myNEO focuses on research, development, and optimisation of the clinical exploitability of personalised cancer immunotherapy.
It is myNEO’s mission to enable improved neoantigen-directed immunotherapy by integrating three important pillars of successful therapy. myNEO’s primary focus is to tackle the challenge of identifying, in a quick but accurate way, the neoantigen targets that determine the success of each immunotherapy. These – often personalised – neoantigens are obtained by interpreting tumour samples with data-driven neural networks trained on gathered biological datasets. But personalisation can be pushed even further, by immune typing of the tumour micro-environment to ensure that the best (combination) therapy is selected. Lastly, myNEO enables efficient monitoring of treatment response and disease progression using personalised biomarkers.
The primary therapeutic focus of our patient-specific tumour screening platform is personalised immunotherapy through neoantigen prediction. A validated set of tumour-specific surface molecules is chosen and validated per patient. Via various cell-based and vaccination strategies, the patient’s own immune system is redirected against these chosen neoantigens. The software module is firmly integrated with experimental and clinical validation.
By performing the personalised analysis on a cohort of different samples, targets that are detected in a multitude of samples (‘shared immunogenic target discovery’) are used for off-the-shelf therapeutics. Big data analytics are used to identify alterations frequently shared amid patients and to explore other inter-patient associations.
myNEO Treatment Advisor
The tumour fingerprint is used to analyse specific mutations in genes or gene regions that have known or suspected associations with the prognosis of the patient, and to decide upon the optimal treatment plan. New (diagnostic) markers to improve therapy efficacy predictions and distinguish responders from non-responders in clinical trials are also actively sought after.
We really appreciate the way the myNEO team involves the eTheRNA team during the conduct of the project. The very clear and concise reporting of myNEO was extremely helpful to make the right decisions. Thanks to the myNEO team for the good collaboration!
myNEO is a top partner for a project where academia and biotech reinforce one another. Though the teams never met ‘’in person’’, the collaboration was immediately, pleasant, constructive, and successful. We look forward to a long and productive collaboration.
It’s a real pleasure to collaborate with myNEO; innovative and solid science delivered by a creative and dynamic team!
The team of myNEO greatly helped us to screen for potentially damaging forms of variation that appeared in cells. The analysis and its results were trustworthy, due to its transparency, extensiveness, and the high quality standards
The myNEO technology platform focuses on identifying, exploring and validating unusual alterations and their immunogenic impact. In a personalised manner, the sequencing data of tumour cells (biopsy) and healthy cells (blood) are compared, and tumour-specific alterations leading to peptides present on the tumour surface are annotated. Since these antigens are absent from healthy cells, they can have important immunogenic implications, and are fit for use in therapeutic or prognostic applications. The bioinformatic platform is incorporated in a comprehensive end-to-end flow ranging from sample processing to vaccine construct design.
Prioritising on continuous improvement of the neoantigen prediction pipeline, by incorporating new algorithms based on in-house research and our academic/industrial collaborations. Both private and public validated antigen sets are used to train, test, and optimise the prediction platform.
Discovering a broad set of neoantigens to enable identification of valuable targets in cold tumours where other immunotherapies are not working adequately. Proprietary algorithms combined with enhanced patient datasets allow for detection of novel antigen types caused by unusual tumour alterations. Both the MHC-I and MHC-II epitopes arising from these tumour-mutational processes are deemed more valuable as targets.
Lowering the number of falsely identified neoantigens. Important screening steps take place to validate the results of the bioinformatics platform. These involve tandem mass spectrometry analysis of the HLA ligandome and various immunogenicity assays. To cope with the limitation of large biopsy sample requirements for mass spec analysis, a cross-patient employable deep-learning algorithm predicts which antigens are most likely to be presented on the patient tumour cells.
Assisting partners in designing the optimal vaccination construct containing the selected targets. Multi-epitope constructs containing a carefully selected combination of MHC-I and MHC-II presented epitopes ensure induction of an enhanced immune response against the tumour antigens.
Integrating the platform in an end-to-end solution for clinical use, including sample fixation and preparation, state-of-the-art sequencing, tumour microenvironment screening, and immunogenicity testing. Key to the development of the myNEO sample flow has been the condition of clinical-grade platform use, allowing the personalised therapy to reach the patient in time and in a cost-effective manner.
Setting up clinical and research collaborations due to our strong belief in the phrase ‘together we achieve more’. We acknowledge that identifying the correct target in a patient sample is only part of the end puzzle, and there are several other critical success factors when developing therapeutic cancer vaccines.
Monday 3 January 2022
myNEO will attend job fairs and participate in the following events this year provided that the Covid-19 regulations will allow for these events to t…
Wednesday 23 November 2022
myNEO is xtremely excited to announce the publication in the Cancer Cell journal, written by myNEO colleagues Lien, Steve, and Bruno together with ke…
Monday 14 November 2022
myNEO has won Deloitte's 2022 Most Disruptive Innovator award. This award, which is part of the Rising Star category of the Deloitte Technology Fast …