Abstract 4348: A translational pharmacokinetic-pharmacodynamic (PKPD) modeling framework of novel, highly selective, next-generation allosteric cyclin-dependent kinase 2 (CDK2) inhibitors
Abstract Background: CDK2 plays a crucial role in regulating multiple oncogenic signaling pathways, and its activity is essential for the loss of growth control during cancer development. The amplification and overexpression of the CDK2 binding partner Cyclin E1 (CCNE1) is a key mechanism in various cancers. Selective CDK2/CCNE1 inhibition therefore offers a promising treatment for patients with CCNE1 overexpressing tumors. CDK2/CCNE1 inhibition has been shown to reduce phosphorylation of the retinoblastoma protein (pRB), a direct downstream target, which is associated with decreased tumor growth in preclinical in vitro and in vivo models. Reduced levels of pRB have also been observed in patients treated with CDK2 inhibitors. We have developed a pharmacokinetic-pharmacodynamic (PKPD) model for CDK2 inhibitors and examine the relationship between dose, exposure, pRB and tumor growth, using published and in-house in vitro and in vivo data from several compounds, to support preclinical and clinical phases. Methods: Our PKPD model framework consists of in vitro and in vivo components. The in vitro model evaluates the relationship between compound concentrations and pRB levels as well as cell proliferation in CCNE1-overexpressing cell lines for multiple CDK2 inhibitors. The in vivo model describes compound exposure in plasma and tumor and the modulation of pRB, which is associated with changes in tumor growth. Model building and validation was informed by published literature on CDK2 inhibitors, in vitro data showing modulation of pRB and proliferation, and in vivo mouse data in CCNE1-overexpressing OVCAR3 xenografts, including plasma and tumor exposure, pRB measurements, and tumor growth inhibition data for different CDK2 inhibitors and dose levels. The model was developed using the MonolixSuite (Lixoft) software. Results: For the investigated CDK2 inhibitors a direct nonlinear model quantitatively characterizes the association of compound exposure and pRB levels, allowing the derivation of an IC50 from in vitro data for use in the in vivo model. The in vivo model describes plasma PK by a two-compartment model and tumor PK by an additional tumor compartment. The modulation of pRB levels by compound concentration in the tumor is described using an indirect response model and the in vitro derived IC50. Further, the reduction of pRB is linked to tumor growth inhibition using a Simeoni model. Diagnostic plots and model parameter estimates show that the in vitro and in vivo models well capture the complete data of the investigated CDK2 inhibitors, increasing confidence in the established model and applied hypotheses. Conclusion: We have established a translational PKPD modelling framework to support preclinical candidate selection, which will be evaluated in the clinical development of novel, next-generation CDK2 inhibitors. Citation Format: Andrea Gruber, Sven Christian, Carsten Schmeck, Antje Rottmann, Hongyu Xue, Marine Garrido, Mariya Pavlyuk, Bart Ploeger, Peter N. Morcos. A translational pharmacokinetic-pharmacodynamic (PKPD) modeling framework of novel, highly selective, next-generation allosteric cyclin-dependent kinase 2 (CDK2) inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4348.
Authors
- Bart A. Ploeger (ORCID: https://orcid.org/0000-0003-1183-7458)
- Carsten Schmeck
- Mariya Pavlyuk
- Sven Christian
- Andrea Grüber (ORCID: https://orcid.org/0000-0001-8298-5090)
- Hongyu Xue
- Marine F. Garrido
- Peter N. Morcos
- Antje Rottmann
Institutions
- Bayer (Germany) (DE)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-4348
- Citations
- 1
- Primary Topic
- Advanced Breast Cancer Therapies
- Type
- article
- Field-Weighted Citation Impact
- 1.52