Our client, a therapeutics company, has a novel drug candidate showing promise in both in vitro and in vivo studies. However, the drug’s mechanism of action was not well understood, leading to uncertainty and risk for future clinical trials. Our client conducted a functional proteomics assay (RPPA) on diseased, healthy, and tissues treated with their drug candidate. They needed a data science-driven analysis of the RPPA data to identify the genes, proteins, and pathways involved in both the diseased and treated state.
The client sourced RPPA, an antibody based assay, from an academic core facility with highly validated antibodies. Our team used data science techniques to find clusters of proteins up or down-regulated in the disease state and in the treated state relative to healthy states. We mapped patterns of protein levels to pathways to infer mechanism of action of treatment. We confirmed hypotheses to guide the next phase of drug development. This work holds additional promise for developing a clinical assay to determine therapeutic response during trials.