Company: IMRX
Filing Date: 2025-03-20
Form Type: 10-K
Source: 0001790340-25-000042
Chunk: 46

Company: Immuneering Corp
Filing Date: 2025-03-20
Form: 10-K
Item: Item 1
Chunk 46
---
, our platform has previously been applied extensively in successful partnerships with large pharmaceutical and biotechnology companies, and through our internal drug discovery and development.

Insights from Human Data

Our analyses often begin by comparing existing transcriptomic data from two groups of patients (e.g., from those whose tumors have metastasized versus those whose tumors have not) to help elucidate the biological mechanisms underlying a particular aspect of disease which we seek to counteract. As another example, we may analyze existing data from patients with differences in response to an existing therapy, in order to better understand what is happening in responders versus non-responders. We may also analyze existing data from patients with a disease to identify novel subsets of patients. Our platform has enabled us to conduct multiple projects that involve stratifying patients into novel subsets. We associate transcriptomic profiles with each subset, which can then be directly inputted into DCT to identify novel targets specific to a given patient subset.

30

Novel Biology

Disease Cancelling Technology

We have developed DCT to identify targets that reverse a disease signal across multiple relevant genes with the potential to yield product candidates with differentiated mechanisms that are less likely to be discovered by traditional drug discovery methods. Additional biologic context is derived from quantifying the extent to which different time points, concentrations and perturbations (e.g., inhibition and overexpression) may cancel a disease signal more effectively than existing drug targets. DCT ranks target perturbations by the extent to which they generate signals that counteract disease-associated gene expression changes observed in patient data. Thus, we believe DCT enables hypothesis-free, data-driven identification of novel targets and new ways to drug existing targets.

DCT leverages gene expression data derived from human patient samples to identify targets that may rescue abnormal gene expression and restore pathway homeostasis. In addition, DCT identifies biology relevant to attenuating a disease by quantifying the similarity of genome-wide signatures of specific aspects of the disease to signatures of target induced gene expression changes using a mathematical similarity metric. Uniquely, DCT quantifies the per-gene contribution to overall disease amplification or cancellation. An example of a typical analysis begins by running DCT to identify an unwanted, disease-specific gene expression pattern. The ideal input to DCT is focused on a specific aspect of a disease, such as tumors that have metastasized versus those that have not, rather than comparing diseased versus healthy states. DCT identifies target candidates by screening a disease differential expression signature and comparing it to thousands of target gene expression signatures.