Optimal Scheduling of Bevacizumab and Pemetrexed/cisplatin Dosing in Non-Small Cell Lung Cancer

Schneider, Benjamin; Boyer, Arnaud; Ciccolini, Joseph; Wang, Kenneth; Benzekry, Sébastien; Mochel, Jonathan P.

doi:10.1101/540849

Cited by 2 publications

(3 citation statements)

References 49 publications

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“…The identification of an optimal drug-dosing schedule of targeted therapy combinations remains a challenge due to a large number of possible drug administration schedules as well as overlapping toxicity profiles. To address this problem, several computational strategies have been proposed [12][13][14][15] . Most approaches have adopted a tumor evolution model with resistant cell clones in different patient groups 13,16,17 , yet few account for the complex pharmacokinetics and the inter-patient variability of drug concentrations identified from large patient cohorts.…”

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confidence: 99%

Identification of optimal dosing schedules of dacomitinib and osimertinib for a phase I/II trial in advanced EGFR-mutant non-small cell lung cancer

et al. 2021

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Despite the clinical success of the third-generation EGFR inhibitor osimertinib as a first-line treatment of EGFR-mutant non-small cell lung cancer (NSCLC), resistance arises due to the acquisition of EGFR second-site mutations and other mechanisms, which necessitates alternative therapies. Dacomitinib, a pan-HER inhibitor, is approved for first-line treatment and results in different acquired EGFR mutations than osimertinib that mediate on-target resistance. A combination of osimertinib and dacomitinib could therefore induce more durable responses by preventing the emergence of resistance. Here we present an integrated computational modeling and experimental approach to identify an optimal dosing schedule for osimertinib and dacomitinib combination therapy. We developed a predictive model that encompasses tumor heterogeneity and inter-subject pharmacokinetic variability to predict tumor evolution under different dosing schedules, parameterized using in vitro dose-response data. This model was validated using cell line data and used to identify an optimal combination dosing schedule. Our schedule was subsequently confirmed tolerable in an ongoing dose-escalation phase I clinical trial (NCT03810807), with some dose modifications, demonstrating that our rational modeling approach can be used to identify appropriate dosing for combination therapy in the clinical setting.

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confidence: 99%

Identification of optimal dosing schedules of dacomitinib and osimertinib for a phase I/II trial in advanced EGFR-mutant non-small cell lung cancer

et al. 2021

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“…Previously, we have shown experimentally and described mathematically the time-course of this transient perfusion-normalization in a xenograft-murine model of NSCLC (9). In that experiment, pemetrexed-cisplatin (PEM/CIS) was administered sequentially with bevacizumab (BEV).…”

Section: Introductionmentioning

confidence: 97%

“…This variation can be an advantage of pooling datasets from separate trials if the statistical framework for analysis is able to account for and elucidate any potential sources of variation. Non-linear mixed effects (NLME) modeling of tumor proliferation and response is a proven framework for pooling data to model-build (9,11,12)…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Joint Modeling of First-Line Therapeutics in Non-Small Cell Lung Cancer

Benzekry

Mochel

2020

Preprint

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First-line antiproliferatives for non-small cell lung cancer (NSCLC) have a relatively high failure rate due to high intrinsic resistance rates and acquired resistance rates to therapy. 57% patients are diagnosed in late-stage disease due to the tendency of early-stage NSCLC to be asymptomatic. For patients first diagnosed with metastatic disease the 5-year survival rate is approximately 5%. To help accelerate the development of novel therapeutics and computer-based tools for optimizing individual therapy, we have collated data from 11 different clinical trials in NSCLC and developed a semi-mechanistic, clinical model of NSCLC growth and pharmacodynamics relative to the various therapeutics represented in the study. In this study, we have produced extremely precise estimates of clinical parameters fundamental to cancer modeling such as the rate of acquired resistance to various pharmaceuticals, the relationship between drug concentration and rate of cancer cell death, as well as the fine temporal dynamics of anti-VEGF therapy. In the simulation sets documented in this study, we have used the model to make meaningful descriptions of efficacy gain in making bevacizumab-antiproliferative combination therapy sequential, over a series of days, rather than concurrent.

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Optimal Scheduling of Bevacizumab and Pemetrexed/cisplatin Dosing in Non-Small Cell Lung Cancer

Cited by 2 publications

References 49 publications

Identification of optimal dosing schedules of dacomitinib and osimertinib for a phase I/II trial in advanced EGFR-mutant non-small cell lung cancer

Identification of optimal dosing schedules of dacomitinib and osimertinib for a phase I/II trial in advanced EGFR-mutant non-small cell lung cancer

Comprehensive Joint Modeling of First-Line Therapeutics in Non-Small Cell Lung Cancer

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