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Detecting bliss synergy in in vivo combination studies with a tumor kinetic model
Author(s) -
Zhao Wei,
Vicini Paolo,
Novick Steven,
Anderton Judith,
Davies Gareth,
DAngelo Gina,
O'Day Terrance,
Yu Binbing,
Harper Jay,
Narwal Rajesh,
Roskos Lorin,
Yang Harry
Publication year - 2019
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1952
Subject(s) - in vivo , drug , linear model , mathematics , medicine , pharmacology , statistics , biology , microbiology and biotechnology
SUMMARY Linear models are generally reliable methods for analyzing tumor growth in vivo, with drug effectiveness being represented by the steepness of the regression slope. With immunotherapy, however, not all tumor growth follows a linear pattern, even after log transformation. Tumor kinetics models are mechanistic models that describe tumor proliferation and tumor killing macroscopically, through a set of differential equations. In drug combination studies, although an additional drug‐drug interaction term can be added to such models, however, the drug interactions suggested by tumor kinetics models cannot be translated directly into synergistic effects. We have developed a novel statistical approach that simultaneously models tumor growth in control, monotherapy, and combination therapy groups. This approach makes it possible to test for synergistic effects directly and to compare such effects among different studies.