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Quantitative prediction of drug-drug interactions resulting from cytochrome P450 inhibition using microsomes and hepatocytes
Başlık:
Quantitative prediction of drug-drug interactions resulting from cytochrome P450 inhibition using microsomes and hepatocytes
Yazar:
Brown, Hayley Susan, author.
ISBN:
9780438085039
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (285 pages)
Genel Not:
Source: Dissertation Abstracts International, Volume: 76-08C.
Özet:
Drug-drug interactions that result from cytochrome P450 inhibition are of major concern in the pharmaceutical industry since serious toxicities including fatalities have occurred, which have led to the withdrawal of a number of compounds from the market. Obviously, in vivo clinical interaction studies cannot be performed with every possible substrate and inhibitor pair, so the ability to quantitatively predict the extent of an in vivo interaction would be of great benefit. The accurate prediction of an in vivo interaction revolves around the inhibitor concentration at the enzyme active site along with its in vitro Ki value. The inhibitor concentration to which the P450 enzyme is exposed cannot be directly measured and there is no adequately validated model for the extrapolation of the measurable plasma concentration to the unbound cytosolic concentration within the liver. The unbound inhibitor concentration in the plasma does not necessarily reflect the unbound liver concentration for drugs that undergo concentrative or active uptake into the hepatocyte. The quantitative prediction of an in vivo interaction can therefore be very complex. This study was initiated from in vivo databases of clinical interaction studies along with databases of in vitro inhibition studies for CYP2C9 and CYP2D6. These databases were used to select inhibitors with a range of pharmacokinetic properties for further in vitro study. Four azole inhibitors (miconazole, sulphaphenazole, fluconazole and ketoconazole) were selected for study with the CYP2C9 probe substrate tolbutamide, whilst quinidine, quinine, fluoxetine and fluvoxamine were selected for CYP2D6 studies with dextromethorphan. Kinetic and inhibition studies were performed with each substrate-inhibitor pair using rat microsomes, freshly isolated rat hepatocytes and human microsomes, along with studies using cryopreserved human hepatocytes. The inhibition data were compared between both microsomes and hepatocytes in order to make an assessment of the inhibitor concentration within the cell and to identify the contribution of active transport and intracellular binding. Three of the inhibitors studied; miconazole, ketoconazole and fluoxetine are highly accumulated within the hepatocyte (cell to media ratios of 6000, 1200 and 2000, respectively). The results show that intracellular binding is the reason for the high intracellular accumulation of these compounds, with little evidence for active transport due to reasonably good agreement between Ki values obtained in both rat microsomes and hepatocytes. Comparable Ki values were also obtained between systems for the other compounds studied, with a difference in microsomal and hepatocyte Ki values of 1 to 2-fold (CYP2C9) and 0.5 to 3 fold (CYP2D6). Studies in human systems however showed approximately a 2 to 3 fold lower Ki value in hepatocytes compared to microsomes, suggesting a possible species difference in transport systems. The in vitro inhibition data obtained in human microsomes was incorporated into in vivo predictions utilising a number of different inhibitor concentrations and validation was achieved by comparison with data from human clinical interaction studies. It was found that by incorporating data on the fraction of the substrate metabolised by way of the inhibited enzyme, resulted in a more successful prediction for both the CYP2C9 and CYP2D6 interactions and while there was not one inhibitor concentration that provided the most accurate prediction for every inhibitor, the [I]average inhibitor concentration using refined Ki values was found to be the most successful overall, with the lowest number of overpredictions and more importantly, the lowest number of underpredictions.
Notlar:
School code: 1543
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(686921.1) | 686921-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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