Evidence that reveals interactions between smoker characteristics, medications and cessation success suggests that effective algorithms to assign medication may be possible. For example, there is evidence that the rate of nicotine metabolism predicts which smokers will be more successful at quitting with bupropion (BUP) [12] and with transdermal NRT [8,13], and that more highly dependent smokers benefit more from combination pharmacotherapies than do less dependent smokers [14]. Despite such findings, at present, no algorithm for the assignment of smoking cessation medication has been demonstrated to be useful in clinical practice and none is widely used. More research is needed on this topic. Nicotinic acetylcholine receptor (nAChR) locus single nucleotide polymorphisms (SNPs) have been related to measures of nicotine dependence [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42], response to tobacco [43,44,45] and smoking cessation [23,46,47,48,49,50,51,52] and, therefore, may prove useful in optimizing assignment of smoking cessation pharmacotherapies. We choose four nAChR SNPs among many possible nAChR SNPs with a priori evidence for an association with nicotine dependence, with response to nicotine or with smoking cessation. We choose these four based on substantial and repeated a priori evidence
