A new probabilistic rule for drug-dug interaction prediction.
A new probabilistic rule for drug-dug interaction prediction.
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DOI：
10.1007/s10928-008-9107-3
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发表时间：
2009-02
影响因子：
2.5
通讯作者：
Li, Lang
中科院分区：
文献类型：
--
作者：
Zhou, Jihao;Qin, Zhaohui;Quinney, Sara K.;Kim, Seongho;Wang, Zhiping;Yu, Menggang;Chien, Jenny Y.;Lucksiri, Aroonrut;Hall, Stephen D.;Li, Lang
关键词：
提出了一种新的概率规则来预测DDI的临床意义或临床无意义。该规则与分层贝叶斯模型方法相结合，以总结来自多个已发表资源的底物/抑制剂PK模型。该方法将受试者间和研究间方差纳入DDI预测。因此，它可以预测群体平均和受试者特异性AUCR。有临床意义的DDI、弱DDI和无临床意义的抑制由预测AUCR落入三个区间（- ∞，1.25）、（1.25，2）和（2，∞）的概率决定。与确定性规则相比，该概率性规则预测DDI临床意义的主要优势在于概率性规则考虑了样本变异性，并且决策独立于样本变异性;而基于确定性规则的决策将因样本而异。本文提出的概率规则最适合于抑制剂和底物的体内PK研究和模型可用的情况。早期决定具有临床意义或无临床意义的抑制可以避免额外的DDI研究。酮康唑和咪达唑仑被用作相互作用对来说明我们的想法。结合受试者间变异性的AUCR预测值始终比群体平均AUCR预测值具有更大的方差。当考虑受试者间变异性时，人群平均水平下的临床不显著AUCR不一定正确。其他模拟研究表明，预测的AUCR高度依赖于相互作用常数Ki和剂量组合。
An innovative probabilistic rule is proposed to predict the clinical significance or clinical insignificance of DDI. This rule is coupled with a hierarchical Bayesian model approach to summarized substrate/inhibitor's PK models from multiple published resources. This approach incorporates between-subject and between-study variances into DDI prediction. Hence, it can predict both population-average and subject-specific AUCR. The clinically significant DDI, weak DDI, and clinically insignificant inhibition are decided by the probabilities of predicted AUCR falling into three intervals, (– ∞, 1.25), (1.25, 2), and (2, ∞). The main advantage of this probabilistic rule to predict clinical significance of DDI over the deterministic rule is that the probabilisticrule considers the sample variability, and the decision is independent of sampling variation; while deterministic rule based decision will vary from sample to sample. The probabilistic rule proposed in this paper is best suited for the situation when in vivo PK studies and models are available for both the inhibitor and substrate. An early decision on clinically significant or clinically insignificant inhibition can avoid additional DDI studies. Ketoconazole and midazolam are used as an interaction pair to illustrate our idea. AUCR predictions incorporating between-subject variability always have greater variances than population-average AUCR predictions. A clinically insignificant AUCR at population-average level is not necessarily true when considering between-subject variability. Additional simulation studies suggest thatpredicted AUCRs highly depend on the interaction constant Ki and dose combinations.
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DOI：
10.1208/ps040425
发表时间：
2002-01-01
期刊：
AAPS PHARMSCI
影响因子：
--
作者：
Ito, K;Chiba, K;Sugiyama, Y
通讯作者：
Sugiyama, Y
影响因子：
6.7
作者：
Lee, JI;Chaves-Gnecco, D;Frye, RF
通讯作者：
Frye, RF
DOI：
10.1016/j.ddtec.2004.10.002
发表时间：
2004-12-01
期刊：
Drug discovery today. Technologies
影响因子：
--
作者：
Rostami-Hodjegan, Amin;Tucker, Geoff
通讯作者：
Tucker, Geoff
影响因子：
4.1
作者：
Van, Linh M.;Heydari, Amir;Rostami-Hodjegan, Amin
通讯作者：
Rostami-Hodjegan, Amin
影响因子：
4.9
作者：
DANESHMEND, TK;WARNOCK, DW;WILLIAMSON, PJ
通讯作者：
WILLIAMSON, PJ