Liang Zhao 1 , Jessie L-S Au 1 , M Guillaume Wientjes 2 . Show Affiliations »
Abstract
BACKGROUND: Commonly used methods for analyzing interactivity between drugs (e.g. synergy, antagonism) such as isobologram, combination index, and curve shift are based on the Loewe Additivity principle of dose equivalence and the inherent assumption of similar concentration- effect (C-E) including parallel curves and equal maximum effects (Emax), and therefore are not suitable for drugs with dissimilar C-E. This study describes a new method that is without this limitation and has the additional advantage of enabling statistical analysis. METHODS AND RESULTS: The method comprises two steps. First, based on the dose equivalence principle, the experimentally obtained C-E of one drug was used to calculate the equally effective C-E of the other drug at no interactivity; the resulting two zero-interactivity C-E formed the upper and lower boundaries of Additivity Envelope. Next, 95% confidence intervals calculated from experimental data were added to Additivity Envelope to obtain Uncertainty Envelope (UE). Experimentally observed effects of drug combinations (C-Ecomb,observed) located within UE indicate additivity whereas C-Ecomb,observed located above or below UE indicate statistically significant (p<0.05) synergy or antagonism, respectively. Additional in silico studies demonstrated the shape and size of Additivity Envelope, which determines the ability to detect drug interactivity, depended on the Drug A-to-B concentration ratios and the ratios of their C-E curve shape parameter. Analyses of experimental results of combinations of drugs with nonparallel C-E and/or unequal Emax indicated UE as more versatile and provided more information, compared to earlier methods. CONCLUSION: UE is a broadly applicable method for analysis, including statistical significance assessment, of drug interactivity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
BACKGROUND: C ommonly used methods for analyzing interac tivity between drugs (e.g. synergy, antagonism) suc h as isobologram, c ombination index, and c urve shift are based on the Loewe Additivity princ iple of dose equivalenc e and the inherent assumption of similar c onc entrat ion- effec t (C -E) inc luding parallel c urves and equal maximum effec ts (Emax ), and therefore are not suitable for drugs with dissimilar C -E. This study desc ribes a new method that is without this limitation and has the additional advantage of enabling statistic al analysis. METHODS AN D RESULTS: The method c omprises two steps. First, based on the dose equivalenc e princ iple, the experimentally obtained C -E of one drug was used to c alc ulate the equally effec tive C -E of the other drug at no interac tivity; the resulting two zero-interac tivity C -E formed the upper and lower bounda ries of Additivity Envelope. N ext, 95% c onfidenc e intervals c alc ulated from experimental da ta were added to Additivity Envelope to obtain Unc ertainty Envelope (UE). Experimentally observed effec ts of drug c ombinations (C-Ecomb ,observed) loc ated within UE indic ate additivity whereas C-Ecomb ,observed loc ated above or below UE indic ate statistic ally signific ant (p<0.05) synergy or antagonism, respec tively. Additional in silic o studies demonstrat ed the shape and size of Additivity Envelope, whic h determines the ability to detec t drug interac tivity, depended on the Drug A-to-B c onc entrat ion rat ios and the rat ios of their C -E c urve shape parameter. Analyses of experimental results of c ombinations of drugs with nonparallel C -E and/or unequal Emax indic ated UE as more versatile and provided more information, c ompared to earlier methods. CONCLUSION: UE is a broadly applic able method for analysis, inc luding statistic al signific anc e assessment, of drug interac tivity. C opyright© Bentham Sc ienc e Publishers; For any queries, please email at epub@benthamsc ienc e.org.
Entities: CellLine
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Keywords:
Combination therapy; antagonism; drug-drug interactivity; loewe-additivity; statistically significant synergy; uncertainty envelope
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Year: 2017
PMID: 28359247 PMCID: PMC5623138 DOI: 10.2174/1568009617666170330154054
Source DB: PubMed Journal: Curr Cancer Drug Targets ISSN: 1568-0096 Impact factor: 3.428