This presentation is being submitted as one piece of a larger, two-hour symposium that would be chaired by John M. Burke, PhD, Co-Founder, President and CEO, Applied BioMath. Harnessing the immune system has revolutionized how cancer is treated. In particular, redirected T-cells can kill tumor cells in therapeutically useful ways (BiTE®, CAR-T, engineered TCR). However, off-target and on-target, off-tumor toxicities have limited the therapeutic index of these approaches. Thus, expanding the antigenic targeting space to increase tumor specificity and constrain immune-activation to the cancer cell surface should widen the therapeutic index of these approaches and allow more efficacious dosing regimens.
At Revitope we are developing two-component systems composed of conditionally activated T cell Engaging Antibody Circuits (TEAC) that initiate and focus cytotoxic immunity accurately on the tumor. Component 1 in the kit is a bispecific Ab composed of a tumor associated antigen binding domain fused to a CD3 half-paratope that is connected to a stabilizing “dummy” domain via a protease cleavable linker. Component 2 is a bispecific Ab composed of a different tumor associated antigen binding domain fused to the complementing, dummy-stabilized CD3 half-paratope. Thus, tumor specificity is enhanced by the Ag1 and Ag2 logic gate and T cell engagement and activation is gated by proteolytic activation and complementation of the full CD3 paratope only in the tumor microenvironment.
The discussion will cover protein engineering considerations and in vitro as well as in vivo activity. In addition we will discuss how quantitative systems pharmacology modeling approaches aid mechanistic understanding.
Upon completion, participants will be able to understand how quantitative systems pharmacology (QSP) modeling approaches aid mechanistic understanding for a bispecific therapeutic in oncology.
Upon completion, participants will see how a QSP model helped assess therapeutic potential of a therapeutic with limitations such as off-target toxicity, on-target/off-tumor toxicities and lack of sufficient antigen.
Upon completion, participants will learn how QSP modeling aids the protein engineering of a conditionally active bispecific.