited and updated by experts to keep your confidential data safe from accidental deletion or unauthorized access.

Integration options

Nexus supports deep integration with third party systems you may be using, such as databases, object stores, etc. Conversely, data and metadata can be queried from our platform via dedicated API's.

Joint research with Aspect Analytics

As a KU Leuven University spin-off, Aspect Analytics has strong scientific roots, as evidenced by our scientific publications. We remain active in cutting-edge research, with our core expertise encompassing bioinformatics, machine learning and mass spectrometry.


We have broad experience analysing biological data, with a primary focus on mass spectrometry imaging and microscopy data analysis. We are currently actively researching techniques for true multimodal data fusion across various imaging and non-imaging modalities.

Machine Learning

Our machine learning expertise includes deep learning, hyperparameter optimization, building and evaluating predictive models in an unsupervised context, as well as Bayesian inference.

Mass spectrometry

We have a long-standing research history in mass spectrometry imaging, including a recently published review paper together with prof. Caprioli. In addition to MSI, we are increasingly involved in analysis of complex LC-MS data.
Two scientists doing joint research