ImmuneWatch DETECT
TCR specificity annotations for comprehensive T-cell response analysis.
Struggling with finding the epitope-specificity of your T-cell receptors?
ImmuneWatch’s DETECT platform uses machine learning to annotate the epitope specificity of T-cell receptor (TCR) sequences.
Together with ImmuneWatch we were able to assess vaccine-induced T-cell signatures in our unique longitudinal sample collection of cancer patients. Based on antibody titers, it has previously been shown that cancer patients induce a weaker response towards COVID19 vaccines. T-cell immunity in this context is far less characterized and understood. Thanks to the ImmuneWatch DETECT platform we were able to take a deep dive into the SARS-CoV-2-specific T-cell response of our cancer patient cohort.
ImmuneWatch assisted us in analysing reactive T-cells through TCR sequencing and data anaysis in an oncology setting. Together, we identified potential TCR candidates for further in vitro validation. This collaboration provided us with insights into T-cell reactivity and the immune profile of our stimulation experiments, advancing our understanding and guiding future research.
The DESIGN analysis performed by ImmuneWatch is very informative and useful for making decisions on our different candidate antigens. Thank you for this nice work!
ImmuneWatch DETECT wins Machine Learning competition
We are excited to share our recent win in the IMMREP23 Kaggle competition focused on TCR (T-cell receptor) specificity prediction.
Read the articleWhitepapers
TCR sequencing for cancer vaccine development
To know the efficacy of your cancer vaccine, it is crucial to analyse the T cell response. Because of its versatility, TCR sequencing is a rising tool to monitor such immune responses. However, the full potential of TCR sequencing remains unrealised at present.
This white paper is directed toward researchers and developers of therapeutic cancer vaccines. It offers a brief overview of TCR sequencing and how it has been applied in the field of therapeutic cancer vaccination. Additionally, we highlight common challenges encountered in the data analysis and present examples of how these can be overcome with state-of-the-art data analysis techniques.
Using machine learning to monitor T-cell responses in an oncology case
This poster showcased how ImmuneWatch DETECT is used for T-cell monitoring in cancer vaccine research, featuring a case study of a stage IV colorectal cancer patient. Using advanced machine learning algorithms and an extensive epitope-TCR database, we demonstrated our technology's ability to identify TCRs recognising tumour- and vaccine-associated antigens, advancing monitoring in precision medicine.
The poster was presented at the Immuno-Oncology Europe summit in London (2024).
Our offering
Find the epitope-specificity of your TCRs today
ImmuneWatch DETECT
Best-in-class TCR-epitope prediction algorithm
Support through a community forum
Deployment through Docker
Run on 1 device
Unlimited number of samples
ImmuneWatch DETECT Premium
academic researchers, students and non-profit institutes
Best-in-class TCR-epitope prediction algorithm
Access to IMWdb for improved accuracy of annotations
Explainability of TCR-epitope predictions
Email support within 5 business days
Installation support
Deployment through Docker, Podman or Singularity
Run on 1 device
Unlimited number of samples
ImmuneWatch DETECT Premium
Best-in-class TCR-epitope prediction algorithm
Access to IMWdb for improved accuracy of annotations
Explainability of TCR-epitope predictions
Email support within 3 business days
Deployment through Docker, Podman or Singularity
Installation support
Run on 5 devices
6h of immunoinformatic consulting/year included
ImmuneWatch DETECT Service
In-depth data analysis by immunoinformatic experts
Detect pathogen-, vaccine-, therapy-specific TCRs with our best-in-class TCR-epitope prediction algorithm
Possibility to generate data for your epitopes of interest
Our offering
Make your vaccine design process more data-driven by implementing machine learning and approaches from reverse vaccinology.