Physiological approaches to the prediction of drug-drug interactions in study populations

被引:13
作者
Chien, JY [1 ]
Mohutsky, MA [1 ]
Wrighton, SA [1 ]
机构
[1] Lilly Corp Ctr, Lilly Res Labs, Drug Disposit, Indianapolis, IN 46285 USA
关键词
drug-drug interactions; physiologically based pharmacokinetic modeling; PBPK; prediction; modeling; simulation;
D O I
10.2174/1389200033489307
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The prediction of metabolic drug-drug interactions should include quantitative attributes, such as variability in the study populations, and the results should be presented in terms of probability and uncertainty. The simple algebraic equations used to calculate one mean value for the extent of drug-drug interaction are adequate for qualitative or semi-quantitative risk assessment. However, truly quantitative predictions continue to fail. The success of drug-drug interaction predictions requires understanding of the relationship between drug disposition and quantifiable influential factors on the change in systemic exposure. The complex interplay of influential factors, including variability estimates, on successful prediction of drug interaction have not been systematically examined. Therefore, physiologically relevant models of metabolic drug-drug interaction will likely play increasingly important roles in improving quantitative predictions and in the assessment of the influential factors underlying the interactions. The physiologically-based approach, with stochastic considerations, offers a powerful alternative to the empirical calculation of mean values. In addition to quantitative estimation of the interaction for assessing probability of risk, a reasonably validated predictive model is useful for prospective optimization of study designs. As a consequence, the definitive clinical trial would yield more meaningful information to support dosing recommendations. This review focuses on illustrating the importance of an integrated approach to building useful models for prediction of metabolism-based drug-drug interactions in human subjects.
引用
收藏
页码:347 / 356
页数:10
相关论文
共 65 条
[1]   Role of modelling and simulation in Phase I drug development [J].
Aarons, L ;
Karlsson, MO ;
Mentré, F ;
Rombout, F ;
Steimer, JL ;
van Peer, A .
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2001, 13 (02) :115-122
[2]   Competitive CYP2C9 inhibitors:: Enzyme inhibition studies, protein homology modeling, and three-dimensional quantitative structure-activity relationship analysis [J].
Afzelius, L ;
Zamora, I ;
Ridderström, M ;
Andersson, TB ;
Karlén, A ;
Masimirembwa, CM .
MOLECULAR PHARMACOLOGY, 2001, 59 (04) :909-919
[4]   The influence of nonspecific microsomal binding on apparent intrinsic clearance, and its prediction from physicochemical properties [J].
Austin, RP ;
Barton, P ;
Cockroft, SL ;
Wenlock, MC ;
Riley, RJ .
DRUG METABOLISM AND DISPOSITION, 2002, 30 (12) :1497-1503
[5]   THE PHARMACOKINETICS OF KETOCONAZOLE AFTER CHRONIC ADMINISTRATION IN ADULTS [J].
BADCOCK, NR ;
BARTHOLOMEUSZ, FD ;
FREWIN, DB ;
SANSOM, LN ;
REID, JG .
EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY, 1987, 33 (05) :531-534
[6]   Development and validation of a 96-well equilibrium dialysis apparatus for measuring plasma protein binding [J].
Banker, MJ ;
Clark, TH ;
Williams, JA .
JOURNAL OF PHARMACEUTICAL SCIENCES, 2003, 92 (05) :967-974
[7]   Use of in vitro and in vivo data to estimate the likelihood of metabolic pharmacokinetic interactions [J].
Bertz, RJ ;
Granneman, GR .
CLINICAL PHARMACOKINETICS, 1997, 32 (03) :210-258
[8]   Prediction of the disposition of midazolam in surgical patients by a physiologically based pharmacokinetic model [J].
Björkman, S ;
Wada, DR ;
Berling, BM ;
Benoni, G .
JOURNAL OF PHARMACEUTICAL SCIENCES, 2001, 90 (09) :1226-1241
[9]  
BJORNSSON TD, 1950, J CLIN PHARMACOL, V43, P443
[10]  
Black DJ, 1996, DRUG METAB DISPOS, V24, P422