Abstract 2129
Background
We present a pharmacodynamic model that describes the tumor volume evolution during and after treatment with radiation and in combination with a radiosensitizing agent. A key contribution is the inclusion of a long-term radiation effect, which allows the model to describe distinct tumor behaviors including tumor eradication and tumor regrowth with different growth rates. Additionally, we introduce the concept of TSE (Tumor Static Exposure), the exposures of one or multiple compounds that result in tumor stasis and provide an example of its utility for optimizing drug combinations in oncology.
Methods
The model was challenged with data from four treatment groups (Vehicle, radiation, radiation + radiosensitizer 25 or 100 mg/kg) in xenograft study using a clinically-relevant administration schedule (6 weeks treatment, 5 days on/2 days off) and a mixed-effects approach was used for model-fitting. The model incorporated a permanent inhibition of the natural growth rate. This step was required to capture the complete tumor eradication and the observed tumor regrowth with different rates with animals having slower regrowth compared to control animals. The presence of a radiosensitizer will lead to the same tumor evolution as if a higher dose of radiation had been administered. The model was applied to predict exposure combinations that result in tumor eradication using the TSE.
Results
The developed model captured experimental data from all treatment groups adequately, with the parameter estimates taking biologically reasonable values. Model simulation showed that tumor eradication is observed at total radiation dose of 110 Gy, which is reduced to 80 or 30 Gy with co-administration of 25 or 100 mg/kg of a radiosensitizer.
Conclusions
The new model can describe different tumor dynamics including tumor eradication and tumor regrowth with different rates. The proposed model can be expanded for radiation in combination with chemical interventions or immunotherapy. The model and TSE can be applied to generate treatment predictions for different dosing schedules or determining drug synergies. The translational utility of the TSE concept is currently under investigation.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Merck Healthcare KGaA.
Funding
Tim Cardilin was supported by an education Grant from Merck Healthcare KGaA, Darmstadt, Germany. This work was also partially funded by the Swedish Foundation for Strategic Research (Grant no. AM13-0046).
Disclosure
S. El Bawab: Full / Part-time employment: Merck Healthcare KGaA. A. Zimmermann: Full / Part-time employment: Merck Healthcare KGaA. F. Lignet: Full / Part-time employment: Merck Healthcare KGaA. All authors have declared no conflicts of interest.
Resources from the same session
4614 - Predictors of Response to Checkpoint Inhibitors in Naïve and Ipilimumab-Refractory Melanoma
Presenter: Domenico Mallardo
Session: Poster Display session 3
Resources:
Abstract
2901 - IFN-γ/IL-10 ratio as predictive biomarker for response to anti-PD-1 therapy in metastatic melanoma patients
Presenter: Emilio Giunta
Session: Poster Display session 3
Resources:
Abstract
2306 - Multiplex Chromogenic Immunohistochemistry (IHC) for Spatial Analysis of Checkpoint-Positive Tumor Infiltrating Lymphocytes (TILs)
Presenter: Scott Ely
Session: Poster Display session 3
Resources:
Abstract
1678 - The role of PD-L1 expression as a predictive biomarker in advanced renal cell carcinoma: a meta-analysis of randomized clinical trials.
Presenter: Alberto Carretero-Gonzalez
Session: Poster Display session 3
Resources:
Abstract
5138 - Radiomic Features as a Non-invasive Biomarker to Predict Response to Immunotherapy in Recurrent or Metastatic Urothelial Carcinoma
Presenter: Kye Jin Park
Session: Poster Display session 3
Resources:
Abstract
5800 - Integrative combination of high-plex digital profiling techniques and cluster analysis to reveal complex immune biology in the tumor microenvironment of mesothelioma
Presenter: Carmen Ballesteros-Merino
Session: Poster Display session 3
Resources:
Abstract
5736 - Predictive factors of response to immunotherapy in 198 patients with metastatic non-microcytic lung cancer (mNSCLC): real world data from 2 university hospitals in Spain
Presenter: Juan Felipe Cordoba Ortega
Session: Poster Display session 3
Resources:
Abstract
5645 - Evaluating Lung CT Density Changes Among Patients with Extensive Stage Small Cell Lung Cancer (ES-SCLC) Treated with Thoracic Radiotherapy (TRT) alone or TRT Followed by Combined Ipilimumab (IPI) and Nivolumab (NIVO).
Presenter: Kujtim Latifi
Session: Poster Display session 3
Resources:
Abstract
1540 - Immuno-oncology therapy biomarkers differences between polyoma-virus positive and negative Merkel cell carcinomas
Presenter: Zoran Gatalica
Session: Poster Display session 3
Resources:
Abstract
4538 - Can we improve patient selection for phase 1 clinical trials (Ph1) based on Immuno-Oncology score prognostic index (VIO)?
Presenter: Ignacio Matos Garcia
Session: Poster Display session 3
Resources:
Abstract