Lj. Cohen et Cl. Devane, CLINICAL IMPLICATIONS OF ANTIDEPRESSANT PHARMACOKINETIC AND PHARMACOGENETICS, The Annals of pharmacotherapy, 30(12), 1996, pp. 1471-1480
OBJECTIVE: TO review available data on pharmacokinetic and pharmacogen
etic influences on the response to antidepressant therapy, analyze the
mechanisms for and clinical significance of pharmacokinetic and pharm
acogenetic differences, and explain the implications of pharmacokineti
cs and pharmacogenetics for patient care. DATA SOURCES: A MEDLlNE sear
ch of English-language clinical studies, abstracts, and review article
s on antidepressant pharmacokinetics, pharmacogenetics, and drug inter
actions was used to identify pertinent literature. DATA SYNTHESIS: The
pharmacokinetic profiles of selected antidepressants are reviewed and
the impact of hepatic microsomal enzymes on antidepressant metabolism
is considered. How phenotypic differences influence the metabolism of
antidepressant drug therapy is addressed. To evaluate the clinical im
plications of these pharmacokinetic and pharmacogenetic considerations
, the findings of studies designed to elucidate drug interactions invo
lving antidepressant agents are discussed. CONCLUSIONS: Differences in
antidepressant plasma concentrations, and possibly safety, are caused
by polymorphism in the genes that encode some of the cytochrome P450
isoenzymes that metabolize antidepressants. The isoenzymes 1A2, 2C9/19
, 2D6, and 3A4 are the major enzymes that catalyze antidepressant meta
bolic reactions. Antidepressants can be tither substrates or inhibitor
s of these enzymes, which also metabolize many other pharmacologic age
nts. Although the cytochrome enzymes that metabolize antidepressants h
ave not been fully characterized, interaction profiles of the newer an
tidepressants are becoming more clearly defined. Determining patient p
henotypes is not practical in the clinical setting, but an awareness o
f the possibility of genetic polymorphism in antidepressant metabolism
may help explain therapeutic failure or toxicity, help predict the li
kelihood of drug interactions, and help clinicians better manage antid
epressant drug therapy.