The recent FDA approval of two more antibody drug conjugates (ADCs) highlights the clinical success and growth in this class of agents. Despite these approvals, however, the attrition rate for new ADCs remains high, and in oncology applications, no ADC for solid tumors has yet been able to repeat the success of ado- trastuzumab emtansine (T-DM1). A substantial effort has been exerted to improve the antibody and target selection, conjugation site, linker stability, and payload properties (potency, bystander effects, etc.), and these improvements will benefit the next generation of compounds. However, fundamental questions remain on how to design a clinically effective agent. Specifically, the relative contribution and interaction between the multiple mechanisms of action of these drugs (receptor signaling blockade, payload efficacy, and Fc effector functions) remains unknown. The long-term goal is to understand the fundamental properties of these complex drugs in sufficient detail to rationally combine the antibody, linker, and payload with a particular target (in a select patient population) for maximum clinical efficacy in both cancer and non-oncologic applications. The goal for this proposal is to quantitatively understand the relative contribution of direct payload effects in antigen positive cells, bystander payload effects in antigen negative cells, and the role of Fc-effector functions in determining efficacy with antibody drug conjugates. Using a combination of near-infrared fluorescence imaging and flow cytometry, the absolute number of intact and degraded (triggering payload release) ADCs per cell can be determined. By pairing these results with pharmacodynamic markers (e.g. DNA damage markers of alkylating agents), the delivery and efficacy of the ADC (both direct and bystander killing) can be quantified with single cell resolution in vivo. Co-administration of varying ratios of ADC with unconjugated antibody will be used to control the tissue distribution to vary direct versus indirect killing. The studies will be conducted in both an immunocompromised and immunocompetent (syngeneic) mouse model to determine the benefit (or requirement) for immune system activation. By comparing the single-cell measurements with the gold standard of preclinical efficacy (tumor growth curves), the relative contribution of each mechanism will be determined. The outcome of the work will enable the rational design of novel ADCs rather than testing the myriad combinations in vivo by focusing development on a) selection of targets with more uniform expression and ADC internalization if direct targeting predominates, b) optimal physicochemical properties and distribution of bystander payloads if bystander effects plays a major role, or c) activation and recruitment of immune cells through co-therapy, Fc engineering, and/or dosing regimens if immune cell recruitment is necessary. A significant number of monoclonal antibodies that failed as monotherapies are sitting dormant within pharmaceutical companies. By leveraging advances in payload and linker chemistry with the knowledge from this proposal, development of new clinically successful ADCs can be rapidly accelerated.

Public Health Relevance

This research uses a systems pharmacology approach to understand the complex distribution and metabolism of antibodies and their small molecule payloads from the whole organism to single-cell level. By combining high-resolution molecular imaging approaches to quantify distribution with computational simulations of drug transport, more effective antibody drug conjugates can be rationally designed for cancer therapy and newer non-oncological disease applications.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
5R35GM128819-03
Application #
9989622
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Garcia, Martha
Project Start
2018-08-01
Project End
2023-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109