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Preclinical Modeling of Combination Treatments: Fantasy or Requirement?
Author(s) -
DECKER SHAN,
SAUSVILLE EDWARD A.
Publication year - 2005
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1339.024
Subject(s) - fantasy , psychology , computer science , computational biology , biology , artificial intelligence
A bstract : Combination chemotherapy is considered the “norm” in cancer chemotherapy. While the development of classical combination regimens took into account factors such as single‐agent activity, different toxicity profiles, and advantageous pharmacology of the component drugs, in the era of targeted therapies there are additional considerations such as new mechanisms of resistance due to modulation of pathway dependence. Since it is not feasible to test all of the possible combinations clinically, some method for preclinically identifying and prioritizing promising combinations is necessary. While in vivo animal models can be used for safety testing and some pharmacokinetics, even they can quickly become prohibitively resource intensive for the purpose of efficacy determinations. Therefore, factors such as biologic rationale, reliable in vitro results in more than one tumor type, achievable in vivo pharmacology, and selectivity of primary tumor cell activity become important in the evaluation of potential combination regimens.