Application of mechanistic preclinical PK/PD/efficacy modeling to support combination strategy for AZD9750, a novel oral androgen receptor degrader (PROTAC)
Presenter: Ana Quiroga, B Eng;M Eng;PhD Session: Proximity-Induced Drug Discovery 1 Time: 4/21/2026 9:00:00 AM → 4/21/2026 12:00:00 PM
Authors
Ana Quiroga 1 , Pablo Morentin Gutierrez 1 , Antonio Ramos-Montoya 1 , Chrysiis Michaloglou 1 , Nuria Galeano-Dalmau 1 , Claire Crafter 1 , Aaron Smith 1 , Jamie Scott 1 , Michael Niedbala 2 1 AstraZeneca, Cambridge, United Kingdom, 2 AstraZeneca, Waltham, MA
Abstract
The androgen receptor (AR) is highly expressed in prostate cancers and is a clinically validated target in oncology. AZD9750 is a novel potent oral selective AR Proteolysis-targeting chimera (PROTAC) with a suitable pharmacological profile to be used in combination with a variety of other therapeutics such as capivasertib, a potent pan-AKT kinase inhibitor with anti-tumor activity in tumors with PIK3CA and PTEN mutations, and saruparib, a PARP1-selective inhibitor especially effective against tumors with mutations in genes like BRCA1 and BRCA2. We present here the preclinical PK/PD/Efficacy modeling work used to understand the anti-tumor mechanism of AZD9750 in combination with AKT and PARP inhibitors. We developed a novel mechanistic mathematical model applied to in vivo preclinical hormone sensitive, ARwt prostate PDX models C901 and MR041. C901 has homologous deletion of BRCA2 and MR041 is PTEN null, making them appropriate candidates for combination with PARP and AKT inhibitors, respectively. The PK module of the model describes the compound exposure in monotherapy and combination. The PD module describes the AR, AKT, GSK3β and S6 total and phosphorylated levels measured by Western Blotting and PARylation levels measured by ELISA. In the efficacy module, the levels of AR, pS6 and PARylation were linked to tumor growth inhibition while pGSK3β and PARylation levels were linked to induction of apoptosis; subsequently, these parameters determine the tumor size. All model parameters were derived from internal studies; some were estimated using Non-Linear Mixed Effect modeling of individual longitudinal PK, PD biomarkers and tumor size data taken from several studies. The model describes well the relationship between plasma concentration of the different compounds and PD biomarkers modulation both in monotherapy and in combination. Furthermore, the mathematical model is capable of explaining the enhanced anti-tumor efficacy in combination as a function of the different biomarkers’ modulation. This study provides quantitative mechanistic insights into the AZD9750 combination with AKT and PARP inhibitors. The study enriches our understanding of biomarkers relevant to AR-PROTACs, PARP inhibitors, and AKT inhibitors, informing the selection of biomarkers for monitoring in clinical trials. Additionally, it quantifies the extent of biomarker modulation required to achieve maximal antitumor activity and supports rational combination strategies, as well as dose and schedule optimization for clinical development.
Disclosure
A. Quiroga, AstraZeneca Employment, Stock, Stock Option. P. Morentin Gutierrez, AstraZeneca Employment, Stock, Stock Option. A. Ramos-Montoya, AstraZeneca Employment, Stock, Stock Option. C. Michaloglou, AstraZeneca Employment, Stock, Stock Option. N. Galeano-Dalmau, AstraZeneca Employment, Stock, Stock Option. C. Crafter, AstraZeneca Employment, Stock, Stock Option. A. Smith, AstraZeneca Employment, Stock, Stock Option. J. Scott, AstraZeneca Employment, Stock, Stock Option. M. Niedbala, AstraZeneca Employment, Stock, Stock Option.
Cited in
Control: 3697 · Presentation Id: 8718 · Meeting 21436