Abstract 4369: Preclinical mechanistic PK/PD-efficacy modeling for AZD9833, a novel next generation oral SERD, to support dose selection during early clinical development
Authors: Pablo Morentin Gutierrez, Christopher Morrow, Natalie Cureton, Mandy Lawson, Dawn Trueman, Eric Gangl, Joanne Wilson, Aaron Smith, James Scott, Teresa Klinowska
Journal: Cancer Research (2020)

Abstract Objectives: The estrogen receptor alpha (ERα) is highly expressed in breast cancers and is a clinically validated target in oncology. AZD9833 is a novel potent oral selective estrogen receptor degrader (SERD) currently being tested in the clinic [SERENA-1 (NCT03616587)]. We present here the preclinical PK/PD modeling work used to understand the required target modulation and concentration required to see anti-tumor efficacy and therefore help support the dose selection during the early clinical development of AZD9833. Methods: We developed a novel mechanistic mathematical model applied to mouse in both a xenograft ESR1 wild-type (MCF-7) and a PDX model harboring an ESR1 D538G mutation (CTC-174) linking the compound pharmacokinetics with the magnitude of target modulation expressed as relative levels of estrogen (ER) or progesterone receptor (PR) both measured by Western Blotting. These changes at the biomarker level were subsequently linked to inhibition of tumor cell proliferation, via a Hill-Langmuir relationship resulting in macroscopic dynamic effects on tumor size. All model parameters were derived from internal studies; some were estimated using Non-Linear Mixed Effect modeling of individual longitudinal PK, PD biomarker and tumor size data taken from several studies. Results: The model described well the relationship between plasma concentration of AZD9833 and modulation of PR (MCF-7) and ER (CTC-174). In vivo AZD9833 concentration required to see 50% of the maximal target modulation in both animal models (1.6 and 0.4 nM respectively) was in very good agreement with in vitro values when accounting for the different levels of estradiol in both animal models. Population tumor size patterns, for all treatment regimens ranging from 0 to 100% Tumor Growth Inhibition (TGI) across both tumor models were very well described with the model proposed. 75% reduction of ER levels and 45% reduction of PR levels were required to slow the tumor growth rate by one half in the CTC-174 and MCF-7 models respectively. This quantitative relationship was further validated with another SERD (Fulvestrant) in both animal models. Conclusions: This study provides quantitative mechanistic insights into the links between key biomarker modulation (ER and PR) and anti-tumor responses, supporting our understanding of the required high target modulation needed (&amp;gt;70% modulation of PR in MCF-7 and &amp;gt;85% modulation of ER in CTC-174) for maximal anti-tumor effects in these two animal tumor models. This basic mechanistic understanding is valuable to contextualize compound-induced PD modulation in patients, for given doses and schedules and helps to support dose selection decisions. Citation Format: Pablo Morentin Gutierrez, Christopher Morrow, Natalie Cureton, Mandy Lawson, Dawn Trueman, Eric Gangl, Joanne Wilson, Aaron Smith, James Scott, Teresa Klinowska. Preclinical mechanistic PK/PD-efficacy modeling for AZD9833, a novel next generation oral SERD, to support dose selection during early clinical development [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4369.