PO.EN01.02 · 内分泌肿瘤

Preclinical mechanistic PK/PD/Efficacy modeling for AZD4241, a novel oral estrogen receptor (ER) degrader (PROTAC), to support dose selection during early clinical development

编号 5019 展板 13 时间 4/21 09:00–12:00 区域 Section 33 主讲 Ana Quiroga, B Eng;M Eng;PhD
分会场 Signaling Pathways, Metabolism, and Emerging Therapeutic Targets
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作者与单位

Ana Quiroga, Pablo Morentin Gutierrez, Lynet Nyoni, Natalie Cureton, Mandy Lawson, Aaron Smith, Thomas Hayhow, Neil Gibson

AstraZeneca, Cambridge, United Kingdom

摘要 Abstract

The high prevalence of ER‑positive breast cancer and the emergence of resistance to current endocrine therapies highlight the need for more effective ER degraders. AZD4241 is a novel, potent, orally bioavailable, and selective ER proteolysis‑targeting chimera (PROTAC) scheduled to enter clinical evaluation in 2026. We describe preclinical pharmacokinetic/pharmacodynamic (PK/PD) and efficacy modeling that quantifies the relationships among drug exposure, ERalpha degradation, and antitumor activity, thereby defining the extent of compound plasma exposure and target modulation required to achieve efficacy. These translational analyses are intended to inform dose selection and guide early clinical development of AZD4241.We developed a mechanistic mathematical model to quantify the exposure-target-response profile of AZD4241 in in-vivo patient‑derived xenograft (PDX) models harboring either wild-type or mutated ESR1. The PK module characterized plasma concentrations across a range of doses. An indirect‑response PK/PD module incorporated AZD4241 mechanism of action, whereby the compound accelerates ERalpha degradation yielding reductions in total ER protein measured by Western blot. The integrated PK/PD/Efficacy model linked plasma exposure, ERalpha levels, and tumor growth kinetics in the PDX models. Model parameters were estimated via nonlinear mixed‑effects (NLME) modeling using individual longitudinal PK, PD biomarker, and tumor volume data aggregated across multiple studies. The mathematical model captured the dose-dependent reduction of ERalpha and the associated inhibition of tumor growth observed in the PDX models. The level of ER degradation required to induce tumor regressions on the PDX models was also quantified and will be presented. This work provides quantitative, mechanistic insight into how exposure drives biomarker modulation and antitumor responses, delineating the level of ERalpha degradation required for robust efficacy in endocrine‑sensitive PDX models. The framework supports interpretation of compound‑induced PD effects in patients under defined dosing regimens and supplies translational evidence to enable dose selection in early clinical development.
利益披露 Disclosure
A. Quiroga, AstraZeneca Employment, Stock, Stock Option. P. Morentin Gutierrez, AstraZeneca Employment, Stock, Stock Option. L. Nyoni, AstraZeneca Employment, Stock, Stock Option. N. Cureton, AstraZeneca Employment, Stock, Stock Option. M. Lawson, AstraZeneca Employment, Stock, Stock Option. A. Smith, AstraZeneca Employment, Stock, Stock Option. T. Hayhow, AstraZeneca Employment, Stock, Stock Option. N. Gibson, AstraZeneca Employment, Stock, Stock Option.

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