Birses Debir1, Andrzej M. Kierzek1, Kei Nishizawa2, Ragini Vuppugalla3, Rachel Rose1, Tomomi Matsuura1, Matthew Hruska3, Piet H. van der Graaf1, Douglas Marsteller3, Krina Mehta3
1Certara UK Ltd., 2Kyowa Kirin Co. Ltd., 3Kyowa Kirin Inc.
Introduction: KK2269 is a novel bispecific antibody that binds to CD40 on antigen presenting cells and epithelial cell adhesion molecule (EpCAM) on tumors. KK2269 exhibits anti-tumor activities through CD40 agonist activity only when it binds to both receptors, thus avoiding systemic toxicity related to CD40. We have previously developed a pharmacokinetic/target engagement model (PK-TE) of KK2269 calibrated the model with nonclinical data and applied this model to inform selection of Phase 1 dose range [1]. Here, we show integration of PK-TE model with the immune-oncology (IO) Simulator- a modular QSP platform model of the cancer immunity cycle in solid tumor [2]. The integrated model was applied to perform virtual trial simulation of KK2269 monotherapy and combination therapy with docetaxel in solid tumors. Methods: IO Simulator is being developed, maintained, and used in QSP Designer software [3]. We used the features of QSP Designer supporting modular development of mechanistic models to connect the KK2269 PK-TE model to the IO Simulator describing the mechanism of CD40-mediated immune activation in lymph node and tumor microenvironment. We used published in vitro and clinical trial data from an anti-CD40 antibody, Sotigalimab, to refine parameters describing the impact of CD40 activation on downstream immune markers and cytokines, including a.o. CD80, CD86, IL-12, IFN-?, TGF-ß. Next, we created virtual population based on literature data on the variability of baseline tumor size, tumor growth rate and leukocyte infiltrations in solid tumors. We leveraged the immune landscape of cancer database to incorporate leukocyte infiltrations in different solid tumors. Results: The IO Simulator was extended to incorporate CD40 activation and downstream effects. The relationship between CD40 engagement on antigen presenting cells and immune activation, as represented by activation of CD80, CD86 and IL-12 was quantified reasonably as suggested by observed vs. predicted diagnostics. The model was then connected to the KK2269 PK-TE model to predict KK2269 mediated CD40 activation. Virtual trial simulations suggested that the model reasonably predicts tumor size reduction observed in Sotigalimab monotherapy clinical trial [5]. Virtual trial simulations predicted tumor size reduction time profiles following KK2269 monotherapy and combination therapy with docetaxel in solid tumor patients. The model is applicable for learn-and-confirm cycle refinement with ongoing Phase 1 clinical study data [6] and is planned to be used to inform Phase 2 dose selection. Conclusions: We present a case study demonstrating the application of a large scale QSP platform model describing the cancer immunity cycle in solid tumor for efficacy prediction in early clinical development. We propose that bespoke QSP models integrated in such platforms describing the biology underlying disease and PK/TE models of a specific compound can be used as “drug companion models”, continuously refined by data available at given stage of drug development and applied to inform decisions for next stage [2].
1. Vuppugalla R, Mehta K, Debir B, Kierzek A, Takada H, Adachi M, Ishida H, Ando M, Kierzek A, Debir B, Marsteller D, Hruska M. Development of a Pharmacokinetic-Tumor Target Engagement Model Using Nonclinical Data to Inform Phase 1 Dosing Scheme for a Novel Bispecific CD40-EpCAM Antibody, KK2269. Poster Number: 087, Presented at American College of Clinical Pharmacology Annual Meeting. September 2024. Poster Number 087. https://accp1.org/pdfs/documents/annualmeeting/2024/CPDDv13iS1AbstractBooklet.pdf 2. Chelliah V, Lazarou G, Bhatnagar S, Gibbs JP, Nijsen M, Ray A, Stoll B, Thompson RA, Gulati A, Soukharev S, Yamada A, Weddell J, Sayama H, Oishi M, Wittemer-Rump S, Patel C, Niederalt C, Burghaus R, Scheerans C, Lippert J, Kabilan S, Kareva I, Belousova N, Rolfe A, Zutshi A, Chenel M, Venezia F, Fouliard S, Oberwittler H, Scholer-Dahirel A, Lelievre H, Bottino D, Collins SC, Nguyen HQ, Wang H, Yoneyama T, Zhu AZX, van der Graaf PH, Kierzek AM. Quantitative Systems Pharmacology Approaches for Immuno-Oncology: Adding Virtual Patients to the Development Paradigm. Clin Pharmacol Ther. 2021 Mar;109(3):605-618. doi: 10.1002/cpt.1987. Epub 2020 Aug 14. PMID: 32686076; PMCID: PMC7983940. 3. Matthews RJ, Hollinshead D, Morrison D, van der Graaf PH, Kierzek AM. QSP Designer: Quantitative systems pharmacology modeling with modular biological process map notation and multiple language code generation. CPT Pharmacometrics Syst Pharmacol. 2023 Jul;12(7):889-903. doi: 10.1002/psp4.12972. Epub 2023 May 4. PMID: 37452454; PMCID: PMC10349184. 4. Filbert EL, Björck PK, Srivastava MK, Bahjat FR, Yang X. APX005M, a CD40 agonist antibody with unique epitope specificity and Fc receptor binding profile for optimal therapeutic application. Cancer Immunol Immunother. 2021 Jul;70(7):1853-1865. doi: 10.1007/s00262-020-02814-2. Epub 2021 Jan 3. PMID: 33392713; PMCID: PMC8195934. 5. Johnson M, Fakih MG, Bendell JC, Bajor DL, Cristea MC, Tremblay TM, Trifan OC. First in Human Study with the CD40 Agonistic Monoclonal Antibody APX005M in Subjects with Solid Tumors. SITC 2017. Nov 8-12. National Harbor, MD. 6. Kyowa Kirin Co. Ltd. KK2269-001. A Study of KK2269 in Adult Participants With Solid Tumors. National Cancer Institute. NCT06266299. NCI-2024-08649. https://www.cancer.gov/research/participate/clinical-trials-search/v?id=NCI-2024-08649
Reference: PAGE 33 (2025) Abstr 11399 [www.page-meeting.org/?abstract=11399]
Poster: Drug/Disease Modelling - Oncology