  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.
