Abstract 365: Using radionuclear imaging and mechanistic modeling to assess the therapeutic potential of antibody-drug conjugates (ADCs)
Authors: Teng Shu-Wen , Yardibi Ozlem , Zhang Julie , Cvet Donna , Yang Johnny , Orcutt Kelly , Gallery Melissa , Chakravarty Arijit , Shyu Wen Chyi , Mettetal Jerome , Bradley Daniel , Veiby Petter 
Published: May 2015

Antibody-drug conjugates (ADCs) comprise a drug class that allows for direct delivery of a cytotoxic agent to the target tumor cell. The successful development of an ADC involves the assessment of patient characteristics such as tumor antigen expression and tumor vascularity. There is a need to develop a mechanistic understanding of the effect these tumor parameters have on ADC biological activity. This mechanistic insight can be derived from a mathematical model integrating quantitative preclinical data, and will support ADC development.

MLN0264 is an investigational ADC consisting of a human anti-guanylyl cyclase C (GCC) antibody linked to the microtubule-disrupting agent monomethyl auristatin (MMAE). Here, we use mathematical modeling, in conjunction with in vivo imaging, to decouple the contribution of different tumor parameters to overall ADC biological activity. We constructed a mathematical model of ADC biological activity by integrating experimental results from (1) in vivo antibody imaging studies, (2) in vitro viability assays, and (3) in vivo xenograft biological activity studies.

First, blood pharmacokinetics and tumor disposition were quantitatively constrained using in vivo radiolabeled antibody single-photon emission computed tomography (SPECT) data for both blood and tumor tissues. SPECT data from three xenografts with various antigen expression levels were used to link antigen expression level to ADC uptake. Second, the relationship between bound GCC receptor concentration and cell viability was established using viability assays run on an engineered cell line (293-GCC) with high antigen expression and high sensitivity to MMAE. Finally, using this relationship, we built a tumor growth dynamics model to describe in vivo xenograft biological activity, and to estimate the growth inhibition coefficient of 293-GCC.

This mechanistic model can be used to gain insights into the factors driving response of a tumor that is intrinsically sensitive to MMAE. Our results indicate the process of ADC vascular permeability is one of the limiting factors of ADC disposition. This outcome is reasonable given that a large ADC molecular weight decreases the permeability. Furthermore, the model simulations suggest some tumors that are intrinsically sensitive to MMAE may not be affected by the ADC if GCC antigen expression levels are very low.

Taken together, the mechanistic model developed here forms the basis of a quantitative understanding for several factors influencing MLN0264 patient selection.

Citation Format: Shu-Wen Teng, Ozlem Yardibi, Julie Zhang, Donna Cvet, Johnny Yang, Kelly Orcutt, Melissa Gallery, Arijit Chakravarty, Wen Chyi Shyu, Jerome Mettetal, Daniel Bradley, Petter Veiby. Using radionuclear imaging and mechanistic modeling to assess the therapeutic potential of antibody-drug conjugates (ADCs). [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 365. doi:10.1158/1538-7445.AM2014-365