Population Pharmacokinetic/Pharmacodynamic Modeling of Tumor Size Dynamics in Pembrolizumab-Treated Advanced Melanoma

Abstract

Pembrolizumab is a potent immune‐modulating antibody active in advanced melanoma, as demonstrated in the KEYNOTE‐001, ‐002, and ‐006 studies. Longitudinal tumor size modeling was pursued to quantify exposure‐response relationships for efficacy. A mixture model was first developed based on an initial dataset from KEYNOTE‐001 to describe four patterns of tumor growth and shrinkage. For subsequent analyses, tumor size measurements were adequately described by a single consolidated model structure that captured continuous tumor size with a combination of growth and regression terms, as well as a fraction of tumor responsive to therapy. This revised model structure provided a framework to efficiently evaluate the impact of covariates and pembrolizumab exposure. Both models indicated that exposure to the drug was not a significant predictor of tumor size response, demonstrating that the dose range evaluated (2 and 10 mg/kg every 3 weeks) is likely near or at the plateau of maximal response.

Standard-dose pembrolizumab in combination with reduced-dose ipilimumab for patients with advanced melanoma (KEYNOTE-029): an open-label, phase 1b trial

“…At the time that this study was done, pembrolizumab 2 mg/kg every 3 weeks was the standard dose of pembrolizumab approved by the US Food and Drug Administration and European Medicines Agency on the basis of the results of pharmacokinetic analyses 23 and randomised dose comparisons showing similar efficacy and safety for both 2 mg/kg and 10 mg/kg every 3 weeks 4,7 and 10 mg/kg both every 2 weeks and 3 weeks. 6,7 The combination of standard-dose pembrolizumab with reduced-dose ipilimumab explored in this study was associated with higher toxicity than that reported for pembrolizumab or ipilimumab monotherapy.…”

Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling

“…The relation between treatment and response, either efficacy or safety, has been described to a lesser extent by mixture modeling despite the heterogeneous nature of such relationships. Tumor size data were initially modeled from pembrolizumab‐treated patients with melanoma using a mixture model with four subpopulations . This study demonstrated that both the initial mixture model and the later consolidated tumor‐size model were able to successfully describe the longitudinal tumor kinetics .…”

“…Tumor dynamics were modeled together with OS to identify biomarkers of efficacy in patients with durvalumab‐treated urothelial carcinoma . TB mixture modeling data were also reported in pembrolizumab‐treated patients with melanoma . Although each individual's TB‐time profile can differ by estimated interindividual variability in model parameters, the reported models with a unimodal parameter distribution do not adequately account for the heterogeneity in tumor response.…”

“…Tumor size data were initially modeled from pembrolizumab‐treated patients with melanoma using a mixture model with four subpopulations . This study demonstrated that both the initial mixture model and the later consolidated tumor‐size model were able to successfully describe the longitudinal tumor kinetics . However, the relationship between the characterized tumor growth (TG) and survival benefit was not reported.…”

Dose Finding Versus Speed in Seamless Immuno‐Oncology Drug Development

“…In addition to overall response rate, tumor size can be used as a continuous end point-enhancing the power of the exposure-response analysis, enabling dose comparisons with a reduced study size. 12 From a patient perspective, the goal of dose finding is not to characterize the entire dose-exposure-response curve, but instead to find a <MTD/MAD dose on the dose-exposure-response plateau-minimizing the likelihood of treating cancer patients at subtherapeutic exposures. Adaptive study designs can also be used to adjust the number of subjects per dose arm based on interim comparison of doses, for example, including the possibility of stopping the inferior dose arm.…”