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CompuSyn Report Examples

A. Drug Combination in Vitro

Am. J. Cancer Res. 6(1):97-104, 2016

www.ajcr.us /ISSN:2156-6976/ajcr0017635
Original Article
Synergistic combination of microtubule targeting anticancer fludelone with cytoprotective panaxytriol derived from panax ginseng against MX-1 cells in vitro: experimental design and data analysis using the combination index method

Ning Zhang, Jia-Ning Fu, and Ting-Chao Chou

Abstract: This brief article focuses on two aims: i) To investigate the in vitro pharmaco-dynamic interactions of combining synthetic potent microtubule targeting anticancer agent, Fludelone (FD) with cyto-protective agent, Panaxytriol (PXT) derived from Panax ginseng, and ii) To illustrate step-by-step operation for conducting two-drug combination in vitro using the combination index method, in terms of experimental design, data acquisition, computerized simulation and data interpretation. The Chou-Talalay method for drug combination is based on the median-effect equation, which provides the theoretical basis for the combination index (CI)-isobologram equation that allows quantitative determination of drug interactions, where CI<1, =1, and >1 indicates synergism, additive effect and antagonism, respectively. Based on these algorithms, computer software, CompySyn, is used for determining synergism and antagonism at all doses or effect levels simulated automatically. The use of Chou-Talalay’s CI method in quantifying synergism or antagonism is increasing steadily during the past two decades, however, confusing questions and pitfalls were still frequently raised by insufficient understanding of the theory, especially reflected when researchers trying to use the computerized software to design and conduct experiments.
In order to specifically address the confusions and to illustrate the practical features of this method, in this paper, a selected example is given based on our unpublished data regarding the combinational pharmacologic interactions of FD and PXT against the growth of breast cancer cell line MX-1. The step-by-step operation from experimental design to the real data analysis is illustrated. The results indicated that FD and PXT combination in vitro exerted synergistic effect when cell growth inhibition was greater than 45%, with CI ranged 0.836-0.609 for the fractional inhibition of Fa=0.50~0.90, as shown by the Fa-CI plot and by the isobologram. Thus, quantitative conclusion of synergism is obtained using the Chou-Talalay CI method, under the well-defined simple conditions for the FD and PXT combinations in vitro.

Example 1: In Vitro CompuSyn Report

B. Drug Combinations in Animals

Synergy 3: 15-30, 2016

Drug combination in vivo using combination index method: Taxotere and T607 against colon carcinoma HCT-116 xenograft tumor in nude mice

DOI: 10.1016/j.synres.2016.06.001

Jianing Fu, Ning Zhang, Joseph H. Chou, Hua-Jin Dong, Shu-Fu Lin, Gudrun S. Ulrich-Merzenich and Ting-Chao Chou

Abstract

The median-effect equation (MEE) of the mass-action law and the combination index (CI) theorem have been used for quantitative determination of synergism (CI <1), antagonism (CI >1) and additive effect (CI = 1) in animals in vivo. Experimental design, the theoretical algorithm and the CompuSyn software simulation have been used to illustrate step-by-step for the combination of two anti-cancer agents, Taxotere and T607 compound, with similar mode of actions of targeting microtubule polymerization, but with distinct chemical structures. These two compounds acted synergistically against human colon carcinoma HCT-116 xenograft tumor in athymic nude mice. In all, only 78 nude mice (10 averaged data points) have been used. The synergy is especially significant (p < 0.01-0.05) following Q3Dx4, x3 i.v. treatments, at higher doses and at later stages of treatment. The MEE and the CI theorem of Chou-Talalay quantitatively determined synergism or antagonism at different doses and different effect levels as indicated by the Fa-CI plot and by isobolograms in CompuSyn simulation and automated graphics. The practical logistics on pre-experimental planning, scheme/design/layout, and precautions in terms of dose number, dose range, dose density, drug combination ratio, conservation of laboratory animals as well as regulatory and cost-effective considerations have been presented. The mass-action law based CI algorithm has been proven to be simple to use, economy to practice, even for in vivo experimentations. Most significantly, the mass-action law based algorithm provides quantitative indexed conclusions.

Example 2: In Animal CompuSyn Report

C. References for Further Q&A