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Immuneering has spent >10 years discovering actionable insights via cellular signaling dynamics, translational bioinformatics, computational biology and artificial intelligence (AI) combined with deep scientific expertise. Our platform is validated by more than a decade of experience partnering with leading pharmaceutical companies (e.g., Janssen, Alexion, UCB, Rhythm, Teva, BMS and Biogen) helping them to characterize drug mechanisms, identify targets, pinpoint biomarkers and more.

Case Studies

In partnership with Bristol-Myers Squibb, Immuneering helped BMS understand why only a certain group of patients with melanoma were responding to YERVOY. We detected gene expression in a subset of immune cells and were able to show that patients with that gene had an increased survival benefit. This work resulted in a new patent application (WO2014078468).

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In published work together with Janssen, Immuneering helped identify why subgroups of multiple myeloma (MM) patients treated with DARZALEX had different response profiles through discovering differential expression of T-cell co-stimulation proteins in better responding patients. This work resulted in several published abstracts and presentations at the American Society of Hematology.

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In partnership with Teva, Immuneering applied transcriptomics to characterize COPAXONE’s mechanism of action and compare it to potential generics, helping to ensure patient safety by providing new ways to more fully assess the biological impact of potential generics. This work resulted in several peer-reviewed publications.

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Disease Cancelling Technology

The Disease Cancelling Technology aspect of our platform is based on the notion that engineering medicines to reverse a disease signal across multiple relevant genes will yield drug candidates with a higher likelihood of success compared to traditional drug discovery methods.

The biology side of our platform (Cosiner) enables hypothesis-free, data-driven target identification. This platform uses gene expression from highly curated human patient datasets, not targets identified in the literature. Cosiner not only produces new targets and more sophisticated ways to drug existing targets, but also specific in vivo/in vitro testable genes, relevant concentrations and timepoint information driving the result.

Fluency screens small molecule compound libraries for hits against identified targets generating binding affinity rankings at near experimental level precision. This platform provides mechanistic insights into regions of the protein being bound and can rank the binding for 20 million compounds to a protein in just a day.

These platforms are not limited to a single aspect or pathology, rather they are disease-agnostic, which enables them to help engineer drug candidates for countless disorders. Immuneering’s platform has the potential to deliver more value to the healthcare system than traditional drug discovery and development.