Abstract

Target engagement is not always a direct indicator of the degree of checkpoint inhibition, an important consideration for checkpoint inhibitor dose projections. Here we show how the special structure of the Applied BioMath Assess Membrane Ligand Competitor model in Applied BioMath Assess is well-suited for modeling checkpoint inhibitors and explaining this phenomenon with a focus on two immune checkpoint inhibitors, atezolizumab and magrolimab. 

This case study highlights the ways in which Applied BioMath Assess™ can be used for early feasibility assessment to predict the PK and pharmacology of a hypothetical monoclonal antibody. It explores a situation in which early feasibility assessment supports decision making and describes how insights can drive alignment during drug discovery.

Human epidermal growth factor receptor 2, or HER2, is a protein overexpressed in some types of cancer. Trastuzumab is a monoclonal antibody that inhibits HER2 signaling by binding to the extracellular domain of HER2 and blocking dimerization with its binding partners.

This case study demonstrates how to use Applied BioMath Assess™ to make early human dose predictions of a HER2 targeting antibody such as Trastuzumab.