Dear Tanvir,

You may read the following:

1-Drug Metab Dispos. 2000 Apr;28(4):467-74.

Prediction of in vivo drug-drug interactions based on mechanism-based inhibition from in vitro data: inhibition of 5-fluorouracil metabolism by (E)-5-(2-Bromovinyl)uracil.

Kanamitsu SI1, Ito K, Okuda H, Ogura K, Watabe T, Muro K, Sugiyama Y.

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1Graduate School of Pharmaceutical Sciences, University of Tokyo, Tokyo, Japan.

Abstract

The fatal drug-drug interaction between sorivudine, an antiviral drug, and 5-fluorouracil (5-FU) has been shown to be caused by a mechanism-based inhibition. In this interaction, sorivudine is converted by gut flora to (E)-5-(2-bromovinyl)uracil (BVU), which is metabolically activated by dihydropyrimidine dehydrogenase (DPD), and the activated BVU irreversibly binds to DPD itself, thereby inactivating it. In an attempt to predict this interaction in vivo from in vitro data, inhibition of 5-FU metabolism by BVU was investigated by using rat and human hepatic cytosol and human recombinant DPD. Whichever enzyme was used, increased inhibition was observed that depended on the preincubation time of BVU and enzyme in the presence of NADPH and BVU concentration. The kinetic parameters obtained for inactivation represented by k(inact) and K'(app) were 2.05 +/- 1.52 min(-1), 69.2 +/- 60.8 microM (rat hepatic cytosol), 2.39 +/- 0.13 min(-1), 48.6 +/- 11.8 microM (human hepatic cytosol), and 0.574 +/- 0.121 min(-1), 2.20 +/- 0.57 microM (human recombinant DPD). The drug-drug interaction in vivo was predicted quantitatively based on a physiologically based pharmacokinetic model, using pharmacokinetic parameters obtained from the literature and kinetic parameters for the enzyme inactivation obtained in the in vitro studies. In rats, DPD was predicted to be completely inactivated by administration of BVU and the area under the curve of 5-FU was predicted to increase 11-fold, which agreed well with the reported data. In humans, a 5-fold increase in the area under the curve of 5-FU was predicted after administration of sorivudine, 150 mg/day for 5 days. Mechanism-based inhibition of drug metabolism is supposed to be very dangerous. We propose that such in vitro studies should be carried out during the drug-developing phase so that in vivo drug-drug interactions can be predicted.

http://www.ncbi.nlm.nih.gov/pubmed/10725316

2-J Young Pharm. 2010 Apr-Jun; 2(2): 196–200.

doi:  10.4103/0975-1483.63169

PMCID: PMC3021697

In vivo and In vitro Drug Interactions Study of Glimepride with Atorvastatin and Rosuvastatin

VJ Galani and M Vyas

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Abstract

Aim of this investigation was to study the in vivo and in vitro drug interaction of glimepride with atorvastatin and rosuvastatin. In vitro drug interaction of glimepride with atorvastatin and rosuvastatin was studied using human pooled liver microsomes and evaluated using high performance liquid chromatography. In vivopharmacokinetic drug interaction of glimepride (6 mg/kg) in coadministration with atorvastatin (60 mg/kg) and rosuvastatin (60 mg/kg) were studied in rats and analyzed using liquid chromatography tandem mass spectrometry (LC–MS/MS). In in vitro study, atorvastatin decreased its own metabolism as well as the metabolism of glimepiride. Rosuvastatin coadministration with glimepride reduced the metabolism of glimepride and increased the metabolism of its own. In in vivo study, concentration in plasma, Cmax, AUC(0–t) and AUC(0–∞) (area under the concentration-time curve, AUC) of glimepride was increased significantly in coadministration with atorvastatin whereas there was no significant change was observed in the case of coadministration with rosuvastatin. Half life (T1/2) and volume of distribution (Vd) of glimepride decreased significantly with both atorvastatin and rosuvastatin. Elimination rate constant, Kel of glimepride increased significantly with both atorvastatin and rosuvastatin. Clearance (Cl) of glimepride decreased significantly but the decrease was more with atorvastatin than with rosuvastatin. It is concluded that glimepride metabolism is little affected by rosuvastatin in vitro, which agreed with the negligible interaction in in vivo study. Thus, from safety point of view rosuvastatin is better to prescribe as a coadministration therapy with glimepiride. On the other hand, atorvastatin could cause an increase in the bioavailability of glimepride per oral and also significantly decrease the metabolism of glimerpride in in vitro study. This may pose a positive implication in clinical practice.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3021697/

3-AAPS J. 2013 Jul; 15(3): 629–645.

Published online 2013 Mar 30. doi:  10.1208/s12248-013-9470-x

PMCID: PMC3691435

Drug–Drug Interaction Studies: Regulatory Guidance and An Industry Perspective

Thomayant Prueksaritanont, Xiaoyan Chu, Christopher Gibson, Donghui Cui, Ka Lai Yee, Jeanine Ballard, Tamara Cabalu, and Jerome Hochman

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Abstract

Recently, the US Food and Drug Administration and European Medicines Agency have issued new guidance for industry on drug interaction studies, which outline comprehensive recommendations on a broad range of in vitro and in vivo studies to evaluate drug–drug interaction (DDI) potential. This paper aims to provide an overview of these new recommendations and an in-depth scientifically based perspective on issues surrounding some of the recommended approaches in emerging areas, particularly, transporters and complex DDIs. We present a number of theoretical considerations and several case examples to demonstrate complexities in applying (1) the proposed transporter decision trees and associated criteria for studying a broad spectrum of transporters to derive actionable information and (2) the recommended model-based approaches at an early stage of drug development to prospectively predict DDIs involving time-dependent inhibition and mixed inhibition/induction of drug metabolizing enzymes. We hope to convey the need for conducting DDI studies on a case-by-case basis using a holistic scientifically based interrogative approach and to communicate the need for additional research to fill in knowledge gaps in these areas where the science is rapidly evolving to better ensure the safety and efficacy of new therapeutic agents.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691435/

4-Methods of Drug Interaction Studies

http://www.nihs.go.jp/phar/pdf/DiGlEngFinal011209.pdf

5-Drug–Drug Interactions Mediated Through

P-Glycoprotein: Clinical Relevance and In Vitro–In Vivo Correlation Using Digoxin as a Probe Drug

KS Fenner1, MD Troutman2, S Kempshall1, JA Cook3, JA Ware4,6, DA Smith1 and CA Lee5

The clinical pharmacokinetics and in vitro inhibition of digoxin were examined to predict the P-glycoprotein (P-gp) component of drug–drug interactions. Coadministered drugs (co-meds) in clinical trials (N = 123) resulted in a small,

≤100% increase in digoxin pharmacokinetics. Digoxin is likely to show the highest perturbation, via inhibition of P-gp, because of the absence of metabolic clearance. In vitro inhibitory potency data (concentration of inhibitor to inhibit 50% P-gp activity; IC50) were generated using Caco-2 cells for 19 P-gp inhibitors. Maximum steady-state inhibitor systemic concentration [I], [I]/IC50 ratios, hypothetical gut concentration ([I 2], dose/250ml), and [I 2]/IC50 ratios were calculated to

simulate systemic and gut-based interactions and were compared with peak plasma concentration (Cmax) ,i,ss/Cmax,ss and area under the curve (AUC)i

/AUC ratios from the clinical trials. [I]/IC50 < 0.1 shows high false-negative rates (24% AUC, 41% Cmax); however, to a limited extent, [I

2]/IC50 < 10 is predictive of negative digoxin interaction for AUC, and [I]/IC50 > 0.1 is predictive of clinical digoxin interactions (AUC and Cmax).

http://www.isdbweb.org/documents/file/1519_5.pdf

Hoping this will be helpful,

Rafik

Thank you,Rafik karaman. These articles are helpfull.