Our mission is to raise the survival curve for the hardest to treat solid tumors.

Single-cell data from human tissues is providing unprecedented detail into target expression and selectivity.

Our platform interrogates single-cell RNA data at scale and is currently focused on solid tumors.

Understanding the biology of tumors as whole systems unlocks powerful new therapeutic approaches.

Despite recent advances, outcomes for most solid tumor patients remain poor (e.g., colorectal, pancreatic, breast cancers). We believe the reason why drugs for these cancers have not translated well in the clinic historically is that they were largely discovered and studied in models that do not account for the diversity of cell types present in human tumors. To address this challenge, we have built an ML-powered transcriptomics platform that allows us to understand the interactions of all the cell types in these tumors to identify compelling targets and a system to test our drugs in human tumor explants thus delivering translational insights during our discovery process.

Our lead program is a CD3 engager that uses a novel targeting approach identified by our platform that should be able to overcome limitations of traditional tumor-associated antigens. This program is generating compelling results in challenging cancers and is now at a development candidate stage demonstrating Phenomic’s ability to identify novel high-impact, druggable targets.

At Phenomic, we are pioneers in using advanced machine learning tools for processing imaging, RNA sequencing, and spatial transcriptomics data to understand the biology of single cells sitting in complex multi-cell systems.

Our platform allows us to explore cell type and target expression profiles in exquisite detail, both in human cancer and normal tissue samples, as well as disease relevant experimental systems (e.g., human tumor explants, animal models).