Michel Tod1,2,3, Laurent Bourguignon4,5,6, Nathalie Bleyzac7, Sylvain Goutelle4,5,6. 1. Pharmacie, Groupement Hospitalier Nord, Hospices Civils de Lyon, Lyon, France. michel.tod@univ-lyon1.fr. 2. EMR3738, Faculté de médecine Lyon-sud, Université Lyon 1, BP 12, Chemin du grand revoyet, 69921, Oullins, France. michel.tod@univ-lyon1.fr. 3. Faculté de pharmacie, Université Lyon 1, Lyon, France. michel.tod@univ-lyon1.fr. 4. Pharmacie, Groupement Hospitalier Nord, Hospices Civils de Lyon, Lyon, France. 5. Faculté de pharmacie, Université Lyon 1, Lyon, France. 6. UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, Lyon, France. 7. EMR3738, Faculté de médecine Lyon-sud, Université Lyon 1, BP 12, Chemin du grand revoyet, 69921, Oullins, France.
Abstract
BACKGROUND: The in vivo mechanistic static model (IMSM) is an effective method to predict the magnitude of drug-drug interactions (DDIs) mediated by cytochromes. OBJECTIVE: The aim of this study was to extend the IMSM paradigm to DDIs mediated by organic anion transporting polypeptide (OATP) 1Bs, breast cancer resistance protein (BCRP) and cytochrome 2C8. METHODS: First, a generic model for this kind of interaction was established, and a literature search was then conducted to retrieve the area under the concentration-time curve (AUC) ratio of a large set of DDIs involving OATP1B1, OATP1B3, BCRP and cytochromes 2C8 or 3A4. The model was fitted to the data to estimate the characteristic parameters (contribution ratios [CRs] and inhibition or induction potencies [IXs]) by nonlinear regression, and the model was qualified by external validation on a different dataset. Lastly, the model was used to identify the risks of overexposure by DDIs of this type. RESULTS: A total of 27 substrates, 26 inhibitors, 3 inducers and 3 genetic variants were considered in the regression analysis. The number of observations (AUC ratios, denoted as Robs) was 101. Forty-six CRs and 47 IXs were estimated. The proportions of predictions within 0.67- to 1.5-fold and 0.5- to twofold Robs were 90% and 99%, respectively, for the internal validation, and 78% and 96%, respectively, for the external validation. The median fold-error was 1.03 (the ideal value is 1). The interquartile range of fold-error was 0.31, and the relative standard error of parameter estimates was, at most, 17%. CONCLUSIONS: The IMSM approach was successfully extended to DDIs mediated by OATP1Bs, BCRP and cytochromes 2C8 or 3A4. The method revealed good predictive performances by internal and external validation.
BACKGROUND: The in vivo mechanistic static model (IMSM) is an effective method to predict the magnitude of drug-drug interactions (DDIs) mediated by cytochromes. OBJECTIVE: The aim of this study was to extend the IMSM paradigm to DDIs mediated by organic anion transporting polypeptide (OATP) 1Bs, breast cancer resistance protein (BCRP) and cytochrome 2C8. METHODS: First, a generic model for this kind of interaction was established, and a literature search was then conducted to retrieve the area under the concentration-time curve (AUC) ratio of a large set of DDIs involving OATP1B1, OATP1B3, BCRP and cytochromes 2C8 or 3A4. The model was fitted to the data to estimate the characteristic parameters (contribution ratios [CRs] and inhibition or induction potencies [IXs]) by nonlinear regression, and the model was qualified by external validation on a different dataset. Lastly, the model was used to identify the risks of overexposure by DDIs of this type. RESULTS: A total of 27 substrates, 26 inhibitors, 3 inducers and 3 genetic variants were considered in the regression analysis. The number of observations (AUC ratios, denoted as Robs) was 101. Forty-six CRs and 47 IXs were estimated. The proportions of predictions within 0.67- to 1.5-fold and 0.5- to twofold Robs were 90% and 99%, respectively, for the internal validation, and 78% and 96%, respectively, for the external validation. The median fold-error was 1.03 (the ideal value is 1). The interquartile range of fold-error was 0.31, and the relative standard error of parameter estimates was, at most, 17%. CONCLUSIONS: The IMSM approach was successfully extended to DDIs mediated by OATP1Bs, BCRP and cytochromes 2C8 or 3A4. The method revealed good predictive performances by internal and external validation.
Authors: Hannah M Jones; Hugh A Barton; Yurong Lai; Yi-An Bi; Emi Kimoto; Sarah Kempshall; Sonya C Tate; Ayman El-Kattan; J Brian Houston; Aleksandra Galetin; Katherine S Fenner Journal: Drug Metab Dispos Date: 2012-02-16 Impact factor: 3.922
Authors: Md Jahangir Alam; Ryota Takahashi; Said M Afify; Aung Ko Ko Oo; Kazuki Kumon; Hend M Nawara; Aprilliana Cahya Khayrani; Juan Du; Maram H Zahra; Akimasa Seno; David S Salomon; Masaharu Seno Journal: Int J Mol Sci Date: 2018-10-26 Impact factor: 5.923