Comparison of tumor size assessments in tumor growth inhibition-overall survival models with second-line colorectal cancer data from the VELOUR study

2018 ◽  
Vol 82 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Laurent Claret ◽  
Christina Pentafragka ◽  
Sanja Karovic ◽  
Binsheng Zhao ◽  
Lawrence H. Schwartz ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Tumor Growth ◽  
Growth Inhibition ◽  
Tumor Size ◽  
Survival Models ◽  
Tumor Growth Inhibition ◽  
Second Line ◽  
Cancer Data

A modeling framework to simulate motesanib efficacy in thyroid cancer

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e14553-e14553
Author(s):  
L. Claret ◽  
J. Lu ◽  
Y. Sun ◽  
D. Stepan ◽  
R. Bruno
Keyword(s):  
Thyroid Cancer ◽  
Tumor Growth ◽  
Growth Inhibition ◽  
Dose Response ◽  
Tumor Size ◽  
Clinical Development ◽  
Tumor Growth Inhibition ◽  
Population Pharmacokinetic ◽  
Modeling Framework ◽  
Dose Reductions

e14553 Background: Motesanib is a highly selective, oral inhibitor of VEGF receptors 1, 2, and 3; PDGFR, and Kit with antiangiogenic and direct antitumor activity. A modeling framework that simulates clinical endpoints, including objective response rate (ORR; per RECIST) and progression-free survival (PFS), was developed to support clinical development of motesanib. This study evaluated the framework using results from a trial of motesanib in thyroid cancer (TC). Methods: Models for tumor growth inhibition (J Clin Oncol 24[18S]:abstract 6025, 2006) with drug effect driven by area under the curve (AUC) (as predicted by a population pharmacokinetic model), overall survival, and probability and duration of dose reductions were developed based on data from 93 differentiated TC (DTC) and 91 medullary TC patients who received motesanib monotherapy (125 mg once daily [QD]) in a phase 2 study (Horm Res 68[suppl 3]:28–9, 2007; NEJM 359:31–42, 2008). The full simulation framework was assessed in predicting dose intensity (starting dose of 125 mg QD), tumor size over time, ORR, and PFS. Dose-response simulations were performed in DTC patients. Results: Survival times followed a Weibull distribution with ECOG performance status, baseline tumor size, and change in tumor size from baseline at week 7 as predictors. The probability of dose reductions was dependent on time and AUC. Time to event Weibull models predicted the duration of dose reductions and dose interruptions. The models correctly predicted median daily exposure intensities up to week 24. The predicted ORR in DTC patients was 15.0% (95% prediction interval [PI], 7.5%-23.7%) compared with the observed ORR of 14.0%. Predicted median PFS was 40 weeks (95% PI, 32–49 wk) compared with the observed median PFS of 40 weeks. Dose- response simulations confirmed the appropriateness of 125-mg QD dosing in DTC: the modeling framework predicted no clinically relevant improvement in PFS would be obtained by dose intensification. Conclusions: This modeling framework (dose reduction/tumor growth inhibition/survival) will be an important tool to simulate clinical response and support clinical development decisions. Further evaluation of the model using additional datasets will be required. [Table: see text]

scholarly journals A Model Relating Overall Survival to Tumor Growth Inhibition in Renal Cell Carcinoma

2014 ◽  
Vol 25 ◽  
pp. iv159
Author(s):  
F. Mercier ◽  
B. Houk ◽  
L. Claret ◽  
P. Milligan ◽  
R. Bruno
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Tumor Growth ◽  
Growth Inhibition ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Tumor Growth Inhibition

scholarly journals 826 Establishing the preclinical/translational PK/PD relationship for BT7480, a nectin-4/CD137 Bicycle tumor-targeted immune cell agonist™ (Bicycle TICA™)

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A865-A865
Author(s):  
Hitesh Mistry ◽  
Fernando Ortega ◽  
Fernando Ortega ◽  
Johanna Lahdenranta ◽  
Punit Upadhyaya ◽  
...  
Keyword(s):  
Growth Rate ◽  
Tumor Growth ◽  
Growth Inhibition ◽  
Drug Concentration ◽  
Tumor Size ◽  
Immune Cell ◽  
Compartment Model ◽  
Maximal Activity ◽  
Tumor Growth Inhibition

BackgroundA new class of modular synthetic drugs, termed Bicycle tumor-targeted immune cell agonists (Bicycle TICAs), based on constrained bicyclic peptides has been developed as agonists of immune costimulatory receptors in cancer therapeutics.1 One example is BT7480 which binds simultaneously to Nectin-4 on tumor cells and CD137 on primed immune cells with activation (agonism) of CD137 being dependent on co-ligation of Nectin-4.MethodsIn vitro CD137 reporter activity and cytokine secretion data were generated using Bicycle TICAs including BT7480. These Bicycle TICAs could display a concentration-dependent activation (e.g. CD137 activation increases IFN-gamma production) reaching a maximal activity, which then decreases as the drug concentration increases.2 We developed a mathematical model to analyse this behaviour.We also modelled plasma and tumor pharmacokinetics of BT7480 in CT26-Nectin-4 tumor-bearing mice. A two-compartment model described the drug plasma profile after intravenous dosing and the tumor profile was described by a one effect compartment model. A tumor growth inhibition model for BT7480 was used to describe the preclinical data by placing the model within a mixed effect framework to estimate the population model parameters, i.e., tumor size at time 0 and tumor size growth rate, and to predict the parameter values for each mouse. We assessed how the tumor growth rate values correlate with the immune system markers collected.ResultsWe assessed the predictions of the in vitro model against the experimental observations and found that the position of the turning point could be predicted from the dissociation constants (Kd's). The combined BT7480 pharmacokinetic model shows that the elimination rate from plasma is faster than that from the tumor. We hypothesized that this results from BT7480 binding to Nectin-4 in the tumor. Also, we found that the level of tumor infiltrating CD8+ T-cells fully captures the treatment effect of BT7480 on tumor growth. Therefore, we established a likely causal link: from pharmacokinetic/dose to CD8+ T-cell infiltration changes and ultimately to tumor growth inhibition.ConclusionsA PK/PD modelling framework was developed that predicts preclinical biomarker level and tumor growth inhibition in response to changes in the BT7480 dose and dosing schedule. In addition, plasma and tumor drug concentration levels can be associated with the target concentration estimated using in vitro data.2 Namely, the product of the square-root of the two target Kds is likely to be the free drug concentration at which maximal activity of the trimer [T-Cell—BT7480—Tumor-Cell] is achieved.ReferencesUpadhyaya P. Anticancer immunity induced by a synthetic tumor-targeted CD137 agonist. Journal for ImmunoTherapy of Cancer 2021;9:e001762.Perelson AS. Receptor clustering on a cell surface. III. theory of receptor cross-linking by multivalent ligands: description by ligand states. Mathematical Biosciences 1981;53:1–39.

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