Literature DB >> 9865733

Modeling of the time-dependency of in vitro drug cytotoxicity and resistance.

L M Levasseur1, H K Slocum, Y M Rustum, W R Greco.   

Abstract

For potential clinical extrapolation of in vitro findings, it is of interest to relate the measured effect of an anticancer agent to concentration and exposure time. The Hill model (A. V. Hill, J. Physiol., 40: iv-vii, 1910) is commonly used to describe pharmacodynamic (PD) effects, including drug-induced growth inhibition of cancer cells in vitro. The IC(X)n x T = k relationship, in which IC(X) is the concentration of agent required to reduce cell growth by X%, T is the exposure time, and n and k are estimable parameters, was first applied to bacterial disinfectant action and then was successfully used to model anticancer drug potency as a function of exposure time (D. J. Adams, Cancer Res., 49: 6615-6620, 1989). Our goal was to create a new global PD modeling paradigm to facilitate the quantitative assessment of the growth-inhibitory effect of anticancer agents as a function of concentration and exposure time. Wild-type human ovarian A2780 and ileocecal HCT-8 carcinoma cells and sublines that were resistant to cisplatin (A2780/CP3), doxorubicin (A2780/DX5B), and raltitrexed (RTX) (HCT-8/DW2) were exposed to various anticancer agents, cisplatin, doxorubicin, paclitaxel, trimetrexate, RTX, methotrexate, and AG2034, for periods ranging from 1 to 96 h. Cell growth inhibition was measured with the sulforhodamine B protein dye assay. Patterns of time-dependency of drug potency, slope of the concentration-effect curves, and relative degree of resistance were characterized. Empirical mathematical expressions were built into a global concentration-time-effect model. The global PD model was then fit to the concentration-time-effect data with iteratively reweighted nonlinear regression. Under specific treatment conditions, the examination of the slope and the shape of the concentration-effect curves revealed a large heterogeneity in drug response, e.g., shallow concentration-effect curve or double or triple Hill "roller coaster" concentration-effect curve. These patterns, which were observed at intermediate exposure times in parental and resistant cells for paclitaxel and trimetrexate or only in resistant HCT-8/DW2 cells for RTX, methotrexate, and AG2034, revealed mechanistic insights for the former cases but possible methodological artifacts for the latter cases. The comprehensive PD modeling of the cytotoxic effect of anticancer agents showed that it was possible to modulate drug effect, response heterogeneity, and drug resistance by altering the time of exposure to the agents. This approach will be useful for: (a) describing complex concentration-time-effect surfaces; (b) refining biological interpretations of data; (c) providing insights on mechanisms of drug action and resistance; and (d) generating leads for clinical use of anticancer drugs.

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Year:  1998        PMID: 9865733

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  26 in total

1.  Implications for clinical pharmacodynamic studies of the statistical characterization of an in vitro antiproliferation assay.

Authors:  L M Levasseur; H Faessel; H K Slocum; W R Greco
Journal:  J Pharmacokinet Biopharm       Date:  1998-12

2.  A mathematical model for cisplatin cellular pharmacodynamics.

Authors:  Ardith W El-Kareh; Timothy W Secomb
Journal:  Neoplasia       Date:  2003 Mar-Apr       Impact factor: 5.715

3.  A theoretical model for intraperitoneal delivery of cisplatin and the effect of hyperthermia on drug penetration distance.

Authors:  Ardith W El-Kareh; Timothy W Secomb
Journal:  Neoplasia       Date:  2004 Mar-Apr       Impact factor: 5.715

4.  A new mathematical pharmacodynamic model of clonogenic cancer cell death by doxorubicin.

Authors:  Jan Lankelma; Rafael Fernández Luque; Henk Dekker; Jaap van den Berg; Bob Kooi
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5.  Cell cycle checkpoint models for cellular pharmacology of paclitaxel and platinum drugs.

Authors:  Ardith W El-Kareh; Rachel E Labes; Timothy W Secomb
Journal:  AAPS J       Date:  2008-02-05       Impact factor: 4.009

Review 6.  Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection.

Authors:  S Sadekar; I Figueroa; M Tabrizi
Journal:  AAPS J       Date:  2015-05-02       Impact factor: 4.009

Review 7.  Array of translational systems pharmacodynamic models of anti-cancer drugs.

Authors:  Sihem Ait-Oudhia; Donald E Mager
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-10-22       Impact factor: 2.745

8.  Chemotherapeutic dosing implicated by pharmacodynamic modeling of in vitro cytotoxic data: a case study of paclitaxel.

Authors:  Hua He; Yanguang Cao
Journal:  J Pharmacokinet Pharmacodyn       Date:  2017-08-31       Impact factor: 2.745

9.  Pharmacodynamic modeling of chemotherapeutic effects: application of a transit compartment model to characterize methotrexate effects in vitro.

Authors:  Evelyn D Lobo; Joseph P Balthasar
Journal:  AAPS PharmSci       Date:  2002

Review 10.  Nanovehicular intracellular delivery systems.

Authors:  Ales Prokop; Jeffrey M Davidson
Journal:  J Pharm Sci       Date:  2008-09       Impact factor: 3.534

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